diff --git a/examples/nlp/active_learning_review_classification.py b/examples/nlp/active_learning_review_classification.py index 9aee8d8e1b..d6ec81780e 100644 --- a/examples/nlp/active_learning_review_classification.py +++ b/examples/nlp/active_learning_review_classification.py @@ -5,6 +5,7 @@ Last modified: 2024/05/08 Description: Demonstrating the advantages of active learning through review classification. Accelerator: GPU +Converted to Keras 3 by: [Sachin Prasad](https://github.com/sachinprasadhs) """ """ @@ -53,7 +54,7 @@ import os -os.environ["KERAS_BACKEND"] = "tensorflow" +os.environ["KERAS_BACKEND"] = "tensorflow" # @param ["tensorflow", "jax", "torch"] import keras from keras import ops from keras import layers @@ -100,18 +101,18 @@ # Creating training, validation and testing splits x_val, y_val = ( - ops.concatenate((x_positives[:val_split], x_negatives[:val_split]), 0), - ops.concatenate((y_positives[:val_split], y_negatives[:val_split]), 0), + tf.concat((x_positives[:val_split], x_negatives[:val_split]), 0), + tf.concat((y_positives[:val_split], y_negatives[:val_split]), 0), ) x_test, y_test = ( - ops.concatenate( + tf.concat( ( x_positives[val_split : val_split + test_split], x_negatives[val_split : val_split + test_split], ), 0, ), - ops.concatenate( + tf.concat( ( y_positives[val_split : val_split + test_split], y_negatives[val_split : val_split + test_split], @@ -120,14 +121,14 @@ ), ) x_train, y_train = ( - ops.concatenate( + tf.concat( ( x_positives[val_split + test_split : val_split + test_split + train_split], x_negatives[val_split + test_split : val_split + test_split + train_split], ), 0, ), - ops.concatenate( + tf.concat( ( y_positives[val_split + test_split : val_split + test_split + train_split], y_negatives[val_split + test_split : val_split + test_split + train_split], @@ -173,16 +174,8 @@ """ -def custom_standardization(input_data): - lowercase = tf.strings.lower(input_data) - stripped_html = tf.strings.regex_replace(lowercase, "
", " ") - return tf.strings.regex_replace( - stripped_html, f"[{re.escape(string.punctuation)}]", "" - ) - - vectorizer = layers.TextVectorization( - 3000, standardize=custom_standardization, output_sequence_length=150 + 3000, standardize="lower_and_strip_punctuation", output_sequence_length=150 ) # Adapting the dataset vectorizer.adapt( diff --git a/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1755.png b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1755.png new file mode 100644 index 0000000000..1e2f9de05d Binary files /dev/null and b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1755.png differ diff --git a/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1756.png b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1756.png new file mode 100644 index 0000000000..7b1eff2d96 Binary files /dev/null and b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_15_1756.png differ diff --git a/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2767.png b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2767.png new file mode 100644 index 0000000000..4ced9577e7 Binary files /dev/null and b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2767.png differ diff --git a/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2768.png b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2768.png new file mode 100644 index 0000000000..6252d9981c Binary files /dev/null and b/examples/nlp/img/active_learning_review_classification/active_learning_review_classification_17_2768.png differ diff --git a/examples/nlp/ipynb/active_learning_review_classification.ipynb b/examples/nlp/ipynb/active_learning_review_classification.ipynb index 6d89a406f1..5b25393f48 100644 --- a/examples/nlp/ipynb/active_learning_review_classification.ipynb +++ b/examples/nlp/ipynb/active_learning_review_classification.ipynb @@ -78,7 +78,7 @@ "source": [ "import os\n", "\n", - "os.environ[\"KERAS_BACKEND\"] = \"tensorflow\"\n", + "os.environ[\"KERAS_BACKEND\"] = \"tensorflow\" # @param [\"tensorflow\", \"jax\", \"torch\"]\n", "import keras\n", "from keras import ops\n", "from keras import layers\n", @@ -153,18 +153,18 @@ "\n", "# Creating training, validation and testing splits\n", "x_val, y_val = (\n", - " ops.concatenate((x_positives[:val_split], x_negatives[:val_split]), 0),\n", - " ops.concatenate((y_positives[:val_split], y_negatives[:val_split]), 0),\n", + " tf.concat((x_positives[:val_split], x_negatives[:val_split]), 0),\n", + " tf.concat((y_positives[:val_split], y_negatives[:val_split]), 0),\n", ")\n", "x_test, y_test = (\n", - " ops.concatenate(\n", + " tf.concat(\n", " (\n", " x_positives[val_split : val_split + test_split],\n", " x_negatives[val_split : val_split + test_split],\n", " ),\n", " 0,\n", " ),\n", - " ops.concatenate(\n", + " tf.concat(\n", " (\n", " y_positives[val_split : val_split + test_split],\n", " y_negatives[val_split : val_split + test_split],\n", @@ -173,14 +173,14 @@ " ),\n", ")\n", "x_train, y_train = (\n", - " ops.concatenate(\n", + " tf.concat(\n", " (\n", " x_positives[val_split + test_split : val_split + test_split + train_split],\n", " x_negatives[val_split + test_split : val_split + test_split + train_split],\n", " ),\n", " 0,\n", " ),\n", - " ops.concatenate(\n", + " tf.concat(\n", " (\n", " y_positives[val_split + test_split : val_split + test_split + train_split],\n", " y_negatives[val_split + test_split : val_split + test_split + train_split],\n", @@ -239,17 +239,9 @@ }, "outputs": [], "source": [ - "\n", - "def custom_standardization(input_data):\n", - " lowercase = tf.strings.lower(input_data)\n", - " stripped_html = tf.strings.regex_replace(lowercase, \"
\", \" \")\n", - " return tf.strings.regex_replace(\n", - " stripped_html, f\"[{re.escape(string.punctuation)}]\", \"\"\n", - " )\n", - "\n", "\n", "vectorizer = layers.TextVectorization(\n", - " 3000, standardize=custom_standardization, output_sequence_length=150\n", + " 3000, standardize=\"lower_and_strip_punctuation\", output_sequence_length=150\n", ")\n", "# Adapting the dataset\n", "vectorizer.adapt(\n", diff --git a/examples/nlp/md/active_learning_review_classification.md b/examples/nlp/md/active_learning_review_classification.md index bb3aa0133a..50beb42dc5 100644 --- a/examples/nlp/md/active_learning_review_classification.md +++ b/examples/nlp/md/active_learning_review_classification.md @@ -56,7 +56,7 @@ Selects data points closest to the decision boundary ```python import os -os.environ["KERAS_BACKEND"] = "tensorflow" +os.environ["KERAS_BACKEND"] = "tensorflow" # @param ["tensorflow", "jax", "torch"] import keras from keras import ops from keras import layers @@ -92,10 +92,6 @@ print("Total examples:", reviews.shape[0])
``` - Downloading and preparing dataset 80.23 MiB (download: 80.23 MiB, generated: Unknown size, total: 80.23 MiB) to /home/codespace/tensorflow_datasets/imdb_reviews/plain_text/1.0.0... - - Dataset imdb_reviews downloaded and prepared to /home/codespace/tensorflow_datasets/imdb_reviews/plain_text/1.0.0. Subsequent calls will reuse this data. - Total examples: 50000 ``` @@ -116,18 +112,18 @@ x_negatives, y_negatives = reviews[labels == 0], labels[labels == 0] # Creating training, validation and testing splits x_val, y_val = ( - ops.concatenate((x_positives[:val_split], x_negatives[:val_split]), 0), - ops.concatenate((y_positives[:val_split], y_negatives[:val_split]), 0), + tf.concat((x_positives[:val_split], x_negatives[:val_split]), 0), + tf.concat((y_positives[:val_split], y_negatives[:val_split]), 0), ) x_test, y_test = ( - ops.concatenate( + tf.concat( ( x_positives[val_split : val_split + test_split], x_negatives[val_split : val_split + test_split], ), 0, ), - ops.concatenate( + tf.concat( ( y_positives[val_split : val_split + test_split], y_negatives[val_split : val_split + test_split], @@ -136,14 +132,14 @@ x_test, y_test = ( ), ) x_train, y_train = ( - ops.concatenate( + tf.concat( ( x_positives[val_split + test_split : val_split + test_split + train_split], x_negatives[val_split + test_split : val_split + test_split + train_split], ), 0, ), - ops.concatenate( + tf.concat( ( y_positives[val_split + test_split : val_split + test_split + train_split], y_negatives[val_split + test_split : val_split + test_split + train_split], @@ -200,16 +196,8 @@ faster, we use the `map()` function with its parallelization functionality. ```python -def custom_standardization(input_data): - lowercase = tf.strings.lower(input_data) - stripped_html = tf.strings.regex_replace(lowercase, "
", " ") - return tf.strings.regex_replace( - stripped_html, f"[{re.escape(string.punctuation)}]", "" - ) - - vectorizer = layers.TextVectorization( - 3000, standardize=custom_standardization, output_sequence_length=150 + 3000, standardize="lower_and_strip_punctuation", output_sequence_length=150 ) # Adapting the dataset vectorizer.adapt( @@ -415,1102 +403,1102 @@ Epoch 1/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 7:25 3s/step - binary_accuracy: 0.5781 - false_negatives: 23.0000 - false_positives: 85.0000 - loss: 0.6887 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 7:18 3s/step - binary_accuracy: 0.5508 - false_negatives: 49.0000 - false_positives: 66.0000 - loss: 0.6905
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 13s 84ms/step - binary_accuracy: 0.5967 - false_negatives: 24.5000 - false_positives: 128.0000 - loss: 0.6865 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 12s 80ms/step - binary_accuracy: 0.5664 - false_negatives: 52.0000 - false_positives: 112.5000 - loss: 0.6886
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 12s 82ms/step - binary_accuracy: 0.6031 - false_negatives: 25.3333 - false_positives: 174.6667 - loss: 0.6848 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 12s 80ms/step - binary_accuracy: 0.5777 - false_negatives: 53.0000 - false_positives: 159.0000 - loss: 0.6869
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 12s 82ms/step - binary_accuracy: 0.6054 - false_negatives: 25.7500 - false_positives: 223.5000 - loss: 0.6839 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 12s 79ms/step - binary_accuracy: 0.5885 - false_negatives: 53.7500 - false_positives: 202.2500 - loss: 0.6846
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 12s 82ms/step - binary_accuracy: 0.6067 - false_negatives: 26.0000 - false_positives: 272.8000 - loss: 0.6831 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 78ms/step - binary_accuracy: 0.5957 - false_negatives: 54.4000 - false_positives: 246.6000 - loss: 0.6831
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 12s 81ms/step - binary_accuracy: 0.6080 - false_negatives: 26.1667 - false_positives: 321.5000 - loss: 0.6823 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 78ms/step - binary_accuracy: 0.6018 - false_negatives: 54.8333 - false_positives: 290.1667 - loss: 0.6815
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 80ms/step - binary_accuracy: 0.6095 - false_negatives: 26.2857 - false_positives: 369.4286 - loss: 0.6814 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 77ms/step - binary_accuracy: 0.6060 - false_negatives: 55.1429 - false_positives: 334.8571 - loss: 0.6804
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 11s 79ms/step - binary_accuracy: 0.6116 - false_negatives: 26.3750 - false_positives: 415.5000 - loss: 0.6805 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 11s 77ms/step - binary_accuracy: 0.6094 - false_negatives: 55.3750 - false_positives: 379.7500 - loss: 0.6794
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 11s 79ms/step - binary_accuracy: 0.6139 - false_negatives: 26.4444 - false_positives: 460.4445 - loss: 0.6793 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 11s 76ms/step - binary_accuracy: 0.6128 - false_negatives: 55.5556 - false_positives: 423.5555 - loss: 0.6782
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 11s 78ms/step - binary_accuracy: 0.6159 - false_negatives: 26.5000 - false_positives: 505.5000 - loss: 0.6782 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 11s 76ms/step - binary_accuracy: 0.6156 - false_negatives: 55.7000 - false_positives: 467.4000 - loss: 0.6772
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 11s 78ms/step - binary_accuracy: 0.6180 - false_negatives: 26.6364 - false_positives: 549.2727 - loss: 0.6770 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 11s 76ms/step - binary_accuracy: 0.6179 - false_negatives: 55.8182 - false_positives: 511.5454 - loss: 0.6762
```  ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 11s 77ms/step - binary_accuracy: 0.6202 - false_negatives: 26.7500 - false_positives: 592.2500 - loss: 0.6758 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6200 - false_negatives: 55.9167 - false_positives: 555.5833 - loss: 0.6753
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 11s 77ms/step - binary_accuracy: 0.6222 - false_negatives: 26.8462 - false_positives: 635.2308 - loss: 0.6747 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6219 - false_negatives: 56.0000 - false_positives: 599.3846 - loss: 0.6743
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 11s 77ms/step - binary_accuracy: 0.6240 - false_negatives: 26.9286 - false_positives: 677.8571 - loss: 0.6736 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6241 - false_negatives: 56.0714 - false_positives: 641.3571 - loss: 0.6732
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 77ms/step - binary_accuracy: 0.6258 - false_negatives: 27.0000 - false_positives: 720.1334 - loss: 0.6725 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6262 - false_negatives: 56.1333 - false_positives: 683.2000 - loss: 0.6721
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 77ms/step - binary_accuracy: 0.6276 - false_negatives: 27.0625 - false_positives: 762.1250 - loss: 0.6715 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6279 - false_negatives: 56.1875 - false_positives: 725.6250 - loss: 0.6713
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6291 - false_negatives: 27.1176 - false_positives: 804.1765 - loss: 0.6705 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6296 - false_negatives: 56.2353 - false_positives: 767.4706 - loss: 0.6703
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6307 - false_negatives: 27.1667 - false_positives: 845.5555 - loss: 0.6696 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6313 - false_negatives: 56.2778 - false_positives: 808.5000 - loss: 0.6694
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6323 - false_negatives: 27.2105 - false_positives: 886.4211 - loss: 0.6687 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6328 - false_negatives: 56.3158 - false_positives: 849.8947 - loss: 0.6685
```  ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6338 - false_negatives: 27.2500 - false_positives: 927.1000 - loss: 0.6678 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6343 - false_negatives: 56.3500 - false_positives: 891.0500 - loss: 0.6676
```  ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6353 - false_negatives: 27.2857 - false_positives: 967.1905 - loss: 0.6668 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 10s 75ms/step - binary_accuracy: 0.6358 - false_negatives: 56.3810 - false_positives: 931.5238 - loss: 0.6667
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6369 - false_negatives: 27.3182 - false_positives: 1006.5909 - loss: 0.6658 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.6372 - false_negatives: 56.4091 - false_positives: 972.0000 - loss: 0.6658
``` - + ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6384 - false_negatives: 27.3478 - false_positives: 1045.7391 - loss: 0.6648 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6385 - false_negatives: 56.4348 - false_positives: 1012.2174 - loss: 0.6649
``` - + ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 10s 76ms/step - binary_accuracy: 0.6398 - false_negatives: 27.3750 - false_positives: 1084.5834 - loss: 0.6639 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6399 - false_negatives: 56.4583 - false_positives: 1051.5834 - loss: 0.6640
``` - + ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 76ms/step - binary_accuracy: 0.6412 - false_negatives: 27.4000 - false_positives: 1123.4399 - loss: 0.6629 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6413 - false_negatives: 56.4800 - false_positives: 1090.4800 - loss: 0.6631
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 76ms/step - binary_accuracy: 0.6425 - false_negatives: 27.4231 - false_positives: 1162.1538 - loss: 0.6621 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6426 - false_negatives: 56.5000 - false_positives: 1129.6154 - loss: 0.6623
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6438 - false_negatives: 27.4444 - false_positives: 1200.7407 - loss: 0.6612 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6439 - false_negatives: 56.5185 - false_positives: 1168.1111 - loss: 0.6614
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6451 - false_negatives: 27.4643 - false_positives: 1238.8214 - loss: 0.6603 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6453 - false_negatives: 56.5357 - false_positives: 1205.8572 - loss: 0.6605
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6464 - false_negatives: 27.4828 - false_positives: 1276.5862 - loss: 0.6595 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6466 - false_negatives: 56.5517 - false_positives: 1243.2069 - loss: 0.6596
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6477 - false_negatives: 27.5000 - false_positives: 1313.8000 - loss: 0.6586 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6479 - false_negatives: 56.5667 - false_positives: 1280.1000 - loss: 0.6587
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6489 - false_negatives: 27.5161 - false_positives: 1350.7419 - loss: 0.6577 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6492 - false_negatives: 56.5806 - false_positives: 1316.8064 - loss: 0.6578
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6502 - false_negatives: 27.5312 - false_positives: 1387.3438 - loss: 0.6568 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6505 - false_negatives: 56.5938 - false_positives: 1353.5625 - loss: 0.6569
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6514 - false_negatives: 27.5455 - false_positives: 1423.8182 - loss: 0.6560 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6516 - false_negatives: 56.6061 - false_positives: 1390.8182 - loss: 0.6561
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6525 - false_negatives: 27.5588 - false_positives: 1460.3823 - loss: 0.6552 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6527 - false_negatives: 56.6176 - false_positives: 1427.9706 - loss: 0.6553
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6536 - false_negatives: 27.5714 - false_positives: 1497.3715 - loss: 0.6544 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.6537 - false_negatives: 56.6286 - false_positives: 1464.9714 - loss: 0.6546
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6546 - false_negatives: 27.5833 - false_positives: 1534.5834 - loss: 0.6537 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6547 - false_negatives: 56.6389 - false_positives: 1502.4166 - loss: 0.6539
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 9s 75ms/step - binary_accuracy: 0.6555 - false_negatives: 27.5946 - false_positives: 1571.7838 - loss: 0.6531 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6556 - false_negatives: 56.6486 - false_positives: 1540.4054 - loss: 0.6532
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6564 - false_negatives: 27.6053 - false_positives: 1609.1052 - loss: 0.6524 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6564 - false_negatives: 56.6579 - false_positives: 1578.9210 - loss: 0.6527
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6572 - false_negatives: 27.6154 - false_positives: 1646.7179 - loss: 0.6519 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6571 - false_negatives: 56.6667 - false_positives: 1617.8462 - loss: 0.6522
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6580 - false_negatives: 27.6250 - false_positives: 1684.9000 - loss: 0.6513 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6577 - false_negatives: 56.6750 - false_positives: 1657.3500 - loss: 0.6517
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6587 - false_negatives: 27.6341 - false_positives: 1723.6342 - loss: 0.6508 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6583 - false_negatives: 56.6829 - false_positives: 1697.3170 - loss: 0.6513
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6593 - false_negatives: 27.6429 - false_positives: 1762.6190 - loss: 0.6504 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6588 - false_negatives: 56.6905 - false_positives: 1737.4762 - loss: 0.6509
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6599 - false_negatives: 27.6512 - false_positives: 1801.5581 - loss: 0.6500 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6592 - false_negatives: 56.6977 - false_positives: 1778.0233 - loss: 0.6505
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6604 - false_negatives: 27.6591 - false_positives: 1841.0454 - loss: 0.6496 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6597 - false_negatives: 56.7045 - false_positives: 1818.8409 - loss: 0.6502
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6609 - false_negatives: 27.6667 - false_positives: 1880.8667 - loss: 0.6493 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6600 - false_negatives: 56.7111 - false_positives: 1860.0222 - loss: 0.6499
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6613 - false_negatives: 27.6739 - false_positives: 1921.0652 - loss: 0.6489 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6603 - false_negatives: 56.7174 - false_positives: 1901.6522 - loss: 0.6496
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6617 - false_negatives: 27.6809 - false_positives: 1961.5319 - loss: 0.6486 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6606 - false_negatives: 56.7234 - false_positives: 1943.6595 - loss: 0.6493
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6621 - false_negatives: 27.6875 - false_positives: 2002.5000 - loss: 0.6484 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.6608 - false_negatives: 56.7292 - false_positives: 1985.9375 - loss: 0.6491
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6624 - false_negatives: 27.6939 - false_positives: 2044.0613 - loss: 0.6481 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6610 - false_negatives: 56.7347 - false_positives: 2028.6327 - loss: 0.6489
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.6626 - false_negatives: 27.7000 - false_positives: 2086.1799 - loss: 0.6479 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6612 - false_negatives: 56.7400 - false_positives: 2072.0601 - loss: 0.6487
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6628 - false_negatives: 27.7059 - false_positives: 2128.8823 - loss: 0.6477 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6613 - false_negatives: 56.7451 - false_positives: 2115.9019 - loss: 0.6486
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6629 - false_negatives: 27.7115 - false_positives: 2171.9424 - loss: 0.6476 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6613 - false_negatives: 56.7500 - false_positives: 2160.1345 - loss: 0.6485
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6630 - false_negatives: 27.7170 - false_positives: 2215.5283 - loss: 0.6474 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6613 - false_negatives: 56.7547 - false_positives: 2204.7737 - loss: 0.6484
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6630 - false_negatives: 27.7222 - false_positives: 2260.0740 - loss: 0.6473 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6613 - false_negatives: 56.7593 - false_positives: 2249.8518 - loss: 0.6483
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6630 - false_negatives: 27.7273 - false_positives: 2305.2363 - loss: 0.6472 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6612 - false_negatives: 56.7636 - false_positives: 2295.5454 - loss: 0.6482
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6629 - false_negatives: 27.7321 - false_positives: 2351.3394 - loss: 0.6472 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6611 - false_negatives: 56.7679 - false_positives: 2341.7322 - loss: 0.6481
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6627 - false_negatives: 27.7544 - false_positives: 2398.1404 - loss: 0.6471 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6610 - false_negatives: 56.7895 - false_positives: 2388.5439 - loss: 0.6481
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6625 - false_negatives: 27.8966 - false_positives: 2445.4138 - loss: 0.6471 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6608 - false_negatives: 56.8103 - false_positives: 2435.7241 - loss: 0.6481
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6623 - false_negatives: 28.1525 - false_positives: 2493.1355 - loss: 0.6471 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6606 - false_negatives: 56.8305 - false_positives: 2483.3899 - loss: 0.6481
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6620 - false_negatives: 28.4000 - false_positives: 2541.4333 - loss: 0.6471 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6604 - false_negatives: 56.8500 - false_positives: 2531.3167 - loss: 0.6481
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6617 - false_negatives: 28.6885 - false_positives: 2590.2622 - loss: 0.6471 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6601 - false_negatives: 56.8689 - false_positives: 2579.7212 - loss: 0.6481
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6614 - false_negatives: 29.0806 - false_positives: 2639.2903 - loss: 0.6471 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.6599 - false_negatives: 56.9677 - false_positives: 2628.5645 - loss: 0.6481
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.6610 - false_negatives: 29.5556 - false_positives: 2688.6826 - loss: 0.6471 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6596 - false_negatives: 57.2698 - false_positives: 2677.3650 - loss: 0.6482
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6607 - false_negatives: 30.0469 - false_positives: 2738.5781 - loss: 0.6471 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6593 - false_negatives: 57.8125 - false_positives: 2726.3906 - loss: 0.6482
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6603 - false_negatives: 30.7538 - false_positives: 2788.6001 - loss: 0.6472 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6589 - false_negatives: 58.8154 - false_positives: 2775.1230 - loss: 0.6482
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6599 - false_negatives: 31.8030 - false_positives: 2838.4546 - loss: 0.6472 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6586 - false_negatives: 60.0455 - false_positives: 2823.8940 - loss: 0.6483
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6595 - false_negatives: 33.1343 - false_positives: 2888.3879 - loss: 0.6473 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6583 - false_negatives: 61.7015 - false_positives: 2872.3730 - loss: 0.6484
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6590 - false_negatives: 34.5882 - false_positives: 2938.8823 - loss: 0.6474 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6579 - false_negatives: 63.9118 - false_positives: 2920.3088 - loss: 0.6484
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6586 - false_negatives: 36.8261 - false_positives: 2988.8406 - loss: 0.6475 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6576 - false_negatives: 66.9855 - false_positives: 2967.5942 - loss: 0.6485
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6581 - false_negatives: 39.7714 - false_positives: 3038.1287 - loss: 0.6475 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6573 - false_negatives: 71.2143 - false_positives: 3013.7144 - loss: 0.6486
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6577 - false_negatives: 43.4366 - false_positives: 3087.0142 - loss: 0.6476 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6569 - false_negatives: 76.6479 - false_positives: 3058.6902 - loss: 0.6486
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6572 - false_negatives: 47.8750 - false_positives: 3135.3057 - loss: 0.6477 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6566 - false_negatives: 83.0556 - false_positives: 3102.7778 - loss: 0.6487
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6567 - false_negatives: 53.0274 - false_positives: 3183.0686 - loss: 0.6478 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6562 - false_negatives: 90.4795 - false_positives: 3145.8220 - loss: 0.6488
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6563 - false_negatives: 58.7703 - false_positives: 3230.2837 - loss: 0.6479 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6559 - false_negatives: 99.2162 - false_positives: 3187.8108 - loss: 0.6489
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6558 - false_negatives: 65.2667 - false_positives: 3276.8667 - loss: 0.6480 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.6556 - false_negatives: 108.9067 - false_positives: 3228.9067 - loss: 0.6490
``` - + ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.6553 - false_negatives: 72.2895 - false_positives: 3322.8289 - loss: 0.6481 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6552 - false_negatives: 119.5000 - false_positives: 3269.1316 - loss: 0.6491
``` - + ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6549 - false_negatives: 80.0779 - false_positives: 3368.1299 - loss: 0.6482 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6549 - false_negatives: 130.8831 - false_positives: 3308.5715 - loss: 0.6491
``` - + ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6544 - false_negatives: 88.6667 - false_positives: 3412.6794 - loss: 0.6483 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6546 - false_negatives: 143.1538 - false_positives: 3347.0642 - loss: 0.6492
``` - + ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6540 - false_negatives: 98.0760 - false_positives: 3456.3291 - loss: 0.6484 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6543 - false_negatives: 156.2278 - false_positives: 3384.6328 - loss: 0.6493
``` - + ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6536 - false_negatives: 108.4000 - false_positives: 3499.0750 - loss: 0.6485 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6539 - false_negatives: 170.1500 - false_positives: 3421.3250 - loss: 0.6494
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6531 - false_negatives: 119.5309 - false_positives: 3541.0493 - loss: 0.6486 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6536 - false_negatives: 184.9506 - false_positives: 3457.1604 - loss: 0.6495
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6527 - false_negatives: 131.3171 - false_positives: 3582.4023 - loss: 0.6487 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6533 - false_negatives: 200.5854 - false_positives: 3492.2439 - loss: 0.6496
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6523 - false_negatives: 143.6747 - false_positives: 3623.1445 - loss: 0.6489 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6530 - false_negatives: 217.0482 - false_positives: 3526.5422 - loss: 0.6496
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6519 - false_negatives: 156.7262 - false_positives: 3663.1667 - loss: 0.6490 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6527 - false_negatives: 234.1071 - false_positives: 3560.1072 - loss: 0.6497
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6515 - false_negatives: 170.4235 - false_positives: 3702.4824 - loss: 0.6491 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6524 - false_negatives: 251.8471 - false_positives: 3592.9058 - loss: 0.6498
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6511 - false_negatives: 184.6744 - false_positives: 3741.1279 - loss: 0.6492 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6521 - false_negatives: 270.3837 - false_positives: 3625.0466 - loss: 0.6499
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.6507 - false_negatives: 199.4368 - false_positives: 3779.1494 - loss: 0.6493 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6519 - false_negatives: 289.6092 - false_positives: 3656.5747 - loss: 0.6499
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6503 - false_negatives: 214.7614 - false_positives: 3816.5227 - loss: 0.6494 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6516 - false_negatives: 309.4546 - false_positives: 3687.5908 - loss: 0.6500
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6499 - false_negatives: 230.5281 - false_positives: 3853.2698 - loss: 0.6495 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.6513 - false_negatives: 329.9101 - false_positives: 3718.1011 - loss: 0.6501
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6496 - false_negatives: 246.8111 - false_positives: 3889.4443 - loss: 0.6496 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6510 - false_negatives: 350.7889 - false_positives: 3748.0557 - loss: 0.6501
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6492 - false_negatives: 263.6703 - false_positives: 3924.9341 - loss: 0.6497 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6507 - false_negatives: 372.1538 - false_positives: 3777.3955 - loss: 0.6502
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6489 - false_negatives: 280.9456 - false_positives: 3959.9021 - loss: 0.6498 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6504 - false_negatives: 394.1413 - false_positives: 3806.1631 - loss: 0.6503
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6486 - false_negatives: 298.7742 - false_positives: 3994.2258 - loss: 0.6499 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6502 - false_negatives: 416.5591 - false_positives: 3834.4731 - loss: 0.6503
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6482 - false_negatives: 317.2234 - false_positives: 4027.9575 - loss: 0.6500 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6499 - false_negatives: 439.4468 - false_positives: 3862.2659 - loss: 0.6504
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6479 - false_negatives: 336.1579 - false_positives: 4061.1580 - loss: 0.6501 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6496 - false_negatives: 462.8105 - false_positives: 3889.5159 - loss: 0.6505
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6476 - false_negatives: 355.5312 - false_positives: 4093.8333 - loss: 0.6502 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6494 - false_negatives: 486.6562 - false_positives: 3916.2812 - loss: 0.6505
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6473 - false_negatives: 375.3299 - false_positives: 4126.0825 - loss: 0.6503 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6491 - false_negatives: 510.9485 - false_positives: 3942.5979 - loss: 0.6506
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6470 - false_negatives: 395.5000 - false_positives: 4157.9185 - loss: 0.6504 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6489 - false_negatives: 535.4592 - false_positives: 3968.7754 - loss: 0.6506
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6467 - false_negatives: 415.8788 - false_positives: 4189.4443 - loss: 0.6504 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6486 - false_negatives: 560.1111 - false_positives: 3994.6768 - loss: 0.6507
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6464 - false_negatives: 436.7600 - false_positives: 4220.3701 - loss: 0.6505 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6484 - false_negatives: 585.3000 - false_positives: 4020.1101 - loss: 0.6507
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6461 - false_negatives: 457.9406 - false_positives: 4250.9404 - loss: 0.6506 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6482 - false_negatives: 610.6931 - false_positives: 4045.2773 - loss: 0.6508
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6458 - false_negatives: 479.5686 - false_positives: 4281.0786 - loss: 0.6507 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6479 - false_negatives: 636.3137 - false_positives: 4070.0686 - loss: 0.6508
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.6456 - false_negatives: 500.9126 - false_positives: 4311.5630 - loss: 0.6508 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6477 - false_negatives: 662.2816 - false_positives: 4094.4175 - loss: 0.6508
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6453 - false_negatives: 522.7981 - false_positives: 4341.4902 - loss: 0.6509 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6475 - false_negatives: 688.6442 - false_positives: 4118.4902 - loss: 0.6509
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6450 - false_negatives: 544.9905 - false_positives: 4370.9810 - loss: 0.6509 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6473 - false_negatives: 714.6762 - false_positives: 4142.8667 - loss: 0.6509
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6448 - false_negatives: 567.3962 - false_positives: 4400.1133 - loss: 0.6510 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6470 - false_negatives: 741.1415 - false_positives: 4166.8018 - loss: 0.6510
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6445 - false_negatives: 590.0374 - false_positives: 4428.9907 - loss: 0.6511 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6468 - false_negatives: 767.6542 - false_positives: 4190.5981 - loss: 0.6510
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6443 - false_negatives: 612.8055 - false_positives: 4457.6758 - loss: 0.6512 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6466 - false_negatives: 794.5926 - false_positives: 4214.0093 - loss: 0.6510
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6440 - false_negatives: 635.9083 - false_positives: 4486.0093 - loss: 0.6513 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6464 - false_negatives: 821.4128 - false_positives: 4237.4585 - loss: 0.6511
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6438 - false_negatives: 659.1636 - false_positives: 4514.0273 - loss: 0.6513 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6462 - false_negatives: 848.3818 - false_positives: 4260.6001 - loss: 0.6511
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6435 - false_negatives: 682.6396 - false_positives: 4541.6577 - loss: 0.6514 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6460 - false_negatives: 875.5225 - false_positives: 4283.4863 - loss: 0.6511
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6433 - false_negatives: 705.9643 - false_positives: 4569.4106 - loss: 0.6515 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6458 - false_negatives: 902.9643 - false_positives: 4306.0713 - loss: 0.6511
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6431 - false_negatives: 729.7079 - false_positives: 4596.7524 - loss: 0.6515 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6456 - false_negatives: 930.1062 - false_positives: 4328.9116 - loss: 0.6512
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6429 - false_negatives: 753.6842 - false_positives: 4623.7456 - loss: 0.6516 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6455 - false_negatives: 957.4825 - false_positives: 4351.3857 - loss: 0.6512
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6427 - false_negatives: 778.0435 - false_positives: 4650.3477 - loss: 0.6517 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6453 - false_negatives: 984.8870 - false_positives: 4373.6958 - loss: 0.6512
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.6424 - false_negatives: 802.4224 - false_positives: 4676.8877 - loss: 0.6517 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6451 - false_negatives: 1012.3535 - false_positives: 4395.7153 - loss: 0.6512
``` - + ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6422 - false_negatives: 827.0000 - false_positives: 4703.1538 - loss: 0.6518 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6450 - false_negatives: 1039.5555 - false_positives: 4417.9658 - loss: 0.6512
``` - + ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6420 - false_negatives: 851.4237 - false_positives: 4729.5850 - loss: 0.6519 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6448 - false_negatives: 1067.1526 - false_positives: 4439.8477 - loss: 0.6512
``` - + ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6418 - false_negatives: 876.1512 - false_positives: 4755.5967 - loss: 0.6519 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6446 - false_negatives: 1094.3109 - false_positives: 4462.3359 - loss: 0.6513
``` - + ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6417 - false_negatives: 901.1250 - false_positives: 4781.2749 - loss: 0.6520 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6445 - false_negatives: 1121.2167 - false_positives: 4485.1084 - loss: 0.6513
``` - + ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6415 - false_negatives: 926.0165 - false_positives: 4807.0083 - loss: 0.6520 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6443 - false_negatives: 1147.9669 - false_positives: 4508.1240 - loss: 0.6513
``` - + ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6413 - false_negatives: 951.3197 - false_positives: 4832.3359 - loss: 0.6521 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6442 - false_negatives: 1174.7131 - false_positives: 4531.0493 - loss: 0.6513
``` - + ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6411 - false_negatives: 976.4553 - false_positives: 4857.8047 - loss: 0.6521 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6440 - false_negatives: 1201.4227 - false_positives: 4554.0083 - loss: 0.6513
``` - + ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6409 - false_negatives: 1001.6613 - false_positives: 4883.1372 - loss: 0.6522 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6438 - false_negatives: 1228.1210 - false_positives: 4576.8467 - loss: 0.6514
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6407 - false_negatives: 1027.0320 - false_positives: 4908.2241 - loss: 0.6522 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6437 - false_negatives: 1254.9840 - false_positives: 4599.4399 - loss: 0.6514
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6406 - false_negatives: 1052.6111 - false_positives: 4933.0557 - loss: 0.6523 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6436 - false_negatives: 1281.7620 - false_positives: 4621.9204 - loss: 0.6514
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6404 - false_negatives: 1078.2205 - false_positives: 4957.7246 - loss: 0.6523 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6434 - false_negatives: 1308.5669 - false_positives: 4644.2285 - loss: 0.6514
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6402 - false_negatives: 1104.1562 - false_positives: 4982.0469 - loss: 0.6524 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6433 - false_negatives: 1335.4844 - false_positives: 4666.3203 - loss: 0.6514
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6401 - false_negatives: 1129.8915 - false_positives: 5006.5425 - loss: 0.6524 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6432 - false_negatives: 1362.3954 - false_positives: 4688.2402 - loss: 0.6514
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6399 - false_negatives: 1156.0000 - false_positives: 5030.6768 - loss: 0.6525 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6431 - false_negatives: 1389.5385 - false_positives: 4709.9229 - loss: 0.6514
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6398 - false_negatives: 1182.1527 - false_positives: 5054.6948 - loss: 0.6525 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6429 - false_negatives: 1416.6718 - false_positives: 4731.5112 - loss: 0.6514
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6396 - false_negatives: 1208.3030 - false_positives: 5078.5757 - loss: 0.6525 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6428 - false_negatives: 1443.9395 - false_positives: 4752.8257 - loss: 0.6514
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6395 - false_negatives: 1234.7218 - false_positives: 5102.1729 - loss: 0.6526 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6427 - false_negatives: 1471.3610 - false_positives: 4773.9551 - loss: 0.6514
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6393 - false_negatives: 1261.0970 - false_positives: 5125.6719 - loss: 0.6526 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6426 - false_negatives: 1498.7687 - false_positives: 4794.9478 - loss: 0.6514
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6392 - false_negatives: 1287.3407 - false_positives: 5149.0518 - loss: 0.6526 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6425 - false_negatives: 1526.1630 - false_positives: 4815.7705 - loss: 0.6514
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6391 - false_negatives: 1313.8677 - false_positives: 5172.1616 - loss: 0.6527 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6424 - false_negatives: 1553.5073 - false_positives: 4836.4927 - loss: 0.6513
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6389 - false_negatives: 1340.2335 - false_positives: 5195.3286 - loss: 0.6527 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6423 - false_negatives: 1580.7737 - false_positives: 4857.0874 - loss: 0.6513
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6388 - false_negatives: 1366.8406 - false_positives: 5218.2246 - loss: 0.6527 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6423 - false_negatives: 1608.1594 - false_positives: 4877.4712 - loss: 0.6513
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6387 - false_negatives: 1393.3885 - false_positives: 5241.0864 - loss: 0.6528 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6422 - false_negatives: 1635.2302 - false_positives: 4898.3311 - loss: 0.6513
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6386 - false_negatives: 1420.1786 - false_positives: 5263.6787 - loss: 0.6528 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6421 - false_negatives: 1662.2142 - false_positives: 4919.1431 - loss: 0.6512
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6384 - false_negatives: 1446.7305 - false_positives: 5286.6172 - loss: 0.6528 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6420 - false_negatives: 1689.1418 - false_positives: 4939.9502 - loss: 0.6512
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6383 - false_negatives: 1473.5211 - false_positives: 5309.2744 - loss: 0.6528 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6419 - false_negatives: 1716.1127 - false_positives: 4960.6055 - loss: 0.6512
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6382 - false_negatives: 1500.1609 - false_positives: 5331.9438 - loss: 0.6529 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.6419 - false_negatives: 1743.0000 - false_positives: 4981.1816 - loss: 0.6511
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6381 - false_negatives: 1527.0000 - false_positives: 5354.3472 - loss: 0.6529 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6418 - false_negatives: 1770.2153 - false_positives: 5001.5068 - loss: 0.6511
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6380 - false_negatives: 1553.5656 - false_positives: 5376.9380 - loss: 0.6529 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6417 - false_negatives: 1797.0758 - false_positives: 5022.3242 - loss: 0.6511
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6379 - false_negatives: 1580.2671 - false_positives: 5399.2808 - loss: 0.6529 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6417 - false_negatives: 1823.6370 - false_positives: 5043.4521 - loss: 0.6510
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6378 - false_negatives: 1606.8776 - false_positives: 5421.5376 - loss: 0.6529 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6416 - false_negatives: 1849.9932 - false_positives: 5064.6123 - loss: 0.6510
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6377 - false_negatives: 1633.6082 - false_positives: 5443.5474 - loss: 0.6530 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6415 - false_negatives: 1876.2230 - false_positives: 5085.7837 - loss: 0.6510
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6376 - false_negatives: 1660.0336 - false_positives: 5465.9263 - loss: 0.6530 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6415 - false_negatives: 1902.4296 - false_positives: 5106.9463 - loss: 0.6510
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6375 - false_negatives: 1686.3267 - false_positives: 5488.2065 - loss: 0.6530 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6414 - false_negatives: 1928.4667 - false_positives: 5128.0601 - loss: 0.6509
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6374 - false_negatives: 1712.7020 - false_positives: 5510.2515 - loss: 0.6530 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6414 - false_negatives: 1954.5298 - false_positives: 5149.0000 - loss: 0.6509
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6374 - false_negatives: 1739.2828 - false_positives: 5532.0527 - loss: 0.6530 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6413 - false_negatives: 1980.6118 - false_positives: 5169.7563 - loss: 0.6508
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6373 - false_negatives: 1765.6536 - false_positives: 5554.1567 - loss: 0.6530 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6413 - false_negatives: 2006.5491 - false_positives: 5190.5361 - loss: 0.6508
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6372 - false_negatives: 1792.0260 - false_positives: 5576.1431 - loss: 0.6530 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6412 - false_negatives: 2032.5909 - false_positives: 5211.1362 - loss: 0.6508
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6371 - false_negatives: 1818.4645 - false_positives: 5597.9355 - loss: 0.6530 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6412 - false_negatives: 2058.4902 - false_positives: 5231.7354 - loss: 0.6507
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6371 - false_negatives: 1844.8206 - false_positives: 5619.7178 - loss: 0.6530 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.6412 - false_negatives: 2084.3333 - false_positives: 5252.1924 - loss: 0.6507
``` -Epoch 1: val_loss improved from inf to 0.58597, saving model to FullModelCheckpoint.keras +Epoch 1: val_loss improved from inf to 0.57198, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 15s 80ms/step - binary_accuracy: 0.6369 - false_negatives: 1896.7468 - false_positives: 5662.4683 - loss: 0.6530 - val_binary_accuracy: 0.7242 - val_false_negatives: 878.0000 - val_false_positives: 501.0000 - val_loss: 0.5860 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 15s 79ms/step - binary_accuracy: 0.6411 - false_negatives: 2135.1772 - false_positives: 5292.4053 - loss: 0.6506 - val_binary_accuracy: 0.7356 - val_false_negatives: 898.0000 - val_false_positives: 424.0000 - val_loss: 0.5720
@@ -1520,1102 +1508,1102 @@ Epoch 2/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.6836 - false_negatives: 60.0000 - false_positives: 21.0000 - loss: 0.6335 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 93ms/step - binary_accuracy: 0.6602 - false_negatives: 68.0000 - false_positives: 19.0000 - loss: 0.6673
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6787 - false_negatives: 64.0000 - false_positives: 60.0000 - loss: 0.6291 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6641 - false_negatives: 73.0000 - false_positives: 55.5000 - loss: 0.6517
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6799 - false_negatives: 70.6667 - false_positives: 93.3333 - loss: 0.6234 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6688 - false_negatives: 79.0000 - false_positives: 89.0000 - loss: 0.6421
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6818 - false_negatives: 78.5000 - false_positives: 124.5000 - loss: 0.6195 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6733 - false_negatives: 86.5000 - false_positives: 119.7500 - loss: 0.6360
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6856 - false_negatives: 86.4000 - false_positives: 152.6000 - loss: 0.6152 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6775 - false_negatives: 93.8000 - false_positives: 149.4000 - loss: 0.6301
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6899 - false_negatives: 97.3333 - false_positives: 175.6667 - loss: 0.6113 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6816 - false_negatives: 100.5000 - false_positives: 178.5000 - loss: 0.6249
``` - + ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.6923 - false_negatives: 105.2857 - false_positives: 203.8571 - loss: 0.6094 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.6865 - false_negatives: 106.8571 - false_positives: 205.0000 - loss: 0.6200
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.6944 - false_negatives: 112.5000 - false_positives: 232.5000 - loss: 0.6074 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6905 - false_negatives: 113.5000 - false_positives: 231.5000 - loss: 0.6162
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6963 - false_negatives: 120.5556 - false_positives: 260.0000 - loss: 0.6056 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6942 - false_negatives: 119.7778 - false_positives: 257.5555 - loss: 0.6126
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6978 - false_negatives: 128.5000 - false_positives: 287.8000 - loss: 0.6041 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6973 - false_negatives: 126.3000 - false_positives: 283.7000 - loss: 0.6095
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.6995 - false_negatives: 136.5455 - false_positives: 314.5454 - loss: 0.6025 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7000 - false_negatives: 132.3636 - false_positives: 310.2727 - loss: 0.6065
```  ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7008 - false_negatives: 146.0000 - false_positives: 340.5000 - loss: 0.6011 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7021 - false_negatives: 140.8333 - false_positives: 335.0000 - loss: 0.6040
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7018 - false_negatives: 154.0000 - false_positives: 368.2308 - loss: 0.6000 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7038 - false_negatives: 148.4615 - false_positives: 361.3846 - loss: 0.6018
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7031 - false_negatives: 161.0000 - false_positives: 395.6429 - loss: 0.5986 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7054 - false_negatives: 156.2143 - false_positives: 387.5714 - loss: 0.5997
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7045 - false_negatives: 167.8667 - false_positives: 422.3333 - loss: 0.5972 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7070 - false_negatives: 163.6667 - false_positives: 413.1333 - loss: 0.5975
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7060 - false_negatives: 175.1250 - false_positives: 447.6875 - loss: 0.5956 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7086 - false_negatives: 171.2500 - false_positives: 437.8750 - loss: 0.5953
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7074 - false_negatives: 181.6471 - false_positives: 473.7647 - loss: 0.5941 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7102 - false_negatives: 178.2941 - false_positives: 462.4118 - loss: 0.5931
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7086 - false_negatives: 188.4444 - false_positives: 499.7778 - loss: 0.5926 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7119 - false_negatives: 185.6667 - false_positives: 485.8333 - loss: 0.5910
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7098 - false_negatives: 194.7895 - false_positives: 526.2105 - loss: 0.5912 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7136 - false_negatives: 192.8421 - false_positives: 509.0000 - loss: 0.5890
```  ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7107 - false_negatives: 203.2500 - false_positives: 551.0500 - loss: 0.5899 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7152 - false_negatives: 200.1500 - false_positives: 531.6500 - loss: 0.5869
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.7116 - false_negatives: 211.0000 - false_positives: 577.0000 - loss: 0.5889 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7168 - false_negatives: 207.2857 - false_positives: 553.9524 - loss: 0.5849
``` - + ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7123 - false_negatives: 218.1364 - false_positives: 603.5455 - loss: 0.5879 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7178 - false_negatives: 219.3182 - false_positives: 574.2727 - loss: 0.5836
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7131 - false_negatives: 224.7391 - false_positives: 630.2174 - loss: 0.5869 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7187 - false_negatives: 230.3044 - false_positives: 595.6087 - loss: 0.5826
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7139 - false_negatives: 230.8750 - false_positives: 657.0833 - loss: 0.5859 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7196 - false_negatives: 240.3750 - false_positives: 617.7083 - loss: 0.5817
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7147 - false_negatives: 236.9600 - false_positives: 683.6000 - loss: 0.5849 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7204 - false_negatives: 249.6800 - false_positives: 640.8400 - loss: 0.5808
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7155 - false_negatives: 242.6538 - false_positives: 709.8846 - loss: 0.5839 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7211 - false_negatives: 258.3077 - false_positives: 664.7308 - loss: 0.5801
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7164 - false_negatives: 248.5185 - false_positives: 735.8519 - loss: 0.5829 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7218 - false_negatives: 266.3704 - false_positives: 689.2963 - loss: 0.5793
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7173 - false_negatives: 254.5357 - false_positives: 760.9286 - loss: 0.5819 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7224 - false_negatives: 274.0714 - false_positives: 713.8929 - loss: 0.5786
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7182 - false_negatives: 260.2414 - false_positives: 785.9310 - loss: 0.5809 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7231 - false_negatives: 281.3793 - false_positives: 738.5172 - loss: 0.5778
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7191 - false_negatives: 266.0667 - false_positives: 810.1334 - loss: 0.5798 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7238 - false_negatives: 288.3000 - false_positives: 763.0667 - loss: 0.5770
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7200 - false_negatives: 271.6129 - false_positives: 834.3226 - loss: 0.5787 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7245 - false_negatives: 295.0645 - false_positives: 787.9032 - loss: 0.5762
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7209 - false_negatives: 278.5625 - false_positives: 857.5938 - loss: 0.5777 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.7251 - false_negatives: 301.5625 - false_positives: 812.6562 - loss: 0.5754
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.7216 - false_negatives: 285.1212 - false_positives: 882.2424 - loss: 0.5770 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7258 - false_negatives: 307.8788 - false_positives: 837.6970 - loss: 0.5747
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.7222 - false_negatives: 291.2941 - false_positives: 907.1177 - loss: 0.5763 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7263 - false_negatives: 314.0588 - false_positives: 863.0588 - loss: 0.5740
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.7229 - false_negatives: 297.2000 - false_positives: 932.6286 - loss: 0.5757 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7269 - false_negatives: 320.2286 - false_positives: 888.3428 - loss: 0.5734
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.7235 - false_negatives: 302.8611 - false_positives: 958.1667 - loss: 0.5750 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7274 - false_negatives: 326.3611 - false_positives: 913.7222 - loss: 0.5727
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.7240 - false_negatives: 308.2973 - false_positives: 984.1622 - loss: 0.5744 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7279 - false_negatives: 332.6216 - false_positives: 939.2703 - loss: 0.5721
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.7245 - false_negatives: 314.2368 - false_positives: 1009.7632 - loss: 0.5738 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7283 - false_negatives: 339.0000 - false_positives: 964.5526 - loss: 0.5715
``` - + ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7251 - false_negatives: 320.1795 - false_positives: 1035.1794 - loss: 0.5732 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7288 - false_negatives: 345.4102 - false_positives: 989.8461 - loss: 0.5710
``` - + ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7256 - false_negatives: 326.2250 - false_positives: 1060.6250 - loss: 0.5727 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7292 - false_negatives: 351.7500 - false_positives: 1015.1000 - loss: 0.5704
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7260 - false_negatives: 332.2683 - false_positives: 1085.8292 - loss: 0.5721 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7297 - false_negatives: 358.2195 - false_positives: 1040.0975 - loss: 0.5699
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7265 - false_negatives: 338.5000 - false_positives: 1110.6904 - loss: 0.5716 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7300 - false_negatives: 364.7857 - false_positives: 1065.4048 - loss: 0.5694
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7270 - false_negatives: 344.6977 - false_positives: 1135.6046 - loss: 0.5710 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7304 - false_negatives: 371.5116 - false_positives: 1090.4884 - loss: 0.5689
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7275 - false_negatives: 351.5000 - false_positives: 1159.7046 - loss: 0.5705 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7308 - false_negatives: 378.1591 - false_positives: 1115.5682 - loss: 0.5684
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7279 - false_negatives: 358.0889 - false_positives: 1184.7111 - loss: 0.5700 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7311 - false_negatives: 384.7556 - false_positives: 1140.7333 - loss: 0.5679
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7283 - false_negatives: 364.6739 - false_positives: 1209.5217 - loss: 0.5696 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.7314 - false_negatives: 391.3913 - false_positives: 1165.7174 - loss: 0.5674
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7287 - false_negatives: 371.6808 - false_positives: 1233.8085 - loss: 0.5691 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7318 - false_negatives: 398.1489 - false_positives: 1190.4681 - loss: 0.5669
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.7291 - false_negatives: 378.5000 - false_positives: 1258.3750 - loss: 0.5687 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7321 - false_negatives: 404.7292 - false_positives: 1215.2500 - loss: 0.5664
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7294 - false_negatives: 385.8776 - false_positives: 1282.4286 - loss: 0.5683 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7325 - false_negatives: 411.7959 - false_positives: 1239.6123 - loss: 0.5660
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7298 - false_negatives: 393.2000 - false_positives: 1306.3800 - loss: 0.5679 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7328 - false_negatives: 418.8000 - false_positives: 1264.0400 - loss: 0.5655
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7301 - false_negatives: 400.9412 - false_positives: 1329.6863 - loss: 0.5675 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7331 - false_negatives: 426.3333 - false_positives: 1287.9412 - loss: 0.5651
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7305 - false_negatives: 408.4038 - false_positives: 1353.9423 - loss: 0.5672 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7333 - false_negatives: 433.8077 - false_positives: 1312.3077 - loss: 0.5647
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7308 - false_negatives: 416.1698 - false_positives: 1377.9056 - loss: 0.5669 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7336 - false_negatives: 442.1698 - false_positives: 1336.0000 - loss: 0.5643
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7310 - false_negatives: 423.8518 - false_positives: 1401.7963 - loss: 0.5666 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7338 - false_negatives: 450.5741 - false_positives: 1359.9630 - loss: 0.5639
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7314 - false_negatives: 431.9636 - false_positives: 1425.0182 - loss: 0.5662 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7340 - false_negatives: 459.2727 - false_positives: 1383.6000 - loss: 0.5636
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7316 - false_negatives: 439.8750 - false_positives: 1448.6608 - loss: 0.5659 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7342 - false_negatives: 467.8214 - false_positives: 1407.2322 - loss: 0.5632
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7319 - false_negatives: 448.4211 - false_positives: 1471.6316 - loss: 0.5656 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7344 - false_negatives: 476.7719 - false_positives: 1430.4210 - loss: 0.5628
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7322 - false_negatives: 456.8276 - false_positives: 1495.1552 - loss: 0.5653 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7346 - false_negatives: 485.6207 - false_positives: 1453.7241 - loss: 0.5625
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7324 - false_negatives: 465.5424 - false_positives: 1518.2543 - loss: 0.5650 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7348 - false_negatives: 495.0508 - false_positives: 1476.5254 - loss: 0.5622
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7327 - false_negatives: 474.2333 - false_positives: 1541.1500 - loss: 0.5647 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.7350 - false_negatives: 504.3333 - false_positives: 1499.8000 - loss: 0.5619
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.7329 - false_negatives: 483.5246 - false_positives: 1563.5574 - loss: 0.5645 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7351 - false_negatives: 514.1639 - false_positives: 1522.6558 - loss: 0.5616
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7331 - false_negatives: 492.5968 - false_positives: 1586.6774 - loss: 0.5642 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7352 - false_negatives: 523.9355 - false_positives: 1545.6129 - loss: 0.5613
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7333 - false_negatives: 501.6349 - false_positives: 1609.9207 - loss: 0.5640 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7354 - false_negatives: 533.9048 - false_positives: 1568.3810 - loss: 0.5611
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7335 - false_negatives: 511.3906 - false_positives: 1632.5469 - loss: 0.5638 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7355 - false_negatives: 543.8750 - false_positives: 1590.8906 - loss: 0.5608
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7336 - false_negatives: 520.9846 - false_positives: 1655.7693 - loss: 0.5636 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7357 - false_negatives: 553.9077 - false_positives: 1613.2770 - loss: 0.5605
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7338 - false_negatives: 530.8636 - false_positives: 1678.5909 - loss: 0.5634 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7358 - false_negatives: 564.4697 - false_positives: 1635.1666 - loss: 0.5602
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7339 - false_negatives: 540.7313 - false_positives: 1701.4626 - loss: 0.5632 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7359 - false_negatives: 574.8508 - false_positives: 1657.3732 - loss: 0.5600
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7340 - false_negatives: 551.1470 - false_positives: 1723.8235 - loss: 0.5630 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7361 - false_negatives: 585.7206 - false_positives: 1679.1617 - loss: 0.5597
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7341 - false_negatives: 561.3623 - false_positives: 1746.6377 - loss: 0.5628 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7362 - false_negatives: 596.4348 - false_positives: 1701.0145 - loss: 0.5595
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7343 - false_negatives: 571.8428 - false_positives: 1768.9857 - loss: 0.5626 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7363 - false_negatives: 607.4572 - false_positives: 1722.4286 - loss: 0.5592
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7344 - false_negatives: 582.4084 - false_positives: 1791.2394 - loss: 0.5624 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7364 - false_negatives: 618.3662 - false_positives: 1744.0000 - loss: 0.5590
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7345 - false_negatives: 593.1250 - false_positives: 1813.1528 - loss: 0.5622 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7366 - false_negatives: 629.7917 - false_positives: 1765.0972 - loss: 0.5587
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7347 - false_negatives: 603.7672 - false_positives: 1835.0411 - loss: 0.5620 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.7367 - false_negatives: 641.0137 - false_positives: 1786.3014 - loss: 0.5585
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7348 - false_negatives: 614.9054 - false_positives: 1856.3918 - loss: 0.5618 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7368 - false_negatives: 652.6486 - false_positives: 1807.0676 - loss: 0.5582
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.7349 - false_negatives: 625.7600 - false_positives: 1878.7067 - loss: 0.5617 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7369 - false_negatives: 664.2933 - false_positives: 1827.6533 - loss: 0.5580
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7350 - false_negatives: 636.6711 - false_positives: 1900.9474 - loss: 0.5615 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7370 - false_negatives: 676.1316 - false_positives: 1848.0922 - loss: 0.5577
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7351 - false_negatives: 647.7662 - false_positives: 1923.0129 - loss: 0.5613 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7371 - false_negatives: 687.8052 - false_positives: 1868.6624 - loss: 0.5575
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7351 - false_negatives: 658.9359 - false_positives: 1944.9872 - loss: 0.5612 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7373 - false_negatives: 700.0897 - false_positives: 1888.8077 - loss: 0.5573
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7352 - false_negatives: 670.3291 - false_positives: 1966.6202 - loss: 0.5610 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7373 - false_negatives: 712.1899 - false_positives: 1909.5443 - loss: 0.5571
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7353 - false_negatives: 681.6375 - false_positives: 1988.2375 - loss: 0.5608 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7374 - false_negatives: 724.5125 - false_positives: 1930.0250 - loss: 0.5569
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7354 - false_negatives: 693.4691 - false_positives: 2009.4321 - loss: 0.5606 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7375 - false_negatives: 737.0247 - false_positives: 1950.2346 - loss: 0.5567
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7355 - false_negatives: 705.1219 - false_positives: 2031.1586 - loss: 0.5605 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7376 - false_negatives: 749.6219 - false_positives: 1970.2073 - loss: 0.5565
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7356 - false_negatives: 716.8073 - false_positives: 2052.6748 - loss: 0.5603 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7377 - false_negatives: 762.2410 - false_positives: 1990.1084 - loss: 0.5563
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7356 - false_negatives: 728.7024 - false_positives: 2073.9167 - loss: 0.5602 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7378 - false_negatives: 774.9286 - false_positives: 2009.8214 - loss: 0.5561
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7357 - false_negatives: 740.8588 - false_positives: 2094.9766 - loss: 0.5600 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7379 - false_negatives: 787.7529 - false_positives: 2029.2706 - loss: 0.5559
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7358 - false_negatives: 752.9651 - false_positives: 2115.9883 - loss: 0.5599 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7380 - false_negatives: 800.5465 - false_positives: 2048.6279 - loss: 0.5556
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7358 - false_negatives: 765.2988 - false_positives: 2136.7356 - loss: 0.5597 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.7381 - false_negatives: 813.4138 - false_positives: 2067.8850 - loss: 0.5554
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.7359 - false_negatives: 777.4432 - false_positives: 2157.7727 - loss: 0.5595 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7382 - false_negatives: 826.3182 - false_positives: 2087.0681 - loss: 0.5552
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7360 - false_negatives: 790.3146 - false_positives: 2178.3596 - loss: 0.5594 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7383 - false_negatives: 839.2697 - false_positives: 2106.0898 - loss: 0.5550
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7360 - false_negatives: 802.9445 - false_positives: 2199.7222 - loss: 0.5593 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7384 - false_negatives: 852.2000 - false_positives: 2124.8889 - loss: 0.5548
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7360 - false_negatives: 815.4945 - false_positives: 2221.2087 - loss: 0.5592 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7385 - false_negatives: 865.1099 - false_positives: 2143.7363 - loss: 0.5545
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7360 - false_negatives: 827.9783 - false_positives: 2242.6738 - loss: 0.5591 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7386 - false_negatives: 878.2500 - false_positives: 2162.2827 - loss: 0.5543
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7361 - false_negatives: 840.5161 - false_positives: 2263.9785 - loss: 0.5589 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7387 - false_negatives: 891.1505 - false_positives: 2181.0859 - loss: 0.5541
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7361 - false_negatives: 853.0851 - false_positives: 2285.0637 - loss: 0.5588 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7388 - false_negatives: 904.3405 - false_positives: 2199.6064 - loss: 0.5539
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7361 - false_negatives: 865.7474 - false_positives: 2306.0315 - loss: 0.5587 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7389 - false_negatives: 917.4211 - false_positives: 2218.1262 - loss: 0.5537
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7362 - false_negatives: 878.4792 - false_positives: 2326.8230 - loss: 0.5586 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7390 - false_negatives: 930.7396 - false_positives: 2236.4167 - loss: 0.5535
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7362 - false_negatives: 891.2886 - false_positives: 2347.4741 - loss: 0.5585 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7391 - false_negatives: 944.0516 - false_positives: 2254.7009 - loss: 0.5532
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7363 - false_negatives: 904.1224 - false_positives: 2368.1226 - loss: 0.5583 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7392 - false_negatives: 957.4592 - false_positives: 2272.8367 - loss: 0.5530
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7363 - false_negatives: 917.1919 - false_positives: 2388.4041 - loss: 0.5582 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7393 - false_negatives: 970.7778 - false_positives: 2290.9395 - loss: 0.5528
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7363 - false_negatives: 930.1600 - false_positives: 2408.8301 - loss: 0.5581 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7394 - false_negatives: 984.2300 - false_positives: 2308.7500 - loss: 0.5526
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7364 - false_negatives: 943.1980 - false_positives: 2429.0000 - loss: 0.5580 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7395 - false_negatives: 997.4752 - false_positives: 2327.0100 - loss: 0.5524
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7364 - false_negatives: 956.1961 - false_positives: 2449.2744 - loss: 0.5578 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7396 - false_negatives: 1011.0490 - false_positives: 2345.0000 - loss: 0.5522
``` - + ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7365 - false_negatives: 969.4369 - false_positives: 2469.2524 - loss: 0.5577 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7397 - false_negatives: 1024.5631 - false_positives: 2363.0486 - loss: 0.5519
``` - + ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7365 - false_negatives: 982.5673 - false_positives: 2489.4136 - loss: 0.5576 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7398 - false_negatives: 1038.1057 - false_positives: 2380.9614 - loss: 0.5517
``` - + ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7366 - false_negatives: 996.0476 - false_positives: 2509.2190 - loss: 0.5575 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7399 - false_negatives: 1051.6095 - false_positives: 2398.7524 - loss: 0.5515
``` - + ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7366 - false_negatives: 1009.3962 - false_positives: 2529.1038 - loss: 0.5573 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7400 - false_negatives: 1065.1698 - false_positives: 2416.4434 - loss: 0.5513
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7367 - false_negatives: 1022.7850 - false_positives: 2548.7944 - loss: 0.5572 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7401 - false_negatives: 1078.7664 - false_positives: 2434.0281 - loss: 0.5511
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7367 - false_negatives: 1036.2870 - false_positives: 2568.2686 - loss: 0.5571 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7402 - false_negatives: 1092.3982 - false_positives: 2451.5647 - loss: 0.5509
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7367 - false_negatives: 1049.6790 - false_positives: 2587.8623 - loss: 0.5569 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7403 - false_negatives: 1106.0367 - false_positives: 2468.9634 - loss: 0.5507
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7368 - false_negatives: 1063.4000 - false_positives: 2607.1545 - loss: 0.5568 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7405 - false_negatives: 1119.7273 - false_positives: 2486.1726 - loss: 0.5505
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7368 - false_negatives: 1076.9369 - false_positives: 2626.8647 - loss: 0.5567 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7406 - false_negatives: 1133.2433 - false_positives: 2503.6216 - loss: 0.5502
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7369 - false_negatives: 1090.5803 - false_positives: 2646.2947 - loss: 0.5565 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7407 - false_negatives: 1147.0714 - false_positives: 2520.7947 - loss: 0.5500
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7369 - false_negatives: 1104.1681 - false_positives: 2665.6726 - loss: 0.5564 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7408 - false_negatives: 1160.6903 - false_positives: 2538.2124 - loss: 0.5498
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7370 - false_negatives: 1117.7808 - false_positives: 2684.9211 - loss: 0.5563 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7409 - false_negatives: 1174.3508 - false_positives: 2555.6316 - loss: 0.5496
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7370 - false_negatives: 1131.3914 - false_positives: 2704.0957 - loss: 0.5561 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7410 - false_negatives: 1188.0261 - false_positives: 2572.9827 - loss: 0.5494
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7371 - false_negatives: 1145.1034 - false_positives: 2723.0947 - loss: 0.5560 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7411 - false_negatives: 1201.7844 - false_positives: 2590.2759 - loss: 0.5492
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7371 - false_negatives: 1158.7179 - false_positives: 2742.1282 - loss: 0.5559 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7411 - false_negatives: 1215.4530 - false_positives: 2607.6155 - loss: 0.5490
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7372 - false_negatives: 1172.7373 - false_positives: 2760.8645 - loss: 0.5557 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7412 - false_negatives: 1229.2034 - false_positives: 2624.8474 - loss: 0.5488
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7372 - false_negatives: 1186.5798 - false_positives: 2779.9329 - loss: 0.5556 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7413 - false_negatives: 1242.9412 - false_positives: 2642.0757 - loss: 0.5486
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7373 - false_negatives: 1200.4083 - false_positives: 2798.8250 - loss: 0.5555 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7414 - false_negatives: 1256.6083 - false_positives: 2659.3833 - loss: 0.5484
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7373 - false_negatives: 1214.2810 - false_positives: 2817.5454 - loss: 0.5554 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7415 - false_negatives: 1270.3472 - false_positives: 2676.5537 - loss: 0.5482
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7374 - false_negatives: 1228.0164 - false_positives: 2836.3770 - loss: 0.5552 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7416 - false_negatives: 1284.0656 - false_positives: 2693.6968 - loss: 0.5480
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7374 - false_negatives: 1242.0975 - false_positives: 2854.9351 - loss: 0.5551 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7417 - false_negatives: 1297.7723 - false_positives: 2710.6992 - loss: 0.5478
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7375 - false_negatives: 1256.0807 - false_positives: 2873.5483 - loss: 0.5550 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7418 - false_negatives: 1311.4193 - false_positives: 2727.7339 - loss: 0.5476
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7375 - false_negatives: 1270.1121 - false_positives: 2891.9441 - loss: 0.5549 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7419 - false_negatives: 1325.2000 - false_positives: 2744.6001 - loss: 0.5474
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7376 - false_negatives: 1284.0476 - false_positives: 2910.4048 - loss: 0.5547 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7420 - false_negatives: 1338.7937 - false_positives: 2761.7539 - loss: 0.5472
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7376 - false_negatives: 1298.1102 - false_positives: 2928.7322 - loss: 0.5546 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7421 - false_negatives: 1352.8740 - false_positives: 2778.6377 - loss: 0.5470
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7377 - false_negatives: 1312.0547 - false_positives: 2947.1797 - loss: 0.5545 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7422 - false_negatives: 1366.8750 - false_positives: 2795.6797 - loss: 0.5469
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7377 - false_negatives: 1326.1705 - false_positives: 2965.4109 - loss: 0.5544 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7423 - false_negatives: 1380.8217 - false_positives: 2812.6899 - loss: 0.5467
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7378 - false_negatives: 1340.1307 - false_positives: 2983.8999 - loss: 0.5542 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7423 - false_negatives: 1394.7616 - false_positives: 2829.5847 - loss: 0.5465
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7378 - false_negatives: 1354.2443 - false_positives: 3002.1299 - loss: 0.5541 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7424 - false_negatives: 1408.6947 - false_positives: 2846.3435 - loss: 0.5463
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7379 - false_negatives: 1368.2803 - false_positives: 3020.4243 - loss: 0.5540 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7425 - false_negatives: 1422.5758 - false_positives: 2863.0303 - loss: 0.5461
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7379 - false_negatives: 1382.6240 - false_positives: 3038.4661 - loss: 0.5538 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7426 - false_negatives: 1436.4812 - false_positives: 2879.6240 - loss: 0.5459
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7380 - false_negatives: 1396.8582 - false_positives: 3056.6567 - loss: 0.5537 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7427 - false_negatives: 1450.3060 - false_positives: 2896.3059 - loss: 0.5458
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7380 - false_negatives: 1411.2148 - false_positives: 3074.6741 - loss: 0.5536 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7428 - false_negatives: 1464.2074 - false_positives: 2912.8296 - loss: 0.5456
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7381 - false_negatives: 1425.5000 - false_positives: 3092.6323 - loss: 0.5535 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7429 - false_negatives: 1478.0515 - false_positives: 2929.3162 - loss: 0.5454
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7382 - false_negatives: 1439.8613 - false_positives: 3110.4307 - loss: 0.5533 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7430 - false_negatives: 1491.9417 - false_positives: 2945.6787 - loss: 0.5452
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7382 - false_negatives: 1454.0797 - false_positives: 3128.3767 - loss: 0.5532 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7431 - false_negatives: 1505.7754 - false_positives: 2962.0000 - loss: 0.5450
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7383 - false_negatives: 1468.4172 - false_positives: 3146.1367 - loss: 0.5531 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7432 - false_negatives: 1519.5972 - false_positives: 2978.2517 - loss: 0.5448
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7383 - false_negatives: 1482.7285 - false_positives: 3163.8787 - loss: 0.5530 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7433 - false_negatives: 1533.3000 - false_positives: 2994.5642 - loss: 0.5446
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7384 - false_negatives: 1497.0283 - false_positives: 3181.5815 - loss: 0.5528 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7434 - false_negatives: 1547.2057 - false_positives: 3010.6809 - loss: 0.5444
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7384 - false_negatives: 1511.3733 - false_positives: 3199.0916 - loss: 0.5527 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7435 - false_negatives: 1561.0422 - false_positives: 3026.9226 - loss: 0.5442
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7385 - false_negatives: 1525.6573 - false_positives: 3216.6572 - loss: 0.5526 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7436 - false_negatives: 1574.9161 - false_positives: 3043.0698 - loss: 0.5440
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7386 - false_negatives: 1539.9166 - false_positives: 3234.1250 - loss: 0.5524 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7437 - false_negatives: 1588.7778 - false_positives: 3059.1736 - loss: 0.5439
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7386 - false_negatives: 1554.1517 - false_positives: 3251.6345 - loss: 0.5523 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7438 - false_negatives: 1602.5931 - false_positives: 3075.2000 - loss: 0.5437
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7387 - false_negatives: 1568.4657 - false_positives: 3269.0068 - loss: 0.5521 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7439 - false_negatives: 1616.4932 - false_positives: 3091.1096 - loss: 0.5435
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7387 - false_negatives: 1582.7279 - false_positives: 3286.3945 - loss: 0.5520 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7440 - false_negatives: 1630.2925 - false_positives: 3107.0815 - loss: 0.5433
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7388 - false_negatives: 1597.0203 - false_positives: 3303.6216 - loss: 0.5519 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7441 - false_negatives: 1644.2703 - false_positives: 3122.8853 - loss: 0.5431
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7389 - false_negatives: 1611.2684 - false_positives: 3320.7986 - loss: 0.5517 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7442 - false_negatives: 1658.1343 - false_positives: 3138.8994 - loss: 0.5429
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7389 - false_negatives: 1625.6533 - false_positives: 3337.8000 - loss: 0.5516 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7443 - false_negatives: 1672.1733 - false_positives: 3154.7534 - loss: 0.5427
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7390 - false_negatives: 1639.8741 - false_positives: 3355.0928 - loss: 0.5514 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7444 - false_negatives: 1686.1458 - false_positives: 3170.6755 - loss: 0.5425
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7391 - false_negatives: 1654.3224 - false_positives: 3372.1843 - loss: 0.5513 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7445 - false_negatives: 1700.0592 - false_positives: 3186.5066 - loss: 0.5424
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7391 - false_negatives: 1668.6210 - false_positives: 3389.4248 - loss: 0.5512 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7446 - false_negatives: 1714.1438 - false_positives: 3202.2288 - loss: 0.5422
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7392 - false_negatives: 1682.9091 - false_positives: 3406.4934 - loss: 0.5510 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7447 - false_negatives: 1728.1884 - false_positives: 3217.9221 - loss: 0.5420
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7393 - false_negatives: 1697.1355 - false_positives: 3423.5032 - loss: 0.5509 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7448 - false_negatives: 1742.2323 - false_positives: 3233.5354 - loss: 0.5418
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7393 - false_negatives: 1711.4294 - false_positives: 3440.3845 - loss: 0.5507 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7448 - false_negatives: 1756.2756 - false_positives: 3249.1411 - loss: 0.5416
``` -Epoch 2: val_loss improved from 0.58597 to 0.43786, saving model to FullModelCheckpoint.keras +Epoch 2: val_loss improved from 0.57198 to 0.41756, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.7395 - false_negatives: 1739.5127 - false_positives: 3473.6077 - loss: 0.5505 - val_binary_accuracy: 0.8106 - val_false_negatives: 646.0000 - val_false_positives: 301.0000 - val_loss: 0.4379 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.7450 - false_negatives: 1783.8925 - false_positives: 3279.8101 - loss: 0.5412 - val_binary_accuracy: 0.8156 - val_false_negatives: 531.0000 - val_false_positives: 391.0000 - val_loss: 0.4176
@@ -2625,1102 +2613,1102 @@ Epoch 3/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.7148 - false_negatives: 51.0000 - false_positives: 22.0000 - loss: 0.5465 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 93ms/step - binary_accuracy: 0.8398 - false_negatives: 25.0000 - false_positives: 16.0000 - loss: 0.4063
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.7354 - false_negatives: 56.0000 - false_positives: 43.0000 - loss: 0.5251 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8271 - false_negatives: 25.5000 - false_positives: 42.5000 - loss: 0.4258
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.7485 - false_negatives: 63.6667 - false_positives: 60.0000 - loss: 0.5155 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 75ms/step - binary_accuracy: 0.8270 - false_negatives: 30.3333 - false_positives: 59.3333 - loss: 0.4288
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.7579 - false_negatives: 71.0000 - false_positives: 76.5000 - loss: 0.5047 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 76ms/step - binary_accuracy: 0.8273 - false_negatives: 36.7500 - false_positives: 74.5000 - loss: 0.4287
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7648 - false_negatives: 80.2000 - false_positives: 91.0000 - loss: 0.4971 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8267 - false_negatives: 43.8000 - false_positives: 90.2000 - loss: 0.4287
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7705 - false_negatives: 87.1667 - false_positives: 106.8333 - loss: 0.4898 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8271 - false_negatives: 51.0000 - false_positives: 104.3333 - loss: 0.4277
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7750 - false_negatives: 95.8571 - false_positives: 121.1429 - loss: 0.4838 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8274 - false_negatives: 57.5714 - false_positives: 119.4286 - loss: 0.4266
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7789 - false_negatives: 103.2500 - false_positives: 136.3750 - loss: 0.4789 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8273 - false_negatives: 66.5000 - false_positives: 132.6250 - loss: 0.4259
``` - + ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7821 - false_negatives: 112.3333 - false_positives: 149.8889 - loss: 0.4749 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8261 - false_negatives: 74.0000 - false_positives: 150.1111 - loss: 0.4272
``` - + ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.7846 - false_negatives: 120.0000 - false_positives: 165.4000 - loss: 0.4717 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8244 - false_negatives: 85.0000 - false_positives: 165.5000 - loss: 0.4291
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7867 - false_negatives: 128.8182 - false_positives: 179.7273 - loss: 0.4690 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8231 - false_negatives: 95.0909 - false_positives: 181.2727 - loss: 0.4306
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7887 - false_negatives: 136.1667 - false_positives: 195.2500 - loss: 0.4667 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 104.5833 - false_positives: 196.4167 - loss: 0.4314
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7906 - false_negatives: 143.3846 - false_positives: 210.3077 - loss: 0.4644 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8215 - false_negatives: 113.8462 - false_positives: 212.2308 - loss: 0.4321
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7924 - false_negatives: 150.4286 - false_positives: 225.1429 - loss: 0.4620 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8209 - false_negatives: 123.1429 - false_positives: 227.3571 - loss: 0.4325
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7942 - false_negatives: 158.0667 - false_positives: 238.8000 - loss: 0.4596 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8205 - false_negatives: 132.1333 - false_positives: 242.4000 - loss: 0.4327
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7957 - false_negatives: 164.8750 - false_positives: 253.6250 - loss: 0.4575 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8203 - false_negatives: 141.1250 - false_positives: 256.9375 - loss: 0.4327
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7971 - false_negatives: 172.6471 - false_positives: 267.3529 - loss: 0.4555 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8202 - false_negatives: 149.5882 - false_positives: 271.5882 - loss: 0.4326
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.7983 - false_negatives: 179.7778 - false_positives: 282.2778 - loss: 0.4538 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8201 - false_negatives: 158.1667 - false_positives: 285.8889 - loss: 0.4322
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.7994 - false_negatives: 187.7895 - false_positives: 296.1053 - loss: 0.4523 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8201 - false_negatives: 166.3158 - false_positives: 300.4211 - loss: 0.4318
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8004 - false_negatives: 195.3000 - false_positives: 310.7500 - loss: 0.4510 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8201 - false_negatives: 174.7000 - false_positives: 314.8500 - loss: 0.4314
```  ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8014 - false_negatives: 202.8095 - false_positives: 325.0000 - loss: 0.4496 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8201 - false_negatives: 182.8095 - false_positives: 329.3333 - loss: 0.4309
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8023 - false_negatives: 209.9545 - false_positives: 339.5909 - loss: 0.4483 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8202 - false_negatives: 190.9091 - false_positives: 343.3182 - loss: 0.4305
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8031 - false_negatives: 217.4348 - false_positives: 354.0000 - loss: 0.4472 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8204 - false_negatives: 198.3478 - false_positives: 357.8261 - loss: 0.4299
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8039 - false_negatives: 224.4583 - false_positives: 368.5833 - loss: 0.4461 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8204 - false_negatives: 207.7083 - false_positives: 371.3750 - loss: 0.4296
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8047 - false_negatives: 231.5200 - false_positives: 382.8400 - loss: 0.4450 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8203 - false_negatives: 216.3200 - false_positives: 385.9600 - loss: 0.4295
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8055 - false_negatives: 238.5000 - false_positives: 396.9231 - loss: 0.4440 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8203 - false_negatives: 224.3462 - false_positives: 401.1538 - loss: 0.4293
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8063 - false_negatives: 245.3704 - false_positives: 410.8148 - loss: 0.4430 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8203 - false_negatives: 232.1481 - false_positives: 416.0370 - loss: 0.4291
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8070 - false_negatives: 252.2857 - false_positives: 424.7857 - loss: 0.4420 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8203 - false_negatives: 239.5357 - false_positives: 431.0000 - loss: 0.4288
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8078 - false_negatives: 259.1035 - false_positives: 438.6207 - loss: 0.4411 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8204 - false_negatives: 246.8276 - false_positives: 445.8621 - loss: 0.4284
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8085 - false_negatives: 265.7333 - false_positives: 452.4333 - loss: 0.4402 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8206 - false_negatives: 254.0000 - false_positives: 460.6000 - loss: 0.4281
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8091 - false_negatives: 273.5807 - false_positives: 465.5807 - loss: 0.4395 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8207 - false_negatives: 260.9355 - false_positives: 475.4516 - loss: 0.4277
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8096 - false_negatives: 280.9375 - false_positives: 480.0938 - loss: 0.4393 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8208 - false_negatives: 268.1250 - false_positives: 490.0000 - loss: 0.4273
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8099 - false_negatives: 287.9091 - false_positives: 495.8182 - loss: 0.4392 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8210 - false_negatives: 275.0909 - false_positives: 504.7879 - loss: 0.4269
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8102 - false_negatives: 294.5882 - false_positives: 512.0588 - loss: 0.4392 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8211 - false_negatives: 281.9118 - false_positives: 519.6177 - loss: 0.4264
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8105 - false_negatives: 300.9714 - false_positives: 528.6286 - loss: 0.4392 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8213 - false_negatives: 288.6857 - false_positives: 534.3143 - loss: 0.4260
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8108 - false_negatives: 307.3889 - false_positives: 545.1111 - loss: 0.4392 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8214 - false_negatives: 295.5000 - false_positives: 548.9445 - loss: 0.4256
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8111 - false_negatives: 313.9460 - false_positives: 561.4054 - loss: 0.4391 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8216 - false_negatives: 302.3243 - false_positives: 563.4054 - loss: 0.4252
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8113 - false_negatives: 320.4474 - false_positives: 578.0789 - loss: 0.4391 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8218 - false_negatives: 308.9737 - false_positives: 577.9211 - loss: 0.4247
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8115 - false_negatives: 327.3077 - false_positives: 594.4359 - loss: 0.4390 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8219 - false_negatives: 315.9744 - false_positives: 592.4359 - loss: 0.4243
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8117 - false_negatives: 334.0500 - false_positives: 610.7250 - loss: 0.4389 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8220 - false_negatives: 322.8250 - false_positives: 607.3750 - loss: 0.4240
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8119 - false_negatives: 340.8537 - false_positives: 626.8781 - loss: 0.4388 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8221 - false_negatives: 330.0488 - false_positives: 622.0975 - loss: 0.4238
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8121 - false_negatives: 347.4524 - false_positives: 643.2619 - loss: 0.4388 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8222 - false_negatives: 337.2381 - false_positives: 636.9762 - loss: 0.4235
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 354.2558 - false_positives: 659.3721 - loss: 0.4387 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 344.4419 - false_positives: 651.7907 - loss: 0.4233
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8125 - false_negatives: 361.0000 - false_positives: 675.4091 - loss: 0.4386 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 351.9773 - false_positives: 666.6818 - loss: 0.4230
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 368.2222 - false_positives: 691.0444 - loss: 0.4386 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8224 - false_negatives: 359.2889 - false_positives: 681.6889 - loss: 0.4228
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8129 - false_negatives: 375.2391 - false_positives: 706.8913 - loss: 0.4385 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8224 - false_negatives: 366.8478 - false_positives: 696.5652 - loss: 0.4226
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8130 - false_negatives: 382.7872 - false_positives: 722.4042 - loss: 0.4385 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8224 - false_negatives: 374.1915 - false_positives: 711.7021 - loss: 0.4225
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8132 - false_negatives: 390.2500 - false_positives: 738.1042 - loss: 0.4385 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8224 - false_negatives: 382.3750 - false_positives: 726.5208 - loss: 0.4224
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8133 - false_negatives: 397.7551 - false_positives: 753.6531 - loss: 0.4385 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8224 - false_negatives: 390.3469 - false_positives: 741.8163 - loss: 0.4223
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8134 - false_negatives: 405.2600 - false_positives: 769.1800 - loss: 0.4384 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 398.5800 - false_positives: 756.8800 - loss: 0.4222
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8135 - false_negatives: 413.6471 - false_positives: 784.2549 - loss: 0.4384 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 406.7451 - false_positives: 771.9804 - loss: 0.4221
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8136 - false_negatives: 421.7115 - false_positives: 799.9423 - loss: 0.4385 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8223 - false_negatives: 414.9231 - false_positives: 787.0769 - loss: 0.4221
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8137 - false_negatives: 430.1509 - false_positives: 815.2830 - loss: 0.4385 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8222 - false_negatives: 423.1698 - false_positives: 802.2264 - loss: 0.4220
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8137 - false_negatives: 438.5185 - false_positives: 830.8704 - loss: 0.4386 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8222 - false_negatives: 431.6482 - false_positives: 817.2222 - loss: 0.4220
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 447.1273 - false_positives: 846.1818 - loss: 0.4386 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8221 - false_negatives: 439.9636 - false_positives: 832.5818 - loss: 0.4220
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 455.5893 - false_positives: 861.7143 - loss: 0.4387 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8220 - false_negatives: 449.0179 - false_positives: 847.4821 - loss: 0.4220
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 464.1404 - false_positives: 877.0526 - loss: 0.4387 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8219 - false_negatives: 457.8421 - false_positives: 862.8947 - loss: 0.4220
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 472.7586 - false_positives: 892.2759 - loss: 0.4387 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8218 - false_negatives: 466.7758 - false_positives: 878.2414 - loss: 0.4221
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 481.2712 - false_positives: 907.7119 - loss: 0.4388 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8217 - false_negatives: 475.7966 - false_positives: 893.4915 - loss: 0.4221
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 490.8000 - false_positives: 922.6667 - loss: 0.4388 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8217 - false_negatives: 484.7667 - false_positives: 908.6833 - loss: 0.4222
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 500.0328 - false_positives: 938.1639 - loss: 0.4389 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8216 - false_negatives: 493.8033 - false_positives: 923.8525 - loss: 0.4223
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 509.4677 - false_positives: 953.5968 - loss: 0.4390 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8215 - false_negatives: 502.9355 - false_positives: 938.8871 - loss: 0.4223
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8139 - false_negatives: 518.9207 - false_positives: 968.9365 - loss: 0.4391 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8214 - false_negatives: 512.0793 - false_positives: 953.9524 - loss: 0.4224
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 528.3906 - false_positives: 984.2344 - loss: 0.4392 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8213 - false_negatives: 521.2812 - false_positives: 968.9531 - loss: 0.4224
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 538.0615 - false_positives: 999.4000 - loss: 0.4392 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8212 - false_negatives: 530.6000 - false_positives: 984.1230 - loss: 0.4225
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 547.6970 - false_positives: 1014.4697 - loss: 0.4393 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8211 - false_negatives: 539.9849 - false_positives: 999.0303 - loss: 0.4226
``` - + ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8138 - false_negatives: 557.3582 - false_positives: 1029.6567 - loss: 0.4394 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8210 - false_negatives: 549.4478 - false_positives: 1013.9702 - loss: 0.4226
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8137 - false_negatives: 567.4265 - false_positives: 1044.4854 - loss: 0.4394 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8209 - false_negatives: 558.9265 - false_positives: 1029.0294 - loss: 0.4227
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8137 - false_negatives: 577.2754 - false_positives: 1059.8986 - loss: 0.4395 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8208 - false_negatives: 568.7681 - false_positives: 1043.7826 - loss: 0.4228
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8136 - false_negatives: 587.5571 - false_positives: 1075.0143 - loss: 0.4396 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8207 - false_negatives: 578.4143 - false_positives: 1059.0428 - loss: 0.4229
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8135 - false_negatives: 597.7465 - false_positives: 1090.5352 - loss: 0.4398 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8206 - false_negatives: 588.4648 - false_positives: 1073.9860 - loss: 0.4230
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8135 - false_negatives: 608.1667 - false_positives: 1105.7084 - loss: 0.4399 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8205 - false_negatives: 598.5000 - false_positives: 1088.9166 - loss: 0.4231
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8134 - false_negatives: 618.4932 - false_positives: 1120.9589 - loss: 0.4400 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8204 - false_negatives: 608.5206 - false_positives: 1104.0273 - loss: 0.4232
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8133 - false_negatives: 629.0270 - false_positives: 1135.9865 - loss: 0.4401 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8202 - false_negatives: 618.8378 - false_positives: 1118.8513 - loss: 0.4233
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8133 - false_negatives: 639.4133 - false_positives: 1151.1067 - loss: 0.4402 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8201 - false_negatives: 629.0667 - false_positives: 1133.6133 - loss: 0.4234
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8132 - false_negatives: 649.8289 - false_positives: 1166.0132 - loss: 0.4402 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8200 - false_negatives: 639.3553 - false_positives: 1148.1842 - loss: 0.4235
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8132 - false_negatives: 660.4026 - false_positives: 1180.6624 - loss: 0.4403 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8199 - false_negatives: 649.7013 - false_positives: 1162.6624 - loss: 0.4235
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8131 - false_negatives: 670.8461 - false_positives: 1195.4744 - loss: 0.4404 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8198 - false_negatives: 660.0769 - false_positives: 1177.0641 - loss: 0.4236
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8131 - false_negatives: 681.6709 - false_positives: 1209.9873 - loss: 0.4404 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8197 - false_negatives: 670.5443 - false_positives: 1191.3291 - loss: 0.4237
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8130 - false_negatives: 692.2500 - false_positives: 1224.7125 - loss: 0.4405 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8196 - false_negatives: 680.9000 - false_positives: 1205.7000 - loss: 0.4237
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8130 - false_negatives: 702.8889 - false_positives: 1239.1975 - loss: 0.4406 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8196 - false_negatives: 691.4938 - false_positives: 1219.7902 - loss: 0.4238
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8129 - false_negatives: 713.5122 - false_positives: 1253.6219 - loss: 0.4406 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8195 - false_negatives: 701.8658 - false_positives: 1234.4878 - loss: 0.4239
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8129 - false_negatives: 724.1325 - false_positives: 1267.9036 - loss: 0.4406 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8194 - false_negatives: 712.3856 - false_positives: 1248.9518 - loss: 0.4240
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8129 - false_negatives: 734.7738 - false_positives: 1282.0834 - loss: 0.4407 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8193 - false_negatives: 722.9524 - false_positives: 1263.3928 - loss: 0.4241
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8128 - false_negatives: 745.3882 - false_positives: 1296.1882 - loss: 0.4407 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8192 - false_negatives: 733.6353 - false_positives: 1277.6588 - loss: 0.4241
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8128 - false_negatives: 756.2558 - false_positives: 1310.1163 - loss: 0.4407 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8191 - false_negatives: 744.2791 - false_positives: 1291.8954 - loss: 0.4242
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8128 - false_negatives: 766.9540 - false_positives: 1324.2413 - loss: 0.4408 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8190 - false_negatives: 754.9540 - false_positives: 1306.0229 - loss: 0.4243
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 777.8636 - false_positives: 1338.1818 - loss: 0.4408 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8189 - false_negatives: 765.6705 - false_positives: 1320.1023 - loss: 0.4243
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 788.7753 - false_positives: 1352.0449 - loss: 0.4408 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8188 - false_negatives: 776.4495 - false_positives: 1334.0674 - loss: 0.4244
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 799.6667 - false_positives: 1365.8223 - loss: 0.4408 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8187 - false_negatives: 787.2556 - false_positives: 1348.0111 - loss: 0.4244
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 810.5494 - false_positives: 1379.6154 - loss: 0.4408 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8187 - false_negatives: 798.1319 - false_positives: 1361.7913 - loss: 0.4245
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8127 - false_negatives: 821.5435 - false_positives: 1393.1957 - loss: 0.4409 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8186 - false_negatives: 808.8913 - false_positives: 1375.6957 - loss: 0.4245
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8126 - false_negatives: 832.4516 - false_positives: 1406.9032 - loss: 0.4409 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8185 - false_negatives: 819.8817 - false_positives: 1389.3441 - loss: 0.4246
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8126 - false_negatives: 843.6170 - false_positives: 1420.4468 - loss: 0.4409 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8185 - false_negatives: 830.7766 - false_positives: 1403.2446 - loss: 0.4247
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8126 - false_negatives: 854.8421 - false_positives: 1433.9684 - loss: 0.4409 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8184 - false_negatives: 841.7789 - false_positives: 1416.9158 - loss: 0.4247
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8126 - false_negatives: 866.0833 - false_positives: 1447.4896 - loss: 0.4409 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8183 - false_negatives: 852.7396 - false_positives: 1430.5312 - loss: 0.4247
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8125 - false_negatives: 877.2268 - false_positives: 1461.0000 - loss: 0.4409 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8183 - false_negatives: 863.7217 - false_positives: 1444.0619 - loss: 0.4248
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8125 - false_negatives: 888.6531 - false_positives: 1474.3368 - loss: 0.4409 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8182 - false_negatives: 874.7347 - false_positives: 1457.5000 - loss: 0.4248
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8125 - false_negatives: 899.9697 - false_positives: 1487.8586 - loss: 0.4409 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8181 - false_negatives: 885.7273 - false_positives: 1470.8990 - loss: 0.4248
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8125 - false_negatives: 911.4600 - false_positives: 1501.1700 - loss: 0.4409 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8181 - false_negatives: 896.8600 - false_positives: 1484.1300 - loss: 0.4249
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 922.8812 - false_positives: 1514.5544 - loss: 0.4409 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8180 - false_negatives: 907.9901 - false_positives: 1497.4357 - loss: 0.4249
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 934.3235 - false_positives: 1527.8137 - loss: 0.4409 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8180 - false_negatives: 919.2353 - false_positives: 1510.5883 - loss: 0.4249
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 945.6699 - false_positives: 1541.1262 - loss: 0.4409 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8179 - false_negatives: 930.3981 - false_positives: 1523.8932 - loss: 0.4249
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 956.9711 - false_positives: 1554.3269 - loss: 0.4409 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8179 - false_negatives: 941.7596 - false_positives: 1537.0673 - loss: 0.4249
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 968.3333 - false_positives: 1567.4095 - loss: 0.4409 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8178 - false_negatives: 953.0571 - false_positives: 1550.3334 - loss: 0.4250
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 979.5660 - false_positives: 1580.5944 - loss: 0.4408 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8178 - false_negatives: 964.3774 - false_positives: 1563.5000 - loss: 0.4250
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 991.0093 - false_positives: 1593.5701 - loss: 0.4408 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8177 - false_negatives: 975.7383 - false_positives: 1576.5514 - loss: 0.4250
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1002.2963 - false_positives: 1606.8889 - loss: 0.4408 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8177 - false_negatives: 986.9815 - false_positives: 1589.6852 - loss: 0.4250
``` - + ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1013.6697 - false_positives: 1620.0551 - loss: 0.4408 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8176 - false_negatives: 998.4312 - false_positives: 1602.5963 - loss: 0.4251
``` - + ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1025.0272 - false_positives: 1633.1909 - loss: 0.4408 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8176 - false_negatives: 1009.7364 - false_positives: 1615.7727 - loss: 0.4251
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1036.2703 - false_positives: 1646.3784 - loss: 0.4408 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8175 - false_negatives: 1021.1081 - false_positives: 1628.7928 - loss: 0.4251
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1047.6517 - false_positives: 1659.4286 - loss: 0.4407 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8175 - false_negatives: 1032.5267 - false_positives: 1641.6964 - loss: 0.4251
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1058.8850 - false_positives: 1672.6726 - loss: 0.4407 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8174 - false_negatives: 1043.8673 - false_positives: 1654.6549 - loss: 0.4251
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1070.2192 - false_positives: 1685.7456 - loss: 0.4407 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8174 - false_negatives: 1055.3334 - false_positives: 1667.5176 - loss: 0.4251
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1081.5044 - false_positives: 1698.9479 - loss: 0.4406 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8173 - false_negatives: 1066.7565 - false_positives: 1680.4435 - loss: 0.4251
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1092.8362 - false_positives: 1712.0431 - loss: 0.4406 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8173 - false_negatives: 1078.2587 - false_positives: 1693.2587 - loss: 0.4252
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1104.1709 - false_positives: 1725.0769 - loss: 0.4406 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8173 - false_negatives: 1089.6837 - false_positives: 1706.1196 - loss: 0.4252
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1115.4746 - false_positives: 1738.0763 - loss: 0.4405 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8172 - false_negatives: 1101.0509 - false_positives: 1719.0424 - loss: 0.4252
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1126.9160 - false_positives: 1750.9580 - loss: 0.4405 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8172 - false_negatives: 1112.5378 - false_positives: 1731.8488 - loss: 0.4252
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1138.2167 - false_positives: 1763.9584 - loss: 0.4405 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8171 - false_negatives: 1123.9250 - false_positives: 1744.7583 - loss: 0.4252
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1149.5702 - false_positives: 1776.8595 - loss: 0.4404 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8171 - false_negatives: 1135.4875 - false_positives: 1757.5289 - loss: 0.4252
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1160.8771 - false_positives: 1789.7377 - loss: 0.4404 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8171 - false_negatives: 1146.9426 - false_positives: 1770.3853 - loss: 0.4252
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1172.2277 - false_positives: 1802.4309 - loss: 0.4404 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8170 - false_negatives: 1158.6179 - false_positives: 1783.0569 - loss: 0.4252
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1183.4919 - false_positives: 1815.2822 - loss: 0.4403 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8170 - false_negatives: 1170.1613 - false_positives: 1795.9678 - loss: 0.4253
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1194.9520 - false_positives: 1828.0081 - loss: 0.4403 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8169 - false_negatives: 1181.6801 - false_positives: 1808.7679 - loss: 0.4253
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1206.3096 - false_positives: 1840.9048 - loss: 0.4402 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8169 - false_negatives: 1193.1746 - false_positives: 1821.5397 - loss: 0.4253
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1217.6614 - false_positives: 1853.7086 - loss: 0.4402 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8169 - false_negatives: 1204.6378 - false_positives: 1834.2205 - loss: 0.4253
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1228.9922 - false_positives: 1866.4531 - loss: 0.4402 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8168 - false_negatives: 1215.9844 - false_positives: 1846.9922 - loss: 0.4253
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1240.3566 - false_positives: 1879.0775 - loss: 0.4401 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8168 - false_negatives: 1227.4806 - false_positives: 1859.6124 - loss: 0.4253
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1251.6000 - false_positives: 1891.8231 - loss: 0.4401 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8168 - false_negatives: 1238.8616 - false_positives: 1872.3923 - loss: 0.4253
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1262.9008 - false_positives: 1904.4504 - loss: 0.4400 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8168 - false_negatives: 1250.2748 - false_positives: 1885.1375 - loss: 0.4253
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1274.1364 - false_positives: 1917.2803 - loss: 0.4400 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8167 - false_negatives: 1261.7046 - false_positives: 1897.8030 - loss: 0.4253
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1285.5338 - false_positives: 1929.9700 - loss: 0.4399 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8167 - false_negatives: 1273.1128 - false_positives: 1910.4512 - loss: 0.4253
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1296.8657 - false_positives: 1942.7239 - loss: 0.4399 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8167 - false_negatives: 1284.5149 - false_positives: 1923.0374 - loss: 0.4253
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1308.2518 - false_positives: 1955.4073 - loss: 0.4399 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8167 - false_negatives: 1295.8740 - false_positives: 1935.6519 - loss: 0.4253
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1319.6691 - false_positives: 1968.0294 - loss: 0.4398 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8166 - false_negatives: 1307.2573 - false_positives: 1948.2427 - loss: 0.4253
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1331.1241 - false_positives: 1980.5620 - loss: 0.4398 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8166 - false_negatives: 1318.6423 - false_positives: 1960.7518 - loss: 0.4253
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1342.5289 - false_positives: 1993.0072 - loss: 0.4397 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8166 - false_negatives: 1329.9565 - false_positives: 1973.2681 - loss: 0.4253
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1353.9496 - false_positives: 2005.3525 - loss: 0.4397 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8166 - false_negatives: 1341.4244 - false_positives: 1985.6475 - loss: 0.4253
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1365.2928 - false_positives: 2017.7285 - loss: 0.4396 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8165 - false_negatives: 1352.7572 - false_positives: 1998.4071 - loss: 0.4253
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1376.6595 - false_positives: 2030.0283 - loss: 0.4396 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8165 - false_negatives: 1364.4255 - false_positives: 2011.0212 - loss: 0.4253
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8122 - false_negatives: 1387.9648 - false_positives: 2042.3733 - loss: 0.4395 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8165 - false_negatives: 1376.1198 - false_positives: 2023.5775 - loss: 0.4253
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1399.3427 - false_positives: 2054.6084 - loss: 0.4395 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8165 - false_negatives: 1387.8672 - false_positives: 2036.0420 - loss: 0.4253
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1410.6250 - false_positives: 2066.9514 - loss: 0.4394 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8164 - false_negatives: 1399.5486 - false_positives: 2048.5068 - loss: 0.4253
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1422.0828 - false_positives: 2079.1311 - loss: 0.4394 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8164 - false_negatives: 1411.2413 - false_positives: 2060.9448 - loss: 0.4253
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1433.4178 - false_positives: 2091.5342 - loss: 0.4393 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8164 - false_negatives: 1422.9657 - false_positives: 2073.3972 - loss: 0.4253
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1444.8844 - false_positives: 2103.8096 - loss: 0.4393 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8164 - false_negatives: 1434.6735 - false_positives: 2085.8640 - loss: 0.4253
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1456.3243 - false_positives: 2116.1555 - loss: 0.4392 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8163 - false_negatives: 1446.4257 - false_positives: 2098.2568 - loss: 0.4253
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1467.7651 - false_positives: 2128.4631 - loss: 0.4392 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8163 - false_negatives: 1458.1343 - false_positives: 2110.6511 - loss: 0.4253
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1479.1934 - false_positives: 2140.7534 - loss: 0.4391 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8163 - false_negatives: 1469.8334 - false_positives: 2122.9934 - loss: 0.4253
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1490.6490 - false_positives: 2153.0198 - loss: 0.4391 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8163 - false_negatives: 1481.4901 - false_positives: 2135.3376 - loss: 0.4253
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1502.1710 - false_positives: 2165.2368 - loss: 0.4390 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8163 - false_negatives: 1493.1052 - false_positives: 2147.6250 - loss: 0.4253
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8123 - false_negatives: 1513.6602 - false_positives: 2177.4575 - loss: 0.4390 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8162 - false_negatives: 1504.8170 - false_positives: 2159.8430 - loss: 0.4253
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 1525.2598 - false_positives: 2189.5779 - loss: 0.4389 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8162 - false_negatives: 1516.4286 - false_positives: 2172.3376 - loss: 0.4253
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 1536.7677 - false_positives: 2201.8708 - loss: 0.4389 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8162 - false_negatives: 1528.1226 - false_positives: 2184.7161 - loss: 0.4253
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8124 - false_negatives: 1548.4359 - false_positives: 2214.0706 - loss: 0.4388 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8162 - false_negatives: 1539.7693 - false_positives: 2197.1475 - loss: 0.4254
``` -Epoch 3: val_loss improved from 0.43786 to 0.38213, saving model to FullModelCheckpoint.keras +Epoch 3: val_loss improved from 0.41756 to 0.38233, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8124 - false_negatives: 1571.3925 - false_positives: 2238.1204 - loss: 0.4388 - val_binary_accuracy: 0.8386 - val_false_negatives: 463.0000 - val_false_positives: 344.0000 - val_loss: 0.3821 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8161 - false_negatives: 1562.6962 - false_positives: 2221.5886 - loss: 0.4254 - val_binary_accuracy: 0.8340 - val_false_negatives: 496.0000 - val_false_positives: 334.0000 - val_loss: 0.3823
@@ -3730,1102 +3718,1102 @@ Epoch 4/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.7812 - false_negatives: 39.0000 - false_positives: 17.0000 - loss: 0.4516 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.8516 - false_negatives: 26.0000 - false_positives: 12.0000 - loss: 0.3925
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.7969 - false_negatives: 45.0000 - false_positives: 31.0000 - loss: 0.4370 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8281 - false_negatives: 33.0000 - false_positives: 36.0000 - loss: 0.4243
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8060 - false_negatives: 51.0000 - false_positives: 44.6667 - loss: 0.4250 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8320 - false_negatives: 38.6667 - false_positives: 48.3333 - loss: 0.4208
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8113 - false_negatives: 58.7500 - false_positives: 57.2500 - loss: 0.4187 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8350 - false_negatives: 46.0000 - false_positives: 59.2500 - loss: 0.4155
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8162 - false_negatives: 64.8000 - false_positives: 70.0000 - loss: 0.4116 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8370 - false_negatives: 52.4000 - false_positives: 71.4000 - loss: 0.4098
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8182 - false_negatives: 76.6667 - false_positives: 79.6667 - loss: 0.4093 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8392 - false_negatives: 59.1667 - false_positives: 82.3333 - loss: 0.4042
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8185 - false_negatives: 85.8571 - false_positives: 94.1429 - loss: 0.4107 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8409 - false_negatives: 66.4286 - false_positives: 93.0000 - loss: 0.3999
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8189 - false_negatives: 96.3750 - false_positives: 106.7500 - loss: 0.4119 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8426 - false_negatives: 73.5000 - false_positives: 103.3750 - loss: 0.3960
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8197 - false_negatives: 105.3333 - false_positives: 119.7778 - loss: 0.4119 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8439 - false_negatives: 80.4444 - false_positives: 114.0000 - loss: 0.3926
``` - + ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8207 - false_negatives: 113.4000 - false_positives: 132.8000 - loss: 0.4111 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8440 - false_negatives: 91.1000 - false_positives: 123.5000 - loss: 0.3914
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8218 - false_negatives: 121.1818 - false_positives: 145.5455 - loss: 0.4101 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8435 - false_negatives: 99.9091 - false_positives: 136.6364 - loss: 0.3925
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8224 - false_negatives: 129.3333 - false_positives: 158.7500 - loss: 0.4093 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8430 - false_negatives: 108.9167 - false_positives: 149.4167 - loss: 0.3933
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8229 - false_negatives: 137.3846 - false_positives: 172.4615 - loss: 0.4086 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8426 - false_negatives: 117.4615 - false_positives: 162.6154 - loss: 0.3939
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8233 - false_negatives: 146.4286 - false_positives: 185.1429 - loss: 0.4080 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8424 - false_negatives: 125.5000 - false_positives: 175.5000 - loss: 0.3942
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8237 - false_negatives: 154.6000 - false_positives: 198.4667 - loss: 0.4073 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8422 - false_negatives: 133.1333 - false_positives: 188.8667 - loss: 0.3943
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8241 - false_negatives: 163.5000 - false_positives: 211.0625 - loss: 0.4067 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8423 - false_negatives: 140.6875 - false_positives: 201.3125 - loss: 0.3941
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8246 - false_negatives: 171.7647 - false_positives: 223.7647 - loss: 0.4061 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8423 - false_negatives: 148.2353 - false_positives: 214.0588 - loss: 0.3939
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8253 - false_negatives: 179.3889 - false_positives: 235.9444 - loss: 0.4053 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8423 - false_negatives: 155.2778 - false_positives: 227.1111 - loss: 0.3935
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8260 - false_negatives: 187.1579 - false_positives: 247.5789 - loss: 0.4043 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8423 - false_negatives: 163.2105 - false_positives: 239.3684 - loss: 0.3931
```  ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8267 - false_negatives: 194.2500 - false_positives: 259.7000 - loss: 0.4034 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8424 - false_negatives: 170.5000 - false_positives: 252.0500 - loss: 0.3926
```  ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8274 - false_negatives: 201.7143 - false_positives: 271.1429 - loss: 0.4024 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8425 - false_negatives: 177.5714 - false_positives: 264.3810 - loss: 0.3920
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8280 - false_negatives: 208.6364 - false_positives: 283.4091 - loss: 0.4016 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8427 - false_negatives: 184.4545 - false_positives: 276.7273 - loss: 0.3915
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8286 - false_negatives: 216.3044 - false_positives: 295.1304 - loss: 0.4009 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8429 - false_negatives: 191.5652 - false_positives: 288.8261 - loss: 0.3909
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8291 - false_negatives: 223.4583 - false_positives: 307.2917 - loss: 0.4001 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8431 - false_negatives: 198.6250 - false_positives: 300.9167 - loss: 0.3903
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8296 - false_negatives: 230.4400 - false_positives: 319.4800 - loss: 0.3994 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8432 - false_negatives: 205.4400 - false_positives: 313.2800 - loss: 0.3896
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8301 - false_negatives: 237.3462 - false_positives: 331.8077 - loss: 0.3987 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8433 - false_negatives: 212.9231 - false_positives: 325.2308 - loss: 0.3891
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8306 - false_negatives: 244.3333 - false_positives: 344.1111 - loss: 0.3980 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8434 - false_negatives: 219.9630 - false_positives: 337.8889 - loss: 0.3886
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8310 - false_negatives: 251.1071 - false_positives: 356.2500 - loss: 0.3972 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8434 - false_negatives: 227.4643 - false_positives: 350.2857 - loss: 0.3883
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8316 - false_negatives: 257.6897 - false_positives: 368.1035 - loss: 0.3964 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8435 - false_negatives: 234.7586 - false_positives: 362.8621 - loss: 0.3879
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8321 - false_negatives: 263.9333 - false_positives: 379.8667 - loss: 0.3956 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8436 - false_negatives: 241.9667 - false_positives: 375.1000 - loss: 0.3875
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8325 - false_negatives: 271.0968 - false_positives: 391.5484 - loss: 0.3949 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8437 - false_negatives: 248.9032 - false_positives: 387.5807 - loss: 0.3871
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8329 - false_negatives: 277.9062 - false_positives: 403.5625 - loss: 0.3942 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8438 - false_negatives: 255.6875 - false_positives: 399.8750 - loss: 0.3866
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8333 - false_negatives: 284.8788 - false_positives: 415.2727 - loss: 0.3936 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8439 - false_negatives: 262.2424 - false_positives: 412.2727 - loss: 0.3862
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8337 - false_negatives: 291.5882 - false_positives: 427.2941 - loss: 0.3930 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8440 - false_negatives: 268.7059 - false_positives: 425.0882 - loss: 0.3858
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8341 - false_negatives: 298.6857 - false_positives: 439.0000 - loss: 0.3924 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8441 - false_negatives: 276.0857 - false_positives: 437.3714 - loss: 0.3856
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8344 - false_negatives: 305.4722 - false_positives: 451.1111 - loss: 0.3919 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8441 - false_negatives: 283.1667 - false_positives: 450.1389 - loss: 0.3854
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8348 - false_negatives: 312.3784 - false_positives: 462.8378 - loss: 0.3914 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8442 - false_negatives: 290.1351 - false_positives: 462.7027 - loss: 0.3852
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8351 - false_negatives: 319.2895 - false_positives: 474.8421 - loss: 0.3910 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8442 - false_negatives: 297.0789 - false_positives: 475.2105 - loss: 0.3849
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8354 - false_negatives: 326.4102 - false_positives: 486.8462 - loss: 0.3905 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8443 - false_negatives: 303.8462 - false_positives: 487.8718 - loss: 0.3847
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8356 - false_negatives: 333.4000 - false_positives: 498.9000 - loss: 0.3901 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8443 - false_negatives: 310.8000 - false_positives: 500.4750 - loss: 0.3845
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8359 - false_negatives: 340.4390 - false_positives: 510.9268 - loss: 0.3897 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8444 - false_negatives: 317.6829 - false_positives: 513.0000 - loss: 0.3843
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8361 - false_negatives: 347.2619 - false_positives: 523.1667 - loss: 0.3893 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8445 - false_negatives: 324.4524 - false_positives: 525.5000 - loss: 0.3841
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8363 - false_negatives: 354.6977 - false_positives: 535.1860 - loss: 0.3890 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8445 - false_negatives: 331.1628 - false_positives: 538.0930 - loss: 0.3839
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8365 - false_negatives: 361.8636 - false_positives: 547.5455 - loss: 0.3886 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 338.3409 - false_positives: 550.4773 - loss: 0.3836
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8367 - false_negatives: 369.7333 - false_positives: 559.6667 - loss: 0.3884 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 345.2222 - false_positives: 563.2444 - loss: 0.3835
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8368 - false_negatives: 377.4131 - false_positives: 572.0435 - loss: 0.3881 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 352.5000 - false_positives: 575.7174 - loss: 0.3833
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8369 - false_negatives: 385.3617 - false_positives: 584.0425 - loss: 0.3878 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 359.5745 - false_positives: 588.5958 - loss: 0.3832
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8371 - false_negatives: 393.1667 - false_positives: 596.3750 - loss: 0.3876 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 366.9792 - false_positives: 601.1042 - loss: 0.3831
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8372 - false_negatives: 401.1224 - false_positives: 608.4898 - loss: 0.3874 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 374.2653 - false_positives: 613.7755 - loss: 0.3830
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8373 - false_negatives: 408.9400 - false_positives: 620.7200 - loss: 0.3871 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 381.6000 - false_positives: 626.3600 - loss: 0.3829
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8374 - false_negatives: 417.0784 - false_positives: 632.6863 - loss: 0.3869 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 389.0196 - false_positives: 638.8823 - loss: 0.3829
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8375 - false_negatives: 424.9231 - false_positives: 645.2308 - loss: 0.3868 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 396.2885 - false_positives: 651.3269 - loss: 0.3827
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8375 - false_negatives: 433.5094 - false_positives: 657.3774 - loss: 0.3867 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 403.7358 - false_positives: 663.5283 - loss: 0.3826
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8376 - false_negatives: 441.8148 - false_positives: 669.8519 - loss: 0.3866 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 411.1482 - false_positives: 676.0370 - loss: 0.3825
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8376 - false_negatives: 450.1273 - false_positives: 682.3636 - loss: 0.3866 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 419.1273 - false_positives: 688.1636 - loss: 0.3825
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8376 - false_negatives: 458.4821 - false_positives: 694.8214 - loss: 0.3865 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 427.0179 - false_positives: 700.4286 - loss: 0.3824
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8377 - false_negatives: 466.8596 - false_positives: 707.1053 - loss: 0.3864 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 434.8772 - false_positives: 712.6316 - loss: 0.3823
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8377 - false_negatives: 475.2931 - false_positives: 719.4138 - loss: 0.3863 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 442.9310 - false_positives: 724.7414 - loss: 0.3822
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 483.9153 - false_positives: 731.5593 - loss: 0.3863 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8447 - false_negatives: 450.8813 - false_positives: 737.0339 - loss: 0.3822
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 492.4333 - false_positives: 744.0000 - loss: 0.3862 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 459.0000 - false_positives: 749.1667 - loss: 0.3821
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 501.1311 - false_positives: 756.1639 - loss: 0.3861 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 467.0164 - false_positives: 761.3442 - loss: 0.3820
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 509.7742 - false_positives: 768.2581 - loss: 0.3860 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 475.2581 - false_positives: 773.3549 - loss: 0.3820
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 518.4286 - false_positives: 780.2698 - loss: 0.3860 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 483.3175 - false_positives: 785.7460 - loss: 0.3820
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 527.1875 - false_positives: 792.1719 - loss: 0.3859 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8445 - false_negatives: 491.7656 - false_positives: 797.8906 - loss: 0.3820
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 535.8000 - false_positives: 804.2000 - loss: 0.3858 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8445 - false_negatives: 500.1077 - false_positives: 810.3231 - loss: 0.3820
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 544.7121 - false_positives: 816.0606 - loss: 0.3857 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8444 - false_negatives: 508.5454 - false_positives: 822.6061 - loss: 0.3820
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 553.4926 - false_positives: 828.2836 - loss: 0.3857 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8444 - false_negatives: 516.8508 - false_positives: 835.1343 - loss: 0.3820
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 562.4706 - false_positives: 840.3235 - loss: 0.3857 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8443 - false_negatives: 525.4117 - false_positives: 847.3677 - loss: 0.3820
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 571.5507 - false_positives: 852.2174 - loss: 0.3856 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8443 - false_negatives: 533.9420 - false_positives: 859.5652 - loss: 0.3820
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 580.6000 - false_positives: 864.1000 - loss: 0.3856 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8443 - false_negatives: 542.5000 - false_positives: 871.6572 - loss: 0.3820
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 589.6057 - false_positives: 876.0704 - loss: 0.3855 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8442 - false_negatives: 551.0845 - false_positives: 883.7606 - loss: 0.3820
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 598.7778 - false_positives: 887.9722 - loss: 0.3855 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8442 - false_negatives: 559.8055 - false_positives: 895.7361 - loss: 0.3820
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 607.9178 - false_positives: 899.7123 - loss: 0.3854 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8441 - false_negatives: 568.4247 - false_positives: 907.7808 - loss: 0.3820
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 617.0811 - false_positives: 911.2703 - loss: 0.3854 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8441 - false_negatives: 577.3649 - false_positives: 919.5541 - loss: 0.3820
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 626.0667 - false_positives: 923.2400 - loss: 0.3854 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8441 - false_negatives: 586.1334 - false_positives: 931.6400 - loss: 0.3820
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 635.6053 - false_positives: 934.9079 - loss: 0.3853 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8440 - false_negatives: 595.3026 - false_positives: 943.4868 - loss: 0.3820
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 644.9351 - false_positives: 946.7532 - loss: 0.3853 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8440 - false_negatives: 604.3506 - false_positives: 955.4286 - loss: 0.3820
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 654.1923 - false_positives: 958.6795 - loss: 0.3853 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8439 - false_negatives: 613.5128 - false_positives: 967.2692 - loss: 0.3821
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 663.5190 - false_positives: 970.5063 - loss: 0.3853 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8438 - false_negatives: 622.7089 - false_positives: 979.1266 - loss: 0.3821
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 672.8250 - false_positives: 982.2750 - loss: 0.3853 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8438 - false_negatives: 631.8875 - false_positives: 990.9250 - loss: 0.3821
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 682.2839 - false_positives: 993.9136 - loss: 0.3853 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8437 - false_negatives: 641.1729 - false_positives: 1002.6543 - loss: 0.3821
``` - + ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 691.6951 - false_positives: 1005.5000 - loss: 0.3853 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8437 - false_negatives: 650.4390 - false_positives: 1014.2683 - loss: 0.3821
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 701.1687 - false_positives: 1017.0000 - loss: 0.3852 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8437 - false_negatives: 659.6506 - false_positives: 1025.9398 - loss: 0.3822
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 710.7381 - false_positives: 1028.3690 - loss: 0.3852 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8436 - false_negatives: 669.0476 - false_positives: 1037.4286 - loss: 0.3822
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 720.2000 - false_positives: 1039.8470 - loss: 0.3852 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8436 - false_negatives: 678.2941 - false_positives: 1049.1530 - loss: 0.3822
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 729.8953 - false_positives: 1051.1279 - loss: 0.3852 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8435 - false_negatives: 687.8140 - false_positives: 1060.6511 - loss: 0.3822
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 739.4943 - false_positives: 1062.5287 - loss: 0.3852 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8435 - false_negatives: 697.2874 - false_positives: 1072.1265 - loss: 0.3823
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 749.1136 - false_positives: 1073.8750 - loss: 0.3851 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8434 - false_negatives: 706.7614 - false_positives: 1083.5682 - loss: 0.3823
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 758.6517 - false_positives: 1085.1686 - loss: 0.3851 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8434 - false_negatives: 716.2809 - false_positives: 1094.9438 - loss: 0.3823
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 768.1778 - false_positives: 1096.3778 - loss: 0.3851 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8433 - false_negatives: 725.8000 - false_positives: 1106.3778 - loss: 0.3823
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 777.7143 - false_positives: 1107.5714 - loss: 0.3851 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8433 - false_negatives: 735.4615 - false_positives: 1117.6593 - loss: 0.3823
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 787.3696 - false_positives: 1118.6305 - loss: 0.3851 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8433 - false_negatives: 744.9891 - false_positives: 1128.9674 - loss: 0.3823
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 796.9462 - false_positives: 1129.8064 - loss: 0.3850 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8432 - false_negatives: 754.6667 - false_positives: 1140.1290 - loss: 0.3823
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 806.8511 - false_positives: 1140.7979 - loss: 0.3850 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8432 - false_negatives: 764.2766 - false_positives: 1151.2872 - loss: 0.3824
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 816.6000 - false_positives: 1152.0842 - loss: 0.3850 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8432 - false_negatives: 774.0316 - false_positives: 1162.3158 - loss: 0.3824
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 826.6354 - false_positives: 1163.2084 - loss: 0.3851 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8431 - false_negatives: 783.6875 - false_positives: 1173.3750 - loss: 0.3824
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 836.6288 - false_positives: 1174.3196 - loss: 0.3851 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8431 - false_negatives: 793.3196 - false_positives: 1184.3093 - loss: 0.3824
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8381 - false_negatives: 846.7449 - false_positives: 1185.3776 - loss: 0.3851 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8431 - false_negatives: 802.9694 - false_positives: 1195.2347 - loss: 0.3824
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 856.8081 - false_positives: 1196.4343 - loss: 0.3851 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8431 - false_negatives: 812.9798 - false_positives: 1205.9596 - loss: 0.3824
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 866.7900 - false_positives: 1207.3900 - loss: 0.3851 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8430 - false_negatives: 822.8200 - false_positives: 1217.1200 - loss: 0.3824
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 876.8614 - false_positives: 1218.3168 - loss: 0.3851 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8430 - false_negatives: 832.8812 - false_positives: 1228.1486 - loss: 0.3825
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 886.8922 - false_positives: 1229.1765 - loss: 0.3851 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8429 - false_negatives: 842.9020 - false_positives: 1239.1471 - loss: 0.3825
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 896.9515 - false_positives: 1239.9418 - loss: 0.3851 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8429 - false_negatives: 852.8641 - false_positives: 1250.2330 - loss: 0.3826
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 906.9808 - false_positives: 1250.7307 - loss: 0.3851 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8429 - false_negatives: 862.8173 - false_positives: 1261.2885 - loss: 0.3826
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 917.2095 - false_positives: 1261.4476 - loss: 0.3851 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8428 - false_negatives: 872.8095 - false_positives: 1272.2572 - loss: 0.3826
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 927.3019 - false_positives: 1272.4434 - loss: 0.3851 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8428 - false_negatives: 882.8302 - false_positives: 1283.1698 - loss: 0.3827
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 937.6168 - false_positives: 1283.2710 - loss: 0.3851 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8428 - false_negatives: 892.8037 - false_positives: 1294.0841 - loss: 0.3827
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 947.8704 - false_positives: 1294.0648 - loss: 0.3851 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8427 - false_negatives: 902.9445 - false_positives: 1304.8982 - loss: 0.3827
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 958.1101 - false_positives: 1304.8624 - loss: 0.3851 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8427 - false_negatives: 913.0551 - false_positives: 1315.8533 - loss: 0.3828
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 968.4000 - false_positives: 1315.5909 - loss: 0.3852 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8426 - false_negatives: 923.2455 - false_positives: 1326.8273 - loss: 0.3828
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 978.6667 - false_positives: 1326.4685 - loss: 0.3852 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8426 - false_negatives: 933.4144 - false_positives: 1337.7838 - loss: 0.3828
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 989.1339 - false_positives: 1337.2322 - loss: 0.3852 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8426 - false_negatives: 943.6786 - false_positives: 1348.6964 - loss: 0.3829
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 999.4691 - false_positives: 1348.1239 - loss: 0.3852 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8425 - false_negatives: 953.8584 - false_positives: 1359.6549 - loss: 0.3829
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 1009.9298 - false_positives: 1358.8596 - loss: 0.3852 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8425 - false_negatives: 964.0526 - false_positives: 1370.5438 - loss: 0.3829
``` - + ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 1020.3478 - false_positives: 1369.6348 - loss: 0.3852 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8425 - false_negatives: 974.2609 - false_positives: 1381.4000 - loss: 0.3829
``` - + ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8380 - false_negatives: 1030.8793 - false_positives: 1380.2844 - loss: 0.3852 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8424 - false_negatives: 984.5086 - false_positives: 1392.1897 - loss: 0.3830
``` - + ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1041.3419 - false_positives: 1390.9487 - loss: 0.3853 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8424 - false_negatives: 994.7350 - false_positives: 1403.0085 - loss: 0.3830
``` - + ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1051.8390 - false_positives: 1401.5677 - loss: 0.3853 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8424 - false_negatives: 1005.1187 - false_positives: 1413.6949 - loss: 0.3830
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1062.2773 - false_positives: 1412.1932 - loss: 0.3853 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8423 - false_negatives: 1015.3782 - false_positives: 1424.5883 - loss: 0.3830
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1072.7333 - false_positives: 1422.7667 - loss: 0.3853 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8423 - false_negatives: 1025.7833 - false_positives: 1435.3750 - loss: 0.3831
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1083.1405 - false_positives: 1433.3472 - loss: 0.3853 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8422 - false_negatives: 1036.1405 - false_positives: 1446.2231 - loss: 0.3831
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1093.7377 - false_positives: 1443.7950 - loss: 0.3853 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8422 - false_negatives: 1046.4836 - false_positives: 1457.0984 - loss: 0.3831
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1104.1708 - false_positives: 1454.7236 - loss: 0.3853 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8422 - false_negatives: 1056.8781 - false_positives: 1467.8943 - loss: 0.3831
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1114.6451 - false_positives: 1465.5807 - loss: 0.3853 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8421 - false_negatives: 1067.2500 - false_positives: 1478.7339 - loss: 0.3832
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1125.1680 - false_positives: 1476.3840 - loss: 0.3854 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8421 - false_negatives: 1077.6080 - false_positives: 1489.5439 - loss: 0.3832
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1135.6825 - false_positives: 1487.1825 - loss: 0.3854 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8421 - false_negatives: 1087.9524 - false_positives: 1500.3096 - loss: 0.3832
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1146.2599 - false_positives: 1497.8503 - loss: 0.3854 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8420 - false_negatives: 1098.2284 - false_positives: 1511.0867 - loss: 0.3832
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1156.7266 - false_positives: 1508.5547 - loss: 0.3854 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8420 - false_negatives: 1108.5625 - false_positives: 1521.7422 - loss: 0.3832
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1167.3411 - false_positives: 1519.1473 - loss: 0.3854 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8420 - false_negatives: 1118.7906 - false_positives: 1532.5814 - loss: 0.3833
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1177.8770 - false_positives: 1529.7539 - loss: 0.3855 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8419 - false_negatives: 1129.1154 - false_positives: 1543.3231 - loss: 0.3833
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1188.3588 - false_positives: 1540.3206 - loss: 0.3855 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8419 - false_negatives: 1139.3282 - false_positives: 1554.2213 - loss: 0.3833
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1198.8939 - false_positives: 1550.8334 - loss: 0.3855 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8419 - false_negatives: 1149.6895 - false_positives: 1564.9773 - loss: 0.3833
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1209.4286 - false_positives: 1561.2632 - loss: 0.3855 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8418 - false_negatives: 1160.0300 - false_positives: 1575.7294 - loss: 0.3833
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1219.8955 - false_positives: 1571.7462 - loss: 0.3855 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8418 - false_negatives: 1170.3582 - false_positives: 1586.4701 - loss: 0.3834
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1230.4592 - false_positives: 1582.0963 - loss: 0.3855 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8418 - false_negatives: 1180.6963 - false_positives: 1597.1777 - loss: 0.3834
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1240.9633 - false_positives: 1592.4559 - loss: 0.3855 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8418 - false_negatives: 1191.0000 - false_positives: 1607.8235 - loss: 0.3834
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1251.5182 - false_positives: 1602.7737 - loss: 0.3855 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8417 - false_negatives: 1201.3358 - false_positives: 1618.4160 - loss: 0.3834
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1262.0145 - false_positives: 1613.1305 - loss: 0.3855 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8417 - false_negatives: 1211.6160 - false_positives: 1628.9855 - loss: 0.3834
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1272.5468 - false_positives: 1623.4172 - loss: 0.3855 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8417 - false_negatives: 1221.9281 - false_positives: 1639.5251 - loss: 0.3834
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1282.9928 - false_positives: 1633.6571 - loss: 0.3855 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8417 - false_negatives: 1232.1714 - false_positives: 1650.0286 - loss: 0.3834
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1293.4114 - false_positives: 1643.8723 - loss: 0.3855 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8417 - false_negatives: 1242.4965 - false_positives: 1660.4823 - loss: 0.3834
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1303.8240 - false_positives: 1654.0282 - loss: 0.3854 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8416 - false_negatives: 1252.7747 - false_positives: 1671.0211 - loss: 0.3835
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1314.2028 - false_positives: 1664.2378 - loss: 0.3854 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8416 - false_negatives: 1263.1958 - false_positives: 1681.4685 - loss: 0.3835
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1324.8055 - false_positives: 1674.3403 - loss: 0.3854 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8416 - false_negatives: 1273.5070 - false_positives: 1692.0972 - loss: 0.3835
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1335.3173 - false_positives: 1684.5931 - loss: 0.3854 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8416 - false_negatives: 1284.1379 - false_positives: 1702.5931 - loss: 0.3835
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1345.9727 - false_positives: 1694.7329 - loss: 0.3854 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8415 - false_negatives: 1294.7261 - false_positives: 1713.1986 - loss: 0.3835
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1356.5851 - false_positives: 1704.8435 - loss: 0.3854 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8415 - false_negatives: 1305.2789 - false_positives: 1723.8639 - loss: 0.3835
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1367.1959 - false_positives: 1714.9189 - loss: 0.3854 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8415 - false_negatives: 1315.8918 - false_positives: 1734.4662 - loss: 0.3836
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1377.7517 - false_positives: 1725.0537 - loss: 0.3854 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8415 - false_negatives: 1326.5436 - false_positives: 1745.0739 - loss: 0.3836
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1388.3267 - false_positives: 1735.1466 - loss: 0.3854 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8414 - false_negatives: 1337.1400 - false_positives: 1755.7200 - loss: 0.3836
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1398.9337 - false_positives: 1745.2119 - loss: 0.3854 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8414 - false_negatives: 1347.7550 - false_positives: 1766.3113 - loss: 0.3836
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8378 - false_negatives: 1409.5132 - false_positives: 1755.2698 - loss: 0.3854 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8414 - false_negatives: 1358.3552 - false_positives: 1776.8552 - loss: 0.3836
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1420.1830 - false_positives: 1765.2810 - loss: 0.3854 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8413 - false_negatives: 1368.9347 - false_positives: 1787.3726 - loss: 0.3837
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1430.7467 - false_positives: 1775.4026 - loss: 0.3854 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8413 - false_negatives: 1379.4415 - false_positives: 1797.8636 - loss: 0.3837
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1441.4193 - false_positives: 1785.4517 - loss: 0.3854 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8413 - false_negatives: 1390.0581 - false_positives: 1808.2581 - loss: 0.3837
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8379 - false_negatives: 1452.0449 - false_positives: 1795.5834 - loss: 0.3854 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8413 - false_negatives: 1400.6538 - false_positives: 1818.7372 - loss: 0.3837
``` -Epoch 4: val_loss improved from 0.38213 to 0.37839, saving model to FullModelCheckpoint.keras +Epoch 4: val_loss improved from 0.38233 to 0.36235, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8379 - false_negatives: 1472.9557 - false_positives: 1815.4873 - loss: 0.3854 - val_binary_accuracy: 0.8328 - val_false_negatives: 626.0000 - val_false_positives: 210.0000 - val_loss: 0.3784 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8412 - false_negatives: 1421.5063 - false_positives: 1839.3102 - loss: 0.3838 - val_binary_accuracy: 0.8396 - val_false_negatives: 548.0000 - val_false_positives: 254.0000 - val_loss: 0.3623
@@ -4835,1102 +4823,1102 @@ Epoch 5/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 94ms/step - binary_accuracy: 0.8125 - false_negatives: 37.0000 - false_positives: 11.0000 - loss: 0.4438 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.8477 - false_negatives: 35.0000 - false_positives: 4.0000 - loss: 0.4281
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 76ms/step - binary_accuracy: 0.8184 - false_negatives: 43.5000 - false_positives: 25.5000 - loss: 0.4150 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8398 - false_negatives: 35.0000 - false_positives: 27.5000 - loss: 0.4217
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8199 - false_negatives: 51.6667 - false_positives: 39.6667 - loss: 0.4048 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8407 - false_negatives: 42.3333 - false_positives: 39.6667 - loss: 0.4110
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8229 - false_negatives: 56.7500 - false_positives: 54.7500 - loss: 0.3975 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8446 - false_negatives: 47.7500 - false_positives: 50.5000 - loss: 0.4013
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8257 - false_negatives: 64.8000 - false_positives: 66.2000 - loss: 0.3912 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8481 - false_negatives: 52.6000 - false_positives: 61.4000 - loss: 0.3924
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8278 - false_negatives: 72.1667 - false_positives: 78.3333 - loss: 0.3871 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8511 - false_negatives: 57.6667 - false_positives: 71.5000 - loss: 0.3859
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8302 - false_negatives: 79.4286 - false_positives: 89.4286 - loss: 0.3837 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8540 - false_negatives: 63.1429 - false_positives: 80.5714 - loss: 0.3801
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8322 - false_negatives: 87.7500 - false_positives: 99.3750 - loss: 0.3812 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8562 - false_negatives: 68.0000 - false_positives: 90.5000 - loss: 0.3758
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8336 - false_negatives: 94.6667 - false_positives: 111.3333 - loss: 0.3793 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8580 - false_negatives: 73.3333 - false_positives: 100.3333 - loss: 0.3723
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8346 - false_negatives: 103.3000 - false_positives: 122.1000 - loss: 0.3784 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8595 - false_negatives: 78.5000 - false_positives: 110.3000 - loss: 0.3692
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8356 - false_negatives: 111.2727 - false_positives: 133.0909 - loss: 0.3774 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8607 - false_negatives: 83.7273 - false_positives: 120.5455 - loss: 0.3668
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8366 - false_negatives: 119.5833 - false_positives: 143.5000 - loss: 0.3764 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8617 - false_negatives: 89.5833 - false_positives: 130.0833 - loss: 0.3646
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8375 - false_negatives: 126.7692 - false_positives: 155.0769 - loss: 0.3756 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8625 - false_negatives: 94.9231 - false_positives: 140.6923 - loss: 0.3630
``` - + ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8382 - false_negatives: 135.0000 - false_positives: 165.7857 - loss: 0.3748 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8630 - false_negatives: 101.4286 - false_positives: 150.6429 - loss: 0.3618
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8387 - false_negatives: 142.6667 - false_positives: 177.4667 - loss: 0.3741 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8636 - false_negatives: 108.0000 - false_positives: 160.3333 - loss: 0.3605
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8392 - false_negatives: 150.0625 - false_positives: 189.5000 - loss: 0.3735 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8640 - false_negatives: 114.1250 - false_positives: 170.6875 - loss: 0.3595
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8397 - false_negatives: 157.0588 - false_positives: 201.1765 - loss: 0.3728 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8643 - false_negatives: 120.8235 - false_positives: 180.4706 - loss: 0.3587
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8404 - false_negatives: 164.0556 - false_positives: 212.3333 - loss: 0.3719 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8646 - false_negatives: 127.2778 - false_positives: 190.7222 - loss: 0.3579
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8410 - false_negatives: 171.4737 - false_positives: 223.1053 - loss: 0.3710 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8648 - false_negatives: 134.4737 - false_positives: 200.5263 - loss: 0.3572
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8415 - false_negatives: 178.4000 - false_positives: 234.2500 - loss: 0.3702 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8650 - false_negatives: 141.1000 - false_positives: 210.9500 - loss: 0.3565
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8422 - false_negatives: 185.0952 - false_positives: 245.0000 - loss: 0.3693 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8651 - false_negatives: 147.7619 - false_positives: 221.4286 - loss: 0.3558
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8428 - false_negatives: 191.8182 - false_positives: 255.7273 - loss: 0.3684 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8652 - false_negatives: 154.5000 - false_positives: 231.9545 - loss: 0.3552
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8434 - false_negatives: 198.3913 - false_positives: 266.3913 - loss: 0.3675 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8653 - false_negatives: 161.0435 - false_positives: 242.4783 - loss: 0.3546
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8440 - false_negatives: 204.9167 - false_positives: 277.0000 - loss: 0.3667 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8654 - false_negatives: 167.4583 - false_positives: 252.8333 - loss: 0.3540
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8446 - false_negatives: 211.4400 - false_positives: 287.4400 - loss: 0.3659 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8656 - false_negatives: 173.8000 - false_positives: 263.2400 - loss: 0.3533
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8451 - false_negatives: 217.8846 - false_positives: 297.8077 - loss: 0.3651 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8657 - false_negatives: 180.3077 - false_positives: 273.3462 - loss: 0.3526
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8457 - false_negatives: 224.5185 - false_positives: 307.9630 - loss: 0.3643 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8658 - false_negatives: 186.6296 - false_positives: 283.8889 - loss: 0.3520
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8462 - false_negatives: 231.0000 - false_positives: 318.2143 - loss: 0.3634 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8659 - false_negatives: 193.1786 - false_positives: 294.0714 - loss: 0.3513
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8467 - false_negatives: 238.1724 - false_positives: 328.0000 - loss: 0.3627 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8661 - false_negatives: 199.4138 - false_positives: 304.2069 - loss: 0.3507
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8471 - false_negatives: 245.0333 - false_positives: 338.2333 - loss: 0.3620 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8662 - false_negatives: 205.5667 - false_positives: 314.5333 - loss: 0.3500
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8475 - false_negatives: 251.9032 - false_positives: 348.4839 - loss: 0.3614 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8663 - false_negatives: 211.8065 - false_positives: 324.7419 - loss: 0.3494
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8479 - false_negatives: 258.8750 - false_positives: 358.5938 - loss: 0.3607 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8664 - false_negatives: 218.2188 - false_positives: 335.0000 - loss: 0.3489
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8482 - false_negatives: 265.4849 - false_positives: 369.3030 - loss: 0.3603 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8665 - false_negatives: 224.5152 - false_positives: 345.3030 - loss: 0.3484
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8485 - false_negatives: 272.6765 - false_positives: 379.5588 - loss: 0.3598 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8667 - false_negatives: 230.8529 - false_positives: 355.2941 - loss: 0.3478
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8488 - false_negatives: 279.6286 - false_positives: 390.1714 - loss: 0.3594 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8668 - false_negatives: 236.9143 - false_positives: 365.4857 - loss: 0.3473
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8491 - false_negatives: 286.3611 - false_positives: 401.0278 - loss: 0.3591 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8669 - false_negatives: 243.5000 - false_positives: 375.2500 - loss: 0.3468
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8494 - false_negatives: 293.0811 - false_positives: 411.8378 - loss: 0.3587 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8670 - false_negatives: 249.7568 - false_positives: 385.7297 - loss: 0.3464
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8496 - false_negatives: 299.7368 - false_positives: 422.7368 - loss: 0.3583 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8670 - false_negatives: 256.0526 - false_positives: 396.2368 - loss: 0.3461
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8499 - false_negatives: 306.5385 - false_positives: 433.5898 - loss: 0.3579 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8671 - false_negatives: 262.3077 - false_positives: 406.7949 - loss: 0.3457
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8501 - false_negatives: 313.2250 - false_positives: 444.5000 - loss: 0.3576 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8671 - false_negatives: 268.5000 - false_positives: 417.3750 - loss: 0.3454
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8503 - false_negatives: 319.9268 - false_positives: 455.4634 - loss: 0.3573 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8672 - false_negatives: 274.5854 - false_positives: 428.0732 - loss: 0.3450
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8505 - false_negatives: 326.8571 - false_positives: 466.1429 - loss: 0.3569 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8672 - false_negatives: 281.0238 - false_positives: 438.4524 - loss: 0.3447
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8507 - false_negatives: 333.6046 - false_positives: 477.0465 - loss: 0.3566 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8672 - false_negatives: 287.3721 - false_positives: 449.0233 - loss: 0.3445
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8509 - false_negatives: 340.7727 - false_positives: 487.7500 - loss: 0.3564 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 293.7500 - false_positives: 459.7046 - loss: 0.3442
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8510 - false_negatives: 347.8222 - false_positives: 498.5111 - loss: 0.3561 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 300.4222 - false_positives: 470.2222 - loss: 0.3440
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8512 - false_negatives: 354.8261 - false_positives: 509.3478 - loss: 0.3558 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 307.0000 - false_positives: 480.7174 - loss: 0.3438
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8513 - false_negatives: 361.9787 - false_positives: 520.1702 - loss: 0.3556 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 313.5319 - false_positives: 491.3192 - loss: 0.3436
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8515 - false_negatives: 369.0833 - false_positives: 531.0417 - loss: 0.3554 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 320.2083 - false_positives: 501.9375 - loss: 0.3434
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8516 - false_negatives: 376.2857 - false_positives: 541.8367 - loss: 0.3552 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 326.7959 - false_positives: 512.6531 - loss: 0.3433
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8517 - false_negatives: 383.4600 - false_positives: 552.6600 - loss: 0.3550 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 333.7800 - false_positives: 523.1200 - loss: 0.3431
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8519 - false_negatives: 390.5490 - false_positives: 563.4117 - loss: 0.3547 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8672 - false_negatives: 340.5490 - false_positives: 534.0980 - loss: 0.3430
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8520 - false_negatives: 397.9231 - false_positives: 574.0577 - loss: 0.3545 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8671 - false_negatives: 347.8077 - false_positives: 544.8269 - loss: 0.3429
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8521 - false_negatives: 405.3207 - false_positives: 584.7736 - loss: 0.3543 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8671 - false_negatives: 354.9811 - false_positives: 555.6981 - loss: 0.3429
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8522 - false_negatives: 412.9445 - false_positives: 595.4259 - loss: 0.3541 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8670 - false_negatives: 362.2222 - false_positives: 566.4074 - loss: 0.3428
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8523 - false_negatives: 420.4546 - false_positives: 606.2545 - loss: 0.3540 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8670 - false_negatives: 369.4546 - false_positives: 577.3818 - loss: 0.3428
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8523 - false_negatives: 428.4821 - false_positives: 616.8036 - loss: 0.3538 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8669 - false_negatives: 376.8393 - false_positives: 588.3214 - loss: 0.3428
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8524 - false_negatives: 436.2807 - false_positives: 627.7018 - loss: 0.3537 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8668 - false_negatives: 384.2456 - false_positives: 599.2281 - loss: 0.3428
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8524 - false_negatives: 444.1552 - false_positives: 638.5000 - loss: 0.3536 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8667 - false_negatives: 391.8448 - false_positives: 610.0000 - loss: 0.3428
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8525 - false_negatives: 452.0847 - false_positives: 649.4576 - loss: 0.3535 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8666 - false_negatives: 399.4576 - false_positives: 620.8135 - loss: 0.3428
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8525 - false_negatives: 460.0833 - false_positives: 660.3000 - loss: 0.3535 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8665 - false_negatives: 407.0500 - false_positives: 631.5500 - loss: 0.3428
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 468.0000 - false_positives: 671.0820 - loss: 0.3534 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8665 - false_negatives: 414.8033 - false_positives: 642.1639 - loss: 0.3428
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 476.0484 - false_positives: 681.6935 - loss: 0.3533 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8664 - false_negatives: 422.5484 - false_positives: 652.6613 - loss: 0.3428
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 484.0952 - false_positives: 692.3969 - loss: 0.3532 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8663 - false_negatives: 430.2381 - false_positives: 663.2381 - loss: 0.3428
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 492.4062 - false_positives: 702.9844 - loss: 0.3531 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8663 - false_negatives: 438.0469 - false_positives: 673.7500 - loss: 0.3428
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 500.6461 - false_positives: 713.8154 - loss: 0.3531 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8662 - false_negatives: 445.8154 - false_positives: 684.3538 - loss: 0.3428
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 509.3030 - false_positives: 724.3485 - loss: 0.3531 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8661 - false_negatives: 453.6970 - false_positives: 694.9243 - loss: 0.3429
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 517.7910 - false_positives: 735.3433 - loss: 0.3531 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8660 - false_negatives: 461.7463 - false_positives: 705.4179 - loss: 0.3429
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 526.3970 - false_positives: 746.1617 - loss: 0.3531 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8659 - false_negatives: 469.6912 - false_positives: 716.1177 - loss: 0.3429
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 535.0000 - false_positives: 756.9855 - loss: 0.3531 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8659 - false_negatives: 477.6956 - false_positives: 726.6522 - loss: 0.3430
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 543.6143 - false_positives: 767.7714 - loss: 0.3531 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8658 - false_negatives: 485.7286 - false_positives: 737.1286 - loss: 0.3430
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 552.2112 - false_positives: 778.5634 - loss: 0.3531 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8657 - false_negatives: 493.7042 - false_positives: 747.6479 - loss: 0.3430
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 560.9167 - false_positives: 789.2500 - loss: 0.3532 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8656 - false_negatives: 501.9167 - false_positives: 758.0000 - loss: 0.3430
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 569.6301 - false_positives: 800.0411 - loss: 0.3532 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8655 - false_negatives: 509.9589 - false_positives: 768.6575 - loss: 0.3431
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 578.3919 - false_positives: 810.5946 - loss: 0.3532 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8655 - false_negatives: 518.2162 - false_positives: 779.1081 - loss: 0.3432
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 587.0267 - false_positives: 821.1600 - loss: 0.3532 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8654 - false_negatives: 526.3734 - false_positives: 789.7333 - loss: 0.3432
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 595.7763 - false_positives: 831.6053 - loss: 0.3532 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8653 - false_negatives: 534.6184 - false_positives: 800.2500 - loss: 0.3433
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 604.4675 - false_positives: 842.0000 - loss: 0.3532 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8652 - false_negatives: 542.9221 - false_positives: 810.6883 - loss: 0.3433
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 613.1923 - false_positives: 852.3205 - loss: 0.3532 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8651 - false_negatives: 551.1923 - false_positives: 821.1411 - loss: 0.3433
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 621.9114 - false_positives: 862.6329 - loss: 0.3532 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8651 - false_negatives: 559.5823 - false_positives: 831.4810 - loss: 0.3434
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8526 - false_negatives: 630.8250 - false_positives: 872.7625 - loss: 0.3532 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8650 - false_negatives: 567.9250 - false_positives: 841.8750 - loss: 0.3434
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 639.6173 - false_positives: 882.9506 - loss: 0.3532 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8649 - false_negatives: 576.2839 - false_positives: 852.1975 - loss: 0.3434
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 648.5366 - false_positives: 893.0366 - loss: 0.3532 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8648 - false_negatives: 584.6951 - false_positives: 862.5000 - loss: 0.3435
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 657.3615 - false_positives: 903.0602 - loss: 0.3532 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8648 - false_negatives: 593.0723 - false_positives: 872.7108 - loss: 0.3435
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 666.1786 - false_positives: 912.9881 - loss: 0.3532 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8647 - false_negatives: 601.3690 - false_positives: 882.9048 - loss: 0.3435
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 675.0236 - false_positives: 922.8823 - loss: 0.3532 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8646 - false_negatives: 609.9647 - false_positives: 892.9647 - loss: 0.3435
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 683.9302 - false_positives: 932.6977 - loss: 0.3532 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8646 - false_negatives: 618.3953 - false_positives: 903.3488 - loss: 0.3436
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8527 - false_negatives: 692.8276 - false_positives: 942.5057 - loss: 0.3531 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8645 - false_negatives: 627.0115 - false_positives: 913.5632 - loss: 0.3436
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 701.8182 - false_positives: 952.1705 - loss: 0.3531 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8644 - false_negatives: 635.6477 - false_positives: 923.7614 - loss: 0.3437
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 710.6180 - false_positives: 962.1461 - loss: 0.3531 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8643 - false_negatives: 644.3259 - false_positives: 933.8876 - loss: 0.3437
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 719.7889 - false_positives: 971.9445 - loss: 0.3531 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8643 - false_negatives: 652.9556 - false_positives: 943.9000 - loss: 0.3438
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 728.9011 - false_positives: 981.7802 - loss: 0.3531 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8642 - false_negatives: 661.6703 - false_positives: 953.9121 - loss: 0.3438
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 737.9891 - false_positives: 991.5652 - loss: 0.3531 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8641 - false_negatives: 670.4565 - false_positives: 963.8261 - loss: 0.3438
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 747.0860 - false_positives: 1001.3226 - loss: 0.3531 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8641 - false_negatives: 679.2366 - false_positives: 973.7312 - loss: 0.3439
``` - + ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 756.1383 - false_positives: 1011.0106 - loss: 0.3531 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8640 - false_negatives: 687.9681 - false_positives: 983.5851 - loss: 0.3439
``` - + ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8528 - false_negatives: 765.1684 - false_positives: 1020.6842 - loss: 0.3531 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8640 - false_negatives: 696.7474 - false_positives: 993.3579 - loss: 0.3440
``` - + ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 774.1979 - false_positives: 1030.3541 - loss: 0.3531 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8639 - false_negatives: 705.5521 - false_positives: 1003.1250 - loss: 0.3440
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 783.2783 - false_positives: 1039.9381 - loss: 0.3531 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8639 - false_negatives: 714.4949 - false_positives: 1012.7938 - loss: 0.3440
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 792.1938 - false_positives: 1049.7755 - loss: 0.3531 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8638 - false_negatives: 723.4081 - false_positives: 1022.5102 - loss: 0.3441
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 801.4041 - false_positives: 1059.4445 - loss: 0.3531 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8638 - false_negatives: 732.4243 - false_positives: 1032.1414 - loss: 0.3441
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 810.5200 - false_positives: 1069.2200 - loss: 0.3531 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8637 - false_negatives: 741.3800 - false_positives: 1041.8199 - loss: 0.3442
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 819.6634 - false_positives: 1079.0396 - loss: 0.3531 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8636 - false_negatives: 750.3663 - false_positives: 1051.3663 - loss: 0.3442
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 828.8922 - false_positives: 1088.8431 - loss: 0.3531 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8636 - false_negatives: 759.2647 - false_positives: 1061.0197 - loss: 0.3442
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 838.1262 - false_positives: 1098.5923 - loss: 0.3531 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8635 - false_negatives: 768.3690 - false_positives: 1070.5049 - loss: 0.3443
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 847.2789 - false_positives: 1108.3365 - loss: 0.3532 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8635 - false_negatives: 777.3558 - false_positives: 1080.3557 - loss: 0.3443
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 856.4191 - false_positives: 1118.0190 - loss: 0.3532 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8634 - false_negatives: 786.6190 - false_positives: 1090.0571 - loss: 0.3444
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 865.4905 - false_positives: 1127.6698 - loss: 0.3532 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8634 - false_negatives: 795.8302 - false_positives: 1099.8019 - loss: 0.3445
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives: 874.6168 - false_positives: 1137.2056 - loss: 0.3532 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8633 - false_negatives: 805.0841 - false_positives: 1109.5046 - loss: 0.3445
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 883.6667 - false_positives: 1146.9630 - loss: 0.3532 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8632 - false_negatives: 814.3055 - false_positives: 1119.1389 - loss: 0.3446
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 893.0184 - false_positives: 1156.5688 - loss: 0.3532 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8632 - false_negatives: 823.4863 - false_positives: 1128.6790 - loss: 0.3446
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 902.2636 - false_positives: 1166.2909 - loss: 0.3532 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8631 - false_negatives: 832.7182 - false_positives: 1138.1000 - loss: 0.3447
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 911.5045 - false_positives: 1175.9640 - loss: 0.3532 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8631 - false_negatives: 841.8739 - false_positives: 1147.5586 - loss: 0.3447
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 920.7500 - false_positives: 1185.5714 - loss: 0.3532 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8630 - false_negatives: 851.1607 - false_positives: 1156.9286 - loss: 0.3448
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 930.0177 - false_positives: 1195.1858 - loss: 0.3533 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8630 - false_negatives: 860.3983 - false_positives: 1166.3805 - loss: 0.3448
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 939.2895 - false_positives: 1204.7894 - loss: 0.3533 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8629 - false_negatives: 869.7018 - false_positives: 1175.7018 - loss: 0.3448
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 948.5391 - false_positives: 1214.2783 - loss: 0.3533 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8629 - false_negatives: 878.9739 - false_positives: 1185.0348 - loss: 0.3449
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 957.7414 - false_positives: 1223.8190 - loss: 0.3533 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8629 - false_negatives: 888.2759 - false_positives: 1194.3879 - loss: 0.3449
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 967.0256 - false_positives: 1233.2821 - loss: 0.3533 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8628 - false_negatives: 897.5214 - false_positives: 1203.8291 - loss: 0.3450
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 976.2373 - false_positives: 1242.7881 - loss: 0.3533 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8628 - false_negatives: 906.8475 - false_positives: 1213.1610 - loss: 0.3450
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 985.4706 - false_positives: 1252.2185 - loss: 0.3533 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8627 - false_negatives: 916.1008 - false_positives: 1222.5126 - loss: 0.3451
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 994.6833 - false_positives: 1261.6750 - loss: 0.3533 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8627 - false_negatives: 925.4083 - false_positives: 1231.7833 - loss: 0.3451
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 1004.0000 - false_positives: 1271.0743 - loss: 0.3533 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8626 - false_negatives: 934.6694 - false_positives: 1241.2314 - loss: 0.3451
``` - + ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8530 - false_negatives: 1013.2295 - false_positives: 1280.4918 - loss: 0.3532 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8626 - false_negatives: 944.0328 - false_positives: 1250.5819 - loss: 0.3452
``` - + ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1022.5203 - false_positives: 1289.8456 - loss: 0.3532 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8626 - false_negatives: 953.3577 - false_positives: 1259.8862 - loss: 0.3452
``` - + ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1031.7661 - false_positives: 1299.2258 - loss: 0.3532 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8625 - false_negatives: 962.6210 - false_positives: 1269.2097 - loss: 0.3453
``` - + ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1041.0560 - false_positives: 1308.5520 - loss: 0.3532 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8625 - false_negatives: 972.0480 - false_positives: 1278.4640 - loss: 0.3453
``` - + ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1050.3096 - false_positives: 1317.9286 - loss: 0.3532 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8624 - false_negatives: 981.4048 - false_positives: 1287.9683 - loss: 0.3454
``` - + ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1059.5984 - false_positives: 1327.2205 - loss: 0.3532 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8624 - false_negatives: 990.8740 - false_positives: 1297.4094 - loss: 0.3454
``` - + ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1068.8047 - false_positives: 1336.6641 - loss: 0.3532 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8623 - false_negatives: 1000.3203 - false_positives: 1306.9141 - loss: 0.3455
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1077.9922 - false_positives: 1346.0233 - loss: 0.3532 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8623 - false_negatives: 1009.8295 - false_positives: 1316.3566 - loss: 0.3455
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1087.1538 - false_positives: 1355.4000 - loss: 0.3532 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8622 - false_negatives: 1019.3000 - false_positives: 1325.8231 - loss: 0.3456
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8531 - false_negatives: 1096.3130 - false_positives: 1364.7633 - loss: 0.3532 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8622 - false_negatives: 1028.7787 - false_positives: 1335.2443 - loss: 0.3456
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1105.4395 - false_positives: 1374.0909 - loss: 0.3531 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8621 - false_negatives: 1038.2122 - false_positives: 1344.6970 - loss: 0.3457
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1114.5864 - false_positives: 1383.4512 - loss: 0.3531 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8621 - false_negatives: 1047.6466 - false_positives: 1354.1204 - loss: 0.3457
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1123.6865 - false_positives: 1392.9478 - loss: 0.3531 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8621 - false_negatives: 1057.0597 - false_positives: 1363.5970 - loss: 0.3458
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1132.8962 - false_positives: 1402.3629 - loss: 0.3531 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8620 - false_negatives: 1066.4963 - false_positives: 1373.0297 - loss: 0.3458
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1142.0735 - false_positives: 1411.7721 - loss: 0.3531 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8620 - false_negatives: 1075.8529 - false_positives: 1382.6177 - loss: 0.3459
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1151.3795 - false_positives: 1421.0876 - loss: 0.3531 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8619 - false_negatives: 1085.3138 - false_positives: 1392.1387 - loss: 0.3459
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1160.5797 - false_positives: 1430.5435 - loss: 0.3531 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8619 - false_negatives: 1094.7319 - false_positives: 1401.7029 - loss: 0.3460
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1169.8993 - false_positives: 1439.9353 - loss: 0.3531 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8618 - false_negatives: 1104.2158 - false_positives: 1411.2518 - loss: 0.3460
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1179.1857 - false_positives: 1449.3785 - loss: 0.3531 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8618 - false_negatives: 1113.6714 - false_positives: 1420.8143 - loss: 0.3460
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1188.5461 - false_positives: 1458.7446 - loss: 0.3531 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8617 - false_negatives: 1123.1348 - false_positives: 1430.3405 - loss: 0.3461
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1197.8944 - false_positives: 1468.0986 - loss: 0.3530 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8617 - false_negatives: 1132.5211 - false_positives: 1439.8802 - loss: 0.3461
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 1207.2657 - false_positives: 1477.4755 - loss: 0.3530 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8617 - false_negatives: 1142.0210 - false_positives: 1449.3427 - loss: 0.3462
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1216.6250 - false_positives: 1486.8611 - loss: 0.3530 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8616 - false_negatives: 1151.4375 - false_positives: 1458.9514 - loss: 0.3462
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1225.9448 - false_positives: 1496.2759 - loss: 0.3530 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8616 - false_negatives: 1160.8690 - false_positives: 1468.5242 - loss: 0.3463
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1235.3219 - false_positives: 1505.6233 - loss: 0.3530 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8615 - false_negatives: 1170.3151 - false_positives: 1478.1028 - loss: 0.3463
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1244.6123 - false_positives: 1515.1973 - loss: 0.3530 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8615 - false_negatives: 1179.7279 - false_positives: 1487.7075 - loss: 0.3464
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1254.0270 - false_positives: 1524.7095 - loss: 0.3530 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8614 - false_negatives: 1189.1487 - false_positives: 1497.2838 - loss: 0.3464
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1263.4296 - false_positives: 1534.2214 - loss: 0.3530 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8614 - false_negatives: 1198.6443 - false_positives: 1506.8256 - loss: 0.3465
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1272.8667 - false_positives: 1543.7267 - loss: 0.3530 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8614 - false_negatives: 1208.0667 - false_positives: 1516.3933 - loss: 0.3465
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1282.2914 - false_positives: 1553.2318 - loss: 0.3530 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8613 - false_negatives: 1217.5099 - false_positives: 1525.8940 - loss: 0.3466
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1291.7302 - false_positives: 1562.7106 - loss: 0.3530 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8613 - false_negatives: 1226.8948 - false_positives: 1535.4606 - loss: 0.3466
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1301.1438 - false_positives: 1572.2222 - loss: 0.3530 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8613 - false_negatives: 1236.3071 - false_positives: 1544.9542 - loss: 0.3466
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1310.5065 - false_positives: 1581.7208 - loss: 0.3530 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8612 - false_negatives: 1245.6948 - false_positives: 1554.5454 - loss: 0.3467
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1319.9161 - false_positives: 1591.1548 - loss: 0.3530 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8612 - false_negatives: 1255.1033 - false_positives: 1564.0903 - loss: 0.3467
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8533 - false_negatives: 1329.3077 - false_positives: 1600.6154 - loss: 0.3530 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8611 - false_negatives: 1264.5256 - false_positives: 1573.5962 - loss: 0.3468
``` -Epoch 5: val_loss improved from 0.37839 to 0.33996, saving model to FullModelCheckpoint.keras +Epoch 5: val_loss did not improve from 0.36235  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8533 - false_negatives: 1347.8354 - false_positives: 1619.2025 - loss: 0.3530 - val_binary_accuracy: 0.8548 - val_false_negatives: 238.0000 - val_false_positives: 488.0000 - val_loss: 0.3400 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 75ms/step - binary_accuracy: 0.8611 - false_negatives: 1283.0632 - false_positives: 1592.3228 - loss: 0.3468 - val_binary_accuracy: 0.8222 - val_false_negatives: 734.0000 - val_false_positives: 155.0000 - val_loss: 0.4081
@@ -5940,1102 +5928,1102 @@ Epoch 6/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 91ms/step - binary_accuracy: 0.8633 - false_negatives: 17.0000 - false_positives: 18.0000 - loss: 0.3310 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.8047 - false_negatives: 44.0000 - false_positives: 6.0000 - loss: 0.4729
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8545 - false_negatives: 27.0000 - false_positives: 30.0000 - loss: 0.3336 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 10s 70ms/step - binary_accuracy: 0.8164 - false_negatives: 44.5000 - false_positives: 24.5000 - loss: 0.4546
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8513 - false_negatives: 37.6667 - false_positives: 40.0000 - loss: 0.3398 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8277 - false_negatives: 48.3333 - false_positives: 36.0000 - loss: 0.4339
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8487 - false_negatives: 48.0000 - false_positives: 51.0000 - loss: 0.3439 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8344 - false_negatives: 54.0000 - false_positives: 46.5000 - loss: 0.4219
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8496 - false_negatives: 56.2000 - false_positives: 60.6000 - loss: 0.3423 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8394 - false_negatives: 58.8000 - false_positives: 57.6000 - loss: 0.4111
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8507 - false_negatives: 63.1667 - false_positives: 71.0000 - loss: 0.3413 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8440 - false_negatives: 63.6667 - false_positives: 67.3333 - loss: 0.4014
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8514 - false_negatives: 71.8571 - false_positives: 80.1429 - loss: 0.3425 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8473 - false_negatives: 69.5714 - false_positives: 76.7143 - loss: 0.3942
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8514 - false_negatives: 79.2500 - false_positives: 91.7500 - loss: 0.3438 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8498 - false_negatives: 74.8750 - false_positives: 87.1250 - loss: 0.3884
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8516 - false_negatives: 86.5556 - false_positives: 103.1111 - loss: 0.3445 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8517 - false_negatives: 81.1111 - false_positives: 97.0000 - loss: 0.3838
``` - + ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8521 - false_negatives: 93.9000 - false_positives: 113.5000 - loss: 0.3445 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8532 - false_negatives: 86.8000 - false_positives: 107.6000 - loss: 0.3800
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8525 - false_negatives: 100.3636 - false_positives: 124.8182 - loss: 0.3444 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8545 - false_negatives: 93.4545 - false_positives: 117.2727 - loss: 0.3769
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8532 - false_negatives: 106.9167 - false_positives: 135.1667 - loss: 0.3440 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8554 - false_negatives: 99.5833 - false_positives: 127.9167 - loss: 0.3745
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8538 - false_negatives: 112.9231 - false_positives: 146.0000 - loss: 0.3436 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8562 - false_negatives: 105.8462 - false_positives: 138.6154 - loss: 0.3724
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8545 - false_negatives: 119.6429 - false_positives: 155.8571 - loss: 0.3431 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8570 - false_negatives: 112.4286 - false_positives: 148.5714 - loss: 0.3703
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8552 - false_negatives: 125.6667 - false_positives: 165.8667 - loss: 0.3425 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8577 - false_negatives: 119.0000 - false_positives: 158.5333 - loss: 0.3686
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8560 - false_negatives: 131.8750 - false_positives: 175.5000 - loss: 0.3418 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8584 - false_negatives: 125.6875 - false_positives: 168.1250 - loss: 0.3667
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8567 - false_negatives: 137.5882 - false_positives: 185.3529 - loss: 0.3408 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8591 - false_negatives: 132.2353 - false_positives: 177.2941 - loss: 0.3648
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8575 - false_negatives: 143.7222 - false_positives: 194.4444 - loss: 0.3399 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8598 - false_negatives: 138.6111 - false_positives: 186.4444 - loss: 0.3630
``` - + ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8581 - false_negatives: 149.4211 - false_positives: 204.5263 - loss: 0.3393 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8605 - false_negatives: 144.5263 - false_positives: 195.8421 - loss: 0.3612
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8586 - false_negatives: 155.7000 - false_positives: 213.9500 - loss: 0.3388 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8612 - false_negatives: 150.9500 - false_positives: 204.6500 - loss: 0.3594
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8592 - false_negatives: 161.7619 - false_positives: 223.5238 - loss: 0.3382 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8618 - false_negatives: 157.1905 - false_positives: 213.6667 - loss: 0.3577
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8597 - false_negatives: 168.0000 - false_positives: 233.0000 - loss: 0.3378 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8625 - false_negatives: 163.4091 - false_positives: 222.5000 - loss: 0.3561
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8601 - false_negatives: 174.2174 - false_positives: 242.6087 - loss: 0.3373 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8630 - false_negatives: 169.3913 - false_positives: 231.5652 - loss: 0.3546
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8605 - false_negatives: 180.7083 - false_positives: 252.3333 - loss: 0.3370 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8636 - false_negatives: 175.5833 - false_positives: 240.5417 - loss: 0.3532
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8609 - false_negatives: 187.1600 - false_positives: 261.8800 - loss: 0.3366 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8641 - false_negatives: 181.5600 - false_positives: 249.3200 - loss: 0.3518
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8613 - false_negatives: 193.5385 - false_positives: 271.0769 - loss: 0.3362 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8647 - false_negatives: 187.3846 - false_positives: 257.8846 - loss: 0.3503
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8617 - false_negatives: 199.6296 - false_positives: 280.4815 - loss: 0.3358 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8652 - false_negatives: 193.1111 - false_positives: 266.4445 - loss: 0.3490
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8621 - false_negatives: 205.7500 - false_positives: 289.7143 - loss: 0.3353 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8658 - false_negatives: 198.7500 - false_positives: 275.2143 - loss: 0.3478
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8626 - false_negatives: 211.4483 - false_positives: 298.7931 - loss: 0.3347 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8663 - false_negatives: 204.2069 - false_positives: 283.8965 - loss: 0.3465
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8630 - false_negatives: 217.0000 - false_positives: 307.9333 - loss: 0.3342 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8668 - false_negatives: 209.4000 - false_positives: 292.5333 - loss: 0.3453
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8634 - false_negatives: 222.7419 - false_positives: 316.9677 - loss: 0.3336 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8673 - false_negatives: 214.8065 - false_positives: 300.9032 - loss: 0.3441
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8638 - false_negatives: 228.2812 - false_positives: 326.4062 - loss: 0.3330 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8678 - false_negatives: 220.0000 - false_positives: 309.7500 - loss: 0.3430
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8642 - false_negatives: 234.2727 - false_positives: 335.4546 - loss: 0.3326 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8683 - false_negatives: 225.4545 - false_positives: 318.1515 - loss: 0.3420
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8645 - false_negatives: 240.0000 - false_positives: 344.9118 - loss: 0.3322 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8687 - false_negatives: 230.6765 - false_positives: 326.6765 - loss: 0.3410
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8648 - false_negatives: 246.0286 - false_positives: 354.0857 - loss: 0.3318 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8691 - false_negatives: 236.3428 - false_positives: 335.2857 - loss: 0.3401
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8651 - false_negatives: 251.8333 - false_positives: 363.3889 - loss: 0.3314 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8694 - false_negatives: 241.7222 - false_positives: 344.3333 - loss: 0.3393
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8654 - false_negatives: 257.5135 - false_positives: 372.7567 - loss: 0.3310 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8698 - false_negatives: 247.3243 - false_positives: 353.1622 - loss: 0.3385
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8657 - false_negatives: 263.3947 - false_positives: 382.0000 - loss: 0.3306 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8701 - false_negatives: 252.7368 - false_positives: 362.1579 - loss: 0.3377
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8660 - false_negatives: 269.2564 - false_positives: 391.4359 - loss: 0.3302 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8704 - false_negatives: 258.2051 - false_positives: 370.9744 - loss: 0.3369
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8662 - false_negatives: 275.5250 - false_positives: 400.6500 - loss: 0.3300 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8707 - false_negatives: 263.5250 - false_positives: 379.9000 - loss: 0.3362
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8664 - false_negatives: 281.4878 - false_positives: 410.6097 - loss: 0.3298 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8710 - false_negatives: 269.0732 - false_positives: 388.5854 - loss: 0.3355
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8665 - false_negatives: 287.6905 - false_positives: 420.3333 - loss: 0.3296 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 274.5000 - false_positives: 397.6429 - loss: 0.3349
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8667 - false_negatives: 293.8837 - false_positives: 430.0000 - loss: 0.3294 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8715 - false_negatives: 280.2093 - false_positives: 406.6279 - loss: 0.3343
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8668 - false_negatives: 299.9546 - false_positives: 439.8182 - loss: 0.3293 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8718 - false_negatives: 285.9091 - false_positives: 415.6591 - loss: 0.3337
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 306.2667 - false_positives: 449.4222 - loss: 0.3291 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8719 - false_negatives: 292.1778 - false_positives: 424.5555 - loss: 0.3332
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8671 - false_negatives: 312.4783 - false_positives: 459.3261 - loss: 0.3290 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8721 - false_negatives: 298.1956 - false_positives: 434.0217 - loss: 0.3329
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8672 - false_negatives: 318.9575 - false_positives: 469.0851 - loss: 0.3289 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8722 - false_negatives: 304.4468 - false_positives: 443.3830 - loss: 0.3325
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8673 - false_negatives: 325.4375 - false_positives: 479.1667 - loss: 0.3288 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8723 - false_negatives: 310.6667 - false_positives: 452.7917 - loss: 0.3322
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8674 - false_negatives: 331.9184 - false_positives: 489.2449 - loss: 0.3288 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8725 - false_negatives: 316.8571 - false_positives: 462.2449 - loss: 0.3319
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 338.5200 - false_positives: 499.3000 - loss: 0.3287 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 323.1800 - false_positives: 471.5800 - loss: 0.3316
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 344.9804 - false_positives: 509.6078 - loss: 0.3286 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8727 - false_negatives: 329.5490 - false_positives: 480.9608 - loss: 0.3313
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 351.9423 - false_positives: 519.6154 - loss: 0.3286 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8728 - false_negatives: 336.0962 - false_positives: 490.2885 - loss: 0.3310
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 358.6604 - false_positives: 530.2264 - loss: 0.3287 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8728 - false_negatives: 342.5849 - false_positives: 499.8302 - loss: 0.3308
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 365.4074 - false_positives: 540.7593 - loss: 0.3287 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 349.5555 - false_positives: 509.2222 - loss: 0.3306
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 372.2182 - false_positives: 551.1454 - loss: 0.3287 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 356.3455 - false_positives: 518.8727 - loss: 0.3304
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 379.2321 - false_positives: 561.4643 - loss: 0.3288 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 363.1429 - false_positives: 528.4821 - loss: 0.3302
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 386.1228 - false_positives: 571.9825 - loss: 0.3288 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 370.1754 - false_positives: 537.9474 - loss: 0.3300
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 393.2586 - false_positives: 582.3448 - loss: 0.3289 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 377.0862 - false_positives: 547.6379 - loss: 0.3299
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 400.4407 - false_positives: 592.7119 - loss: 0.3289 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 384.3220 - false_positives: 557.1356 - loss: 0.3298
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 407.6000 - false_positives: 602.9500 - loss: 0.3290 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 391.4833 - false_positives: 566.7333 - loss: 0.3296
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 414.6885 - false_positives: 613.2295 - loss: 0.3290 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 398.6885 - false_positives: 576.2787 - loss: 0.3295
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 421.9193 - false_positives: 623.3710 - loss: 0.3290 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 405.9193 - false_positives: 585.7581 - loss: 0.3294
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 429.1905 - false_positives: 633.5555 - loss: 0.3291 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 413.0635 - false_positives: 595.2540 - loss: 0.3293
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 436.4688 - false_positives: 643.6562 - loss: 0.3291 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 420.2188 - false_positives: 604.7656 - loss: 0.3292
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 443.7846 - false_positives: 653.7077 - loss: 0.3291 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 427.4462 - false_positives: 614.1846 - loss: 0.3290
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8676 - false_negatives: 451.0606 - false_positives: 663.7424 - loss: 0.3292 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 434.7121 - false_positives: 623.4545 - loss: 0.3289
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 458.5373 - false_positives: 673.6269 - loss: 0.3292 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 441.8507 - false_positives: 632.7463 - loss: 0.3288
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 465.9853 - false_positives: 683.6030 - loss: 0.3292 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8731 - false_negatives: 449.3971 - false_positives: 641.8677 - loss: 0.3287
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 473.5507 - false_positives: 693.4058 - loss: 0.3293 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 456.7536 - false_positives: 651.6812 - loss: 0.3287
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 480.9429 - false_positives: 703.6714 - loss: 0.3293 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 464.2571 - false_positives: 661.3714 - loss: 0.3287
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 488.7183 - false_positives: 713.6761 - loss: 0.3294 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8730 - false_negatives: 471.7887 - false_positives: 671.0282 - loss: 0.3286
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8674 - false_negatives: 496.3750 - false_positives: 723.9028 - loss: 0.3295 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 479.4445 - false_positives: 680.6250 - loss: 0.3286
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8674 - false_negatives: 504.1233 - false_positives: 734.0274 - loss: 0.3295 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 487.0959 - false_positives: 690.1644 - loss: 0.3286
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8674 - false_negatives: 511.8919 - false_positives: 744.1351 - loss: 0.3296 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8729 - false_negatives: 494.8108 - false_positives: 699.6622 - loss: 0.3286
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8673 - false_negatives: 519.6800 - false_positives: 754.2267 - loss: 0.3297 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8728 - false_negatives: 502.5733 - false_positives: 709.2400 - loss: 0.3286
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8673 - false_negatives: 527.5658 - false_positives: 764.2368 - loss: 0.3297 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8728 - false_negatives: 510.3553 - false_positives: 718.7368 - loss: 0.3286
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8673 - false_negatives: 535.5974 - false_positives: 774.0909 - loss: 0.3298 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8728 - false_negatives: 518.2208 - false_positives: 728.1688 - loss: 0.3287
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8672 - false_negatives: 543.5897 - false_positives: 784.0385 - loss: 0.3299 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8727 - false_negatives: 526.1411 - false_positives: 737.5897 - loss: 0.3287
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8672 - false_negatives: 551.6835 - false_positives: 793.8481 - loss: 0.3299 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8727 - false_negatives: 533.9874 - false_positives: 747.0000 - loss: 0.3287
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8672 - false_negatives: 559.7125 - false_positives: 803.6250 - loss: 0.3300 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8727 - false_negatives: 541.8375 - false_positives: 756.3250 - loss: 0.3287
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8671 - false_negatives: 567.7531 - false_positives: 813.4074 - loss: 0.3301 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 549.6296 - false_positives: 765.5679 - loss: 0.3287
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8671 - false_negatives: 575.9146 - false_positives: 823.0366 - loss: 0.3301 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 557.4146 - false_positives: 774.6829 - loss: 0.3287
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8671 - false_negatives: 584.0120 - false_positives: 832.6385 - loss: 0.3301 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 565.1687 - false_positives: 783.8795 - loss: 0.3286
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 592.1548 - false_positives: 842.2500 - loss: 0.3302 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 573.1548 - false_positives: 792.9167 - loss: 0.3286
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 600.3294 - false_positives: 851.8470 - loss: 0.3302 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 580.9764 - false_positives: 802.2823 - loss: 0.3286
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 608.5465 - false_positives: 861.3605 - loss: 0.3303 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8725 - false_negatives: 589.0233 - false_positives: 811.4883 - loss: 0.3287
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 616.6667 - false_positives: 870.8965 - loss: 0.3303 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8725 - false_negatives: 597.0920 - false_positives: 820.6896 - loss: 0.3287
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8670 - false_negatives: 624.8636 - false_positives: 880.3523 - loss: 0.3304 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8725 - false_negatives: 605.1818 - false_positives: 829.8295 - loss: 0.3287
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8669 - false_negatives: 633.0112 - false_positives: 889.8539 - loss: 0.3304 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8724 - false_negatives: 613.3371 - false_positives: 839.1011 - loss: 0.3287
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8669 - false_negatives: 641.2667 - false_positives: 899.2889 - loss: 0.3304 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8724 - false_negatives: 621.5667 - false_positives: 848.2444 - loss: 0.3288
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8669 - false_negatives: 649.4945 - false_positives: 908.8351 - loss: 0.3305 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8723 - false_negatives: 629.8022 - false_positives: 857.4286 - loss: 0.3288
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8669 - false_negatives: 657.7717 - false_positives: 918.3152 - loss: 0.3305 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8723 - false_negatives: 638.0435 - false_positives: 866.6087 - loss: 0.3288
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8668 - false_negatives: 666.0000 - false_positives: 927.8710 - loss: 0.3305 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8723 - false_negatives: 646.2688 - false_positives: 875.7742 - loss: 0.3289
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8668 - false_negatives: 674.3511 - false_positives: 937.3298 - loss: 0.3306 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8722 - false_negatives: 654.4787 - false_positives: 884.8298 - loss: 0.3289
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8668 - false_negatives: 682.6000 - false_positives: 946.9789 - loss: 0.3306 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8722 - false_negatives: 662.7263 - false_positives: 893.8210 - loss: 0.3289
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8667 - false_negatives: 690.8750 - false_positives: 956.5417 - loss: 0.3306 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8722 - false_negatives: 670.8646 - false_positives: 902.8646 - loss: 0.3289
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8667 - false_negatives: 699.1752 - false_positives: 965.9484 - loss: 0.3307 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8721 - false_negatives: 679.1650 - false_positives: 911.8248 - loss: 0.3289
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8667 - false_negatives: 707.3878 - false_positives: 975.4081 - loss: 0.3307 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8721 - false_negatives: 687.4490 - false_positives: 920.8265 - loss: 0.3290
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8667 - false_negatives: 715.8182 - false_positives: 984.7071 - loss: 0.3307 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8721 - false_negatives: 695.8081 - false_positives: 929.7071 - loss: 0.3290
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8666 - false_negatives: 724.1000 - false_positives: 994.3900 - loss: 0.3308 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8721 - false_negatives: 704.1000 - false_positives: 938.6000 - loss: 0.3290
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8666 - false_negatives: 732.6733 - false_positives: 1003.9406 - loss: 0.3308 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8720 - false_negatives: 712.3961 - false_positives: 947.4059 - loss: 0.3290
``` - + ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8666 - false_negatives: 741.1667 - false_positives: 1013.5686 - loss: 0.3309 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8720 - false_negatives: 720.6177 - false_positives: 956.2941 - loss: 0.3290
``` - + ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8665 - false_negatives: 749.7087 - false_positives: 1023.1068 - loss: 0.3309 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8720 - false_negatives: 729.0291 - false_positives: 965.0679 - loss: 0.3290
``` - + ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8665 - false_negatives: 758.2500 - false_positives: 1032.6057 - loss: 0.3310 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8720 - false_negatives: 737.3558 - false_positives: 974.0000 - loss: 0.3291
``` - + ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8665 - false_negatives: 766.8381 - false_positives: 1042.0095 - loss: 0.3310 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8719 - false_negatives: 745.7809 - false_positives: 982.8476 - loss: 0.3291
``` - + ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8664 - false_negatives: 775.3679 - false_positives: 1051.3962 - loss: 0.3310 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8719 - false_negatives: 754.1321 - false_positives: 991.6698 - loss: 0.3291
``` - + ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8664 - false_negatives: 783.9813 - false_positives: 1060.7196 - loss: 0.3311 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8719 - false_negatives: 762.5047 - false_positives: 1000.4486 - loss: 0.3291
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8664 - false_negatives: 792.5463 - false_positives: 1070.0648 - loss: 0.3311 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8719 - false_negatives: 770.8611 - false_positives: 1009.1852 - loss: 0.3291
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8663 - false_negatives: 801.1284 - false_positives: 1079.4496 - loss: 0.3311 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8718 - false_negatives: 779.1652 - false_positives: 1017.9633 - loss: 0.3292
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8663 - false_negatives: 809.6273 - false_positives: 1088.8000 - loss: 0.3312 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8718 - false_negatives: 787.5546 - false_positives: 1026.6455 - loss: 0.3292
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8663 - false_negatives: 818.1711 - false_positives: 1098.0720 - loss: 0.3312 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8718 - false_negatives: 795.9009 - false_positives: 1035.4054 - loss: 0.3292
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8663 - false_negatives: 826.7143 - false_positives: 1107.3661 - loss: 0.3312 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8718 - false_negatives: 804.2500 - false_positives: 1044.1517 - loss: 0.3292
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8662 - false_negatives: 835.4071 - false_positives: 1116.5929 - loss: 0.3313 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8717 - false_negatives: 812.6725 - false_positives: 1052.8230 - loss: 0.3292
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8662 - false_negatives: 844.0263 - false_positives: 1125.9650 - loss: 0.3313 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8717 - false_negatives: 821.0351 - false_positives: 1061.5878 - loss: 0.3292
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8662 - false_negatives: 852.7478 - false_positives: 1135.2435 - loss: 0.3313 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8717 - false_negatives: 829.4695 - false_positives: 1070.2957 - loss: 0.3292
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8661 - false_negatives: 861.5000 - false_positives: 1144.4482 - loss: 0.3313 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8717 - false_negatives: 837.8707 - false_positives: 1079.0087 - loss: 0.3293
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8661 - false_negatives: 870.2137 - false_positives: 1153.7008 - loss: 0.3314 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8717 - false_negatives: 846.2650 - false_positives: 1087.7522 - loss: 0.3293
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8661 - false_negatives: 878.9068 - false_positives: 1162.9323 - loss: 0.3314 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8716 - false_negatives: 854.6525 - false_positives: 1096.4830 - loss: 0.3293
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8661 - false_negatives: 887.6555 - false_positives: 1172.0420 - loss: 0.3314 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8716 - false_negatives: 862.9832 - false_positives: 1105.2689 - loss: 0.3293
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8660 - false_negatives: 896.3333 - false_positives: 1181.3500 - loss: 0.3314 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8716 - false_negatives: 871.4583 - false_positives: 1113.9917 - loss: 0.3293
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8660 - false_negatives: 905.3140 - false_positives: 1190.5206 - loss: 0.3315 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8716 - false_negatives: 879.8430 - false_positives: 1122.8678 - loss: 0.3293
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8660 - false_negatives: 914.1885 - false_positives: 1199.9836 - loss: 0.3315 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8715 - false_negatives: 888.3279 - false_positives: 1131.6721 - loss: 0.3293
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8659 - false_negatives: 923.1138 - false_positives: 1209.3903 - loss: 0.3316 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8715 - false_negatives: 896.7886 - false_positives: 1140.5284 - loss: 0.3293
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8659 - false_negatives: 931.9919 - false_positives: 1218.7822 - loss: 0.3316 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8715 - false_negatives: 905.3549 - false_positives: 1149.3387 - loss: 0.3293
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8659 - false_negatives: 940.8240 - false_positives: 1228.1281 - loss: 0.3317 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8715 - false_negatives: 913.8720 - false_positives: 1158.1520 - loss: 0.3294
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8658 - false_negatives: 949.6984 - false_positives: 1237.4127 - loss: 0.3317 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8714 - false_negatives: 922.3730 - false_positives: 1166.9445 - loss: 0.3294
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8658 - false_negatives: 958.5827 - false_positives: 1246.7086 - loss: 0.3318 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8714 - false_negatives: 930.9291 - false_positives: 1175.7323 - loss: 0.3294
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8658 - false_negatives: 967.5078 - false_positives: 1255.9297 - loss: 0.3318 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8714 - false_negatives: 939.5391 - false_positives: 1184.5000 - loss: 0.3294
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8657 - false_negatives: 976.3953 - false_positives: 1265.1628 - loss: 0.3318 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 948.1550 - false_positives: 1193.2791 - loss: 0.3294
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8657 - false_negatives: 985.4000 - false_positives: 1274.3000 - loss: 0.3319 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 956.8846 - false_positives: 1201.9615 - loss: 0.3295
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8657 - false_negatives: 994.3206 - false_positives: 1283.5420 - loss: 0.3319 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 965.5344 - false_positives: 1210.8320 - loss: 0.3295
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8656 - false_negatives: 1003.3485 - false_positives: 1292.6742 - loss: 0.3319 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 974.2955 - false_positives: 1219.6136 - loss: 0.3295
``` - + ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8656 - false_negatives: 1012.3534 - false_positives: 1301.8422 - loss: 0.3320 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8712 - false_negatives: 982.9850 - false_positives: 1228.3910 - loss: 0.3296
``` - + ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8656 - false_negatives: 1021.3881 - false_positives: 1310.9701 - loss: 0.3320 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8712 - false_negatives: 991.7612 - false_positives: 1237.1268 - loss: 0.3296
``` - + ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8656 - false_negatives: 1030.3629 - false_positives: 1320.1407 - loss: 0.3321 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8712 - false_negatives: 1000.4889 - false_positives: 1245.8445 - loss: 0.3296
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8655 - false_negatives: 1039.3823 - false_positives: 1329.2500 - loss: 0.3321 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8711 - false_negatives: 1009.2867 - false_positives: 1254.5809 - loss: 0.3296
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8655 - false_negatives: 1048.3430 - false_positives: 1338.4598 - loss: 0.3321 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8711 - false_negatives: 1018.0657 - false_positives: 1263.3065 - loss: 0.3297
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8655 - false_negatives: 1057.4783 - false_positives: 1347.5942 - loss: 0.3322 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8711 - false_negatives: 1026.8986 - false_positives: 1271.9928 - loss: 0.3297
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8654 - false_negatives: 1066.5540 - false_positives: 1356.8058 - loss: 0.3322 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives: 1035.6547 - false_positives: 1280.7195 - loss: 0.3297
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8654 - false_negatives: 1075.6857 - false_positives: 1365.9642 - loss: 0.3322 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives: 1044.4357 - false_positives: 1289.4357 - loss: 0.3297
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8654 - false_negatives: 1084.7943 - false_positives: 1375.1489 - loss: 0.3323 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives: 1053.2482 - false_positives: 1298.1135 - loss: 0.3298
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8653 - false_negatives: 1093.8802 - false_positives: 1384.2465 - loss: 0.3323 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives: 1061.9860 - false_positives: 1306.8873 - loss: 0.3298
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8653 - false_negatives: 1102.9790 - false_positives: 1393.2727 - loss: 0.3324 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8709 - false_negatives: 1070.7832 - false_positives: 1315.6224 - loss: 0.3298
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8653 - false_negatives: 1112.0070 - false_positives: 1402.2847 - loss: 0.3324 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8709 - false_negatives: 1079.5903 - false_positives: 1324.3125 - loss: 0.3298
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8653 - false_negatives: 1120.9724 - false_positives: 1411.2689 - loss: 0.3324 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8709 - false_negatives: 1088.3793 - false_positives: 1333.0068 - loss: 0.3299
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8652 - false_negatives: 1130.0068 - false_positives: 1420.2123 - loss: 0.3324 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8708 - false_negatives: 1097.3151 - false_positives: 1341.6233 - loss: 0.3299
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8652 - false_negatives: 1139.0068 - false_positives: 1429.2449 - loss: 0.3325 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8708 - false_negatives: 1106.1973 - false_positives: 1350.2380 - loss: 0.3299
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8652 - false_negatives: 1148.0676 - false_positives: 1438.2028 - loss: 0.3325 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8708 - false_negatives: 1115.0743 - false_positives: 1358.8582 - loss: 0.3299
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8652 - false_negatives: 1157.0873 - false_positives: 1447.3154 - loss: 0.3325 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8708 - false_negatives: 1123.9329 - false_positives: 1367.4631 - loss: 0.3300
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8651 - false_negatives: 1166.2800 - false_positives: 1456.3400 - loss: 0.3326 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8707 - false_negatives: 1132.8400 - false_positives: 1376.0400 - loss: 0.3300
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8651 - false_negatives: 1175.4172 - false_positives: 1465.4106 - loss: 0.3326 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8707 - false_negatives: 1141.7152 - false_positives: 1384.7218 - loss: 0.3300
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8651 - false_negatives: 1184.5198 - false_positives: 1474.4540 - loss: 0.3327 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8707 - false_negatives: 1150.7040 - false_positives: 1393.3486 - loss: 0.3300
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8651 - false_negatives: 1193.6274 - false_positives: 1483.5098 - loss: 0.3327 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8707 - false_negatives: 1159.6602 - false_positives: 1402.0392 - loss: 0.3300
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8650 - false_negatives: 1202.7662 - false_positives: 1492.5454 - loss: 0.3327 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8706 - false_negatives: 1168.7662 - false_positives: 1410.6428 - loss: 0.3301
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8650 - false_negatives: 1211.9032 - false_positives: 1501.5935 - loss: 0.3328 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8706 - false_negatives: 1177.8387 - false_positives: 1419.3097 - loss: 0.3301
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8650 - false_negatives: 1221.0000 - false_positives: 1510.6025 - loss: 0.3328 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8706 - false_negatives: 1186.9166 - false_positives: 1427.9487 - loss: 0.3301
``` -Epoch 6: val_loss improved from 0.33996 to 0.32718, saving model to FullModelCheckpoint.keras +Epoch 6: val_loss improved from 0.36235 to 0.35041, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8649 - false_negatives: 1238.9241 - false_positives: 1528.3038 - loss: 0.3329 - val_binary_accuracy: 0.8600 - val_false_negatives: 347.0000 - val_false_positives: 353.0000 - val_loss: 0.3272 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8705 - false_negatives: 1204.8038 - false_positives: 1444.9368 - loss: 0.3302 - val_binary_accuracy: 0.8412 - val_false_negatives: 569.0000 - val_false_positives: 225.0000 - val_loss: 0.3504
@@ -7045,1102 +7033,1102 @@ Epoch 7/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.8984 - false_negatives: 17.0000 - false_positives: 9.0000 - loss: 0.2931 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 91ms/step - binary_accuracy: 0.8594 - false_negatives: 30.0000 - false_positives: 6.0000 - loss: 0.3359
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8887 - false_negatives: 20.0000 - false_positives: 24.0000 - loss: 0.3210 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8594 - false_negatives: 33.0000 - false_positives: 21.0000 - loss: 0.3334
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8759 - false_negatives: 36.0000 - false_positives: 31.6667 - loss: 0.3439 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 71ms/step - binary_accuracy: 0.8637 - false_negatives: 39.3333 - false_positives: 29.3333 - loss: 0.3270
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8686 - false_negatives: 46.5000 - false_positives: 43.5000 - loss: 0.3551 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8648 - false_negatives: 45.7500 - false_positives: 39.5000 - loss: 0.3241
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8660 - false_negatives: 55.0000 - false_positives: 54.0000 - loss: 0.3575 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8669 - false_negatives: 51.6000 - false_positives: 48.6000 - loss: 0.3218
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8650 - false_negatives: 62.1667 - false_positives: 64.5000 - loss: 0.3574 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8692 - false_negatives: 56.8333 - false_positives: 57.1667 - loss: 0.3186
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8648 - false_negatives: 69.0000 - false_positives: 74.4286 - loss: 0.3564 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8713 - false_negatives: 62.4286 - false_positives: 65.0000 - loss: 0.3157
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8649 - false_negatives: 75.7500 - false_positives: 84.2500 - loss: 0.3557 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8726 - false_negatives: 67.3750 - false_positives: 74.5000 - loss: 0.3138
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8649 - false_negatives: 82.6667 - false_positives: 94.0000 - loss: 0.3545 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8735 - false_negatives: 74.0000 - false_positives: 82.5556 - loss: 0.3122
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8655 - false_negatives: 89.3000 - false_positives: 102.8000 - loss: 0.3524 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8744 - false_negatives: 80.0000 - false_positives: 90.9000 - loss: 0.3108
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8664 - false_negatives: 95.9091 - false_positives: 110.7273 - loss: 0.3499 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8753 - false_negatives: 86.0000 - false_positives: 99.1818 - loss: 0.3094
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8673 - false_negatives: 102.1667 - false_positives: 118.5833 - loss: 0.3471 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8759 - false_negatives: 91.7500 - false_positives: 108.0000 - loss: 0.3084
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8683 - false_negatives: 108.2308 - false_positives: 126.0769 - loss: 0.3441 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8764 - false_negatives: 98.3077 - false_positives: 116.3077 - loss: 0.3075
``` - + ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8692 - false_negatives: 114.1429 - false_positives: 133.9286 - loss: 0.3416 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8768 - false_negatives: 104.2857 - false_positives: 125.2143 - loss: 0.3068
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8699 - false_negatives: 121.4667 - false_positives: 141.1333 - loss: 0.3398 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8770 - false_negatives: 110.6667 - false_positives: 134.0000 - loss: 0.3063
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8702 - false_negatives: 127.9375 - false_positives: 150.1250 - loss: 0.3387 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8773 - false_negatives: 116.7500 - false_positives: 143.0000 - loss: 0.3058
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8705 - false_negatives: 134.7647 - false_positives: 159.0588 - loss: 0.3378 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8775 - false_negatives: 123.5882 - false_positives: 151.4118 - loss: 0.3053
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8707 - false_negatives: 141.1111 - false_positives: 168.4444 - loss: 0.3369 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8776 - false_negatives: 130.1111 - false_positives: 160.6111 - loss: 0.3051
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8710 - false_negatives: 147.3684 - false_positives: 177.7368 - loss: 0.3361 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8777 - false_negatives: 136.6842 - false_positives: 169.6842 - loss: 0.3048
```  ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8712 - false_negatives: 153.6000 - false_positives: 187.3000 - loss: 0.3352 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8778 - false_negatives: 142.9000 - false_positives: 178.6000 - loss: 0.3045
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8713 - false_negatives: 159.8095 - false_positives: 197.0476 - loss: 0.3345 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8780 - false_negatives: 148.9524 - false_positives: 187.8571 - loss: 0.3042
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8715 - false_negatives: 166.1818 - false_positives: 206.4091 - loss: 0.3338 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8780 - false_negatives: 155.3182 - false_positives: 196.9545 - loss: 0.3040
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8716 - false_negatives: 172.3044 - false_positives: 216.2174 - loss: 0.3332 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8781 - false_negatives: 161.7391 - false_positives: 206.2609 - loss: 0.3038
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 178.7083 - false_positives: 225.6667 - loss: 0.3327 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8781 - false_negatives: 167.8333 - false_positives: 215.5833 - loss: 0.3036
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8719 - false_negatives: 184.8800 - false_positives: 235.1200 - loss: 0.3321 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8783 - false_negatives: 173.8400 - false_positives: 224.5200 - loss: 0.3033
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8721 - false_negatives: 191.0385 - false_positives: 244.4231 - loss: 0.3315 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8785 - false_negatives: 179.6923 - false_positives: 233.3462 - loss: 0.3030
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8723 - false_negatives: 196.9630 - false_positives: 253.7037 - loss: 0.3308 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8786 - false_negatives: 185.5926 - false_positives: 242.0741 - loss: 0.3026
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8725 - false_negatives: 203.0357 - false_positives: 262.6786 - loss: 0.3302 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8788 - false_negatives: 191.1429 - false_positives: 250.8214 - loss: 0.3023
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8727 - false_negatives: 208.8276 - false_positives: 271.7586 - loss: 0.3295 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8791 - false_negatives: 196.6897 - false_positives: 259.4483 - loss: 0.3020
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8729 - false_negatives: 215.2333 - false_positives: 280.4667 - loss: 0.3289 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8793 - false_negatives: 202.2000 - false_positives: 267.8333 - loss: 0.3016
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8731 - false_negatives: 221.3226 - false_positives: 289.6129 - loss: 0.3283 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8795 - false_negatives: 207.4839 - false_positives: 276.4193 - loss: 0.3013
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8732 - false_negatives: 227.5000 - false_positives: 298.9062 - loss: 0.3277 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8797 - false_negatives: 213.1875 - false_positives: 284.9062 - loss: 0.3011
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8733 - false_negatives: 233.8485 - false_positives: 308.0909 - loss: 0.3272 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8799 - false_negatives: 218.7273 - false_positives: 293.8485 - loss: 0.3008
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8734 - false_negatives: 240.1471 - false_positives: 317.2941 - loss: 0.3267 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8800 - false_negatives: 224.6471 - false_positives: 302.5882 - loss: 0.3006
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8736 - false_negatives: 246.4286 - false_positives: 326.3714 - loss: 0.3262 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8801 - false_negatives: 230.5429 - false_positives: 311.4000 - loss: 0.3005
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 252.6944 - false_positives: 335.3333 - loss: 0.3257 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8802 - false_negatives: 236.3611 - false_positives: 320.2778 - loss: 0.3003
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8738 - false_negatives: 258.8649 - false_positives: 344.5946 - loss: 0.3252 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 242.1622 - false_positives: 329.4054 - loss: 0.3001
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8739 - false_negatives: 265.3947 - false_positives: 353.5263 - loss: 0.3248 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 248.3684 - false_positives: 338.2895 - loss: 0.3001
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 271.6667 - false_positives: 362.6923 - loss: 0.3244 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 254.3333 - false_positives: 347.3333 - loss: 0.3000
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 278.3000 - false_positives: 371.6750 - loss: 0.3241 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 260.2750 - false_positives: 356.3750 - loss: 0.2999
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 284.7317 - false_positives: 381.0976 - loss: 0.3238 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 266.5610 - false_positives: 365.3171 - loss: 0.2999
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 291.6667 - false_positives: 390.2619 - loss: 0.3235 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 272.6429 - false_positives: 374.6667 - loss: 0.2999
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 298.3954 - false_positives: 399.6279 - loss: 0.3233 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 278.6512 - false_positives: 384.0000 - loss: 0.2999
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 305.2954 - false_positives: 408.8864 - loss: 0.3231 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 284.9546 - false_positives: 393.2727 - loss: 0.3000
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 312.1333 - false_positives: 418.2889 - loss: 0.3229 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 291.0889 - false_positives: 402.7333 - loss: 0.3000
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 319.0000 - false_positives: 427.5217 - loss: 0.3227 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 297.2609 - false_positives: 412.1087 - loss: 0.3001
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 325.8511 - false_positives: 436.6383 - loss: 0.3225 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 303.4043 - false_positives: 421.6170 - loss: 0.3002
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 332.5833 - false_positives: 445.8125 - loss: 0.3223 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8805 - false_negatives: 309.8333 - false_positives: 430.8542 - loss: 0.3002
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 339.2653 - false_positives: 455.0204 - loss: 0.3221 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 316.1021 - false_positives: 440.2245 - loss: 0.3003
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 346.0800 - false_positives: 464.0800 - loss: 0.3219 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 322.5800 - false_positives: 449.4200 - loss: 0.3004
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 352.8235 - false_positives: 473.6471 - loss: 0.3218 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 329.0588 - false_positives: 458.6274 - loss: 0.3004
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 360.0192 - false_positives: 482.9808 - loss: 0.3217 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 335.5769 - false_positives: 467.8846 - loss: 0.3005
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 367.0000 - false_positives: 492.6604 - loss: 0.3216 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8804 - false_negatives: 342.2642 - false_positives: 477.1132 - loss: 0.3006
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8743 - false_negatives: 374.0185 - false_positives: 502.4259 - loss: 0.3215 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 348.8333 - false_positives: 486.2963 - loss: 0.3007
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 380.9636 - false_positives: 512.2000 - loss: 0.3215 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 355.5273 - false_positives: 495.4000 - loss: 0.3007
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 388.0357 - false_positives: 521.8214 - loss: 0.3214 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 362.2679 - false_positives: 504.5000 - loss: 0.3008
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 395.0000 - false_positives: 531.4211 - loss: 0.3213 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8803 - false_negatives: 368.9825 - false_positives: 513.6140 - loss: 0.3009
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8742 - false_negatives: 401.9655 - false_positives: 541.0000 - loss: 0.3213 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8802 - false_negatives: 375.8276 - false_positives: 522.6724 - loss: 0.3010
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 409.0508 - false_positives: 550.3898 - loss: 0.3212 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8802 - false_negatives: 382.5763 - false_positives: 531.9153 - loss: 0.3011
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 415.9500 - false_positives: 560.0000 - loss: 0.3211 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8801 - false_negatives: 389.6000 - false_positives: 540.9667 - loss: 0.3012
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 423.2295 - false_positives: 569.3279 - loss: 0.3210 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8801 - false_negatives: 396.4918 - false_positives: 550.1639 - loss: 0.3013
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 430.3710 - false_positives: 578.8226 - loss: 0.3210 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8801 - false_negatives: 403.7419 - false_positives: 559.2258 - loss: 0.3014
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 437.5397 - false_positives: 588.1588 - loss: 0.3210 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8800 - false_negatives: 410.8571 - false_positives: 568.5238 - loss: 0.3016
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 444.6719 - false_positives: 597.4531 - loss: 0.3209 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8799 - false_negatives: 418.0156 - false_positives: 577.7031 - loss: 0.3017
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 451.8000 - false_positives: 606.5846 - loss: 0.3208 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8799 - false_negatives: 425.2000 - false_positives: 586.8461 - loss: 0.3019
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 458.9697 - false_positives: 615.6364 - loss: 0.3208 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8798 - false_negatives: 432.3030 - false_positives: 596.0606 - loss: 0.3020
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 466.1791 - false_positives: 624.6567 - loss: 0.3207 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8798 - false_negatives: 439.5373 - false_positives: 605.1940 - loss: 0.3021
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 473.2941 - false_positives: 633.7206 - loss: 0.3206 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8797 - false_negatives: 446.7059 - false_positives: 614.2941 - loss: 0.3023
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 480.3623 - false_positives: 642.7101 - loss: 0.3206 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8797 - false_negatives: 453.9420 - false_positives: 623.2174 - loss: 0.3024
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 487.3286 - false_positives: 651.7571 - loss: 0.3205 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8796 - false_negatives: 461.1571 - false_positives: 632.1714 - loss: 0.3025
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 494.9859 - false_positives: 660.5916 - loss: 0.3205 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8796 - false_negatives: 468.3662 - false_positives: 641.0704 - loss: 0.3026
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 502.4583 - false_positives: 669.9445 - loss: 0.3205 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8796 - false_negatives: 475.7083 - false_positives: 649.9167 - loss: 0.3027
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8740 - false_negatives: 509.9315 - false_positives: 679.2603 - loss: 0.3205 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8795 - false_negatives: 483.0822 - false_positives: 658.7534 - loss: 0.3028
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8739 - false_negatives: 517.4054 - false_positives: 688.5000 - loss: 0.3205 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8795 - false_negatives: 490.3513 - false_positives: 667.6486 - loss: 0.3029
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8739 - false_negatives: 524.8400 - false_positives: 697.7466 - loss: 0.3205 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8794 - false_negatives: 497.8267 - false_positives: 676.4000 - loss: 0.3030
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8739 - false_negatives: 532.4868 - false_positives: 706.8553 - loss: 0.3205 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8794 - false_negatives: 505.2237 - false_positives: 685.1447 - loss: 0.3031
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8739 - false_negatives: 540.1429 - false_positives: 716.1429 - loss: 0.3206 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8794 - false_negatives: 512.7532 - false_positives: 693.8571 - loss: 0.3032
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8738 - false_negatives: 547.8077 - false_positives: 725.3846 - loss: 0.3206 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8793 - false_negatives: 520.3077 - false_positives: 702.4872 - loss: 0.3033
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8738 - false_negatives: 555.4051 - false_positives: 734.5696 - loss: 0.3206 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8793 - false_negatives: 527.7468 - false_positives: 711.1519 - loss: 0.3034
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8738 - false_negatives: 563.0500 - false_positives: 743.7625 - loss: 0.3206 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8792 - false_negatives: 535.4375 - false_positives: 719.6875 - loss: 0.3035
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 570.7654 - false_positives: 752.8519 - loss: 0.3207 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8792 - false_negatives: 543.0123 - false_positives: 728.3087 - loss: 0.3036
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 578.4512 - false_positives: 761.9025 - loss: 0.3207 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8792 - false_negatives: 550.8415 - false_positives: 736.7683 - loss: 0.3037
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 586.1566 - false_positives: 770.9036 - loss: 0.3207 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8791 - false_negatives: 558.5542 - false_positives: 745.2651 - loss: 0.3038
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 593.8333 - false_positives: 779.8690 - loss: 0.3207 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8791 - false_negatives: 566.4286 - false_positives: 753.6667 - loss: 0.3038
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8736 - false_negatives: 601.6235 - false_positives: 788.7765 - loss: 0.3207 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8791 - false_negatives: 574.2000 - false_positives: 762.0588 - loss: 0.3039
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8736 - false_negatives: 609.4186 - false_positives: 797.7675 - loss: 0.3207 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8790 - false_negatives: 582.0930 - false_positives: 770.3488 - loss: 0.3040
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8736 - false_negatives: 617.3678 - false_positives: 806.6552 - loss: 0.3207 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8790 - false_negatives: 589.9425 - false_positives: 778.7126 - loss: 0.3041
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8735 - false_negatives: 625.2159 - false_positives: 815.7273 - loss: 0.3207 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8789 - false_negatives: 597.8864 - false_positives: 787.0114 - loss: 0.3042
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8735 - false_negatives: 633.3708 - false_positives: 824.6180 - loss: 0.3208 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8789 - false_negatives: 605.7303 - false_positives: 795.4269 - loss: 0.3042
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8735 - false_negatives: 641.4889 - false_positives: 833.5889 - loss: 0.3208 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8789 - false_negatives: 613.6556 - false_positives: 803.7444 - loss: 0.3043
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8734 - false_negatives: 649.6484 - false_positives: 842.4725 - loss: 0.3208 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8788 - false_negatives: 621.5604 - false_positives: 812.0110 - loss: 0.3044
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8734 - false_negatives: 657.8370 - false_positives: 851.2826 - loss: 0.3208 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8788 - false_negatives: 629.4239 - false_positives: 820.2500 - loss: 0.3045
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8734 - false_negatives: 665.9893 - false_positives: 860.0860 - loss: 0.3208 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8788 - false_negatives: 637.3549 - false_positives: 828.4409 - loss: 0.3045
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8733 - false_negatives: 674.1808 - false_positives: 868.8405 - loss: 0.3209 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8788 - false_negatives: 645.2341 - false_positives: 836.6064 - loss: 0.3046
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8733 - false_negatives: 682.2842 - false_positives: 877.5263 - loss: 0.3209 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8787 - false_negatives: 653.2105 - false_positives: 844.6526 - loss: 0.3047
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8733 - false_negatives: 690.6250 - false_positives: 886.0833 - loss: 0.3209 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8787 - false_negatives: 661.1146 - false_positives: 852.8958 - loss: 0.3047
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8732 - false_negatives: 698.8350 - false_positives: 894.9794 - loss: 0.3209 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8787 - false_negatives: 669.1650 - false_positives: 861.1237 - loss: 0.3048
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8732 - false_negatives: 707.3367 - false_positives: 903.7449 - loss: 0.3210 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8786 - false_negatives: 677.2347 - false_positives: 869.3571 - loss: 0.3049
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8732 - false_negatives: 715.7576 - false_positives: 912.4949 - loss: 0.3210 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8786 - false_negatives: 685.3232 - false_positives: 877.6465 - loss: 0.3049
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8731 - false_negatives: 724.2700 - false_positives: 921.1700 - loss: 0.3211 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8786 - false_negatives: 693.4800 - false_positives: 885.9200 - loss: 0.3050
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8731 - false_negatives: 732.8218 - false_positives: 929.8812 - loss: 0.3211 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8785 - false_negatives: 701.6238 - false_positives: 894.2178 - loss: 0.3051
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8730 - false_negatives: 741.3627 - false_positives: 938.7157 - loss: 0.3212 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8785 - false_negatives: 709.7451 - false_positives: 902.4510 - loss: 0.3051
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8730 - false_negatives: 749.8641 - false_positives: 947.5243 - loss: 0.3212 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8785 - false_negatives: 717.8544 - false_positives: 910.7087 - loss: 0.3052
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8729 - false_negatives: 758.3750 - false_positives: 956.2211 - loss: 0.3212 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8784 - false_negatives: 725.9423 - false_positives: 918.9039 - loss: 0.3052
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8729 - false_negatives: 766.8000 - false_positives: 964.9810 - loss: 0.3213 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8784 - false_negatives: 734.0095 - false_positives: 927.0476 - loss: 0.3053
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8729 - false_negatives: 775.4056 - false_positives: 973.6132 - loss: 0.3213 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8784 - false_negatives: 742.1132 - false_positives: 935.1981 - loss: 0.3053
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8728 - false_negatives: 783.8691 - false_positives: 982.4953 - loss: 0.3214 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8783 - false_negatives: 750.2804 - false_positives: 943.3271 - loss: 0.3054
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8728 - false_negatives: 792.4445 - false_positives: 991.2222 - loss: 0.3214 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8783 - false_negatives: 758.3055 - false_positives: 951.5278 - loss: 0.3054
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8728 - false_negatives: 800.9816 - false_positives: 999.9358 - loss: 0.3214 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8783 - false_negatives: 766.4495 - false_positives: 959.6605 - loss: 0.3055
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8727 - false_negatives: 809.5818 - false_positives: 1008.5909 - loss: 0.3215 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8783 - false_negatives: 774.5728 - false_positives: 967.8364 - loss: 0.3055
``` - + ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8727 - false_negatives: 818.2343 - false_positives: 1017.2432 - loss: 0.3215 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8782 - false_negatives: 782.7657 - false_positives: 975.9820 - loss: 0.3056
``` - + ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8726 - false_negatives: 826.8125 - false_positives: 1025.9286 - loss: 0.3216 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8782 - false_negatives: 791.0446 - false_positives: 984.0714 - loss: 0.3056
``` - + ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8726 - false_negatives: 835.4160 - false_positives: 1034.5398 - loss: 0.3216 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8782 - false_negatives: 799.2744 - false_positives: 992.2655 - loss: 0.3057
``` - + ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8726 - false_negatives: 843.9561 - false_positives: 1043.3158 - loss: 0.3216 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8781 - false_negatives: 807.6316 - false_positives: 1000.4123 - loss: 0.3057
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8725 - false_negatives: 852.5652 - false_positives: 1052.0261 - loss: 0.3217 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8781 - false_negatives: 815.9130 - false_positives: 1008.6696 - loss: 0.3058
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8725 - false_negatives: 861.1896 - false_positives: 1060.7759 - loss: 0.3217 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8781 - false_negatives: 824.2155 - false_positives: 1016.8362 - loss: 0.3059
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8725 - false_negatives: 869.7350 - false_positives: 1069.4615 - loss: 0.3217 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8780 - false_negatives: 832.4530 - false_positives: 1025.0085 - loss: 0.3059
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8724 - false_negatives: 878.3051 - false_positives: 1078.1017 - loss: 0.3218 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8780 - false_negatives: 840.6949 - false_positives: 1033.1356 - loss: 0.3060
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8724 - false_negatives: 886.8403 - false_positives: 1086.7563 - loss: 0.3218 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8780 - false_negatives: 848.9496 - false_positives: 1041.2437 - loss: 0.3060
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8724 - false_negatives: 895.4083 - false_positives: 1095.3583 - loss: 0.3218 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8779 - false_negatives: 857.1500 - false_positives: 1049.4333 - loss: 0.3061
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8723 - false_negatives: 903.9339 - false_positives: 1104.0000 - loss: 0.3218 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8779 - false_negatives: 865.5207 - false_positives: 1057.5537 - loss: 0.3062
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8723 - false_negatives: 912.5410 - false_positives: 1112.5984 - loss: 0.3219 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8779 - false_negatives: 873.7869 - false_positives: 1065.8442 - loss: 0.3062
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8723 - false_negatives: 921.1301 - false_positives: 1121.2521 - loss: 0.3219 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8778 - false_negatives: 882.1301 - false_positives: 1074.0895 - loss: 0.3063
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8722 - false_negatives: 929.6855 - false_positives: 1129.9113 - loss: 0.3219 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8778 - false_negatives: 890.4677 - false_positives: 1082.3226 - loss: 0.3064
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8722 - false_negatives: 938.3200 - false_positives: 1138.5040 - loss: 0.3219 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8778 - false_negatives: 898.8960 - false_positives: 1090.5200 - loss: 0.3064
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8722 - false_negatives: 946.8571 - false_positives: 1147.1508 - loss: 0.3219 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8777 - false_negatives: 907.2778 - false_positives: 1098.7460 - loss: 0.3065
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8721 - false_negatives: 955.4488 - false_positives: 1155.7086 - loss: 0.3219 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8777 - false_negatives: 915.6851 - false_positives: 1106.9291 - loss: 0.3066
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8721 - false_negatives: 963.9688 - false_positives: 1164.4375 - loss: 0.3220 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8777 - false_negatives: 924.1016 - false_positives: 1115.1016 - loss: 0.3066
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8721 - false_negatives: 972.6512 - false_positives: 1173.0543 - loss: 0.3220 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8776 - false_negatives: 932.4728 - false_positives: 1123.2404 - loss: 0.3067
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8721 - false_negatives: 981.2538 - false_positives: 1181.7230 - loss: 0.3220 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8776 - false_negatives: 940.8461 - false_positives: 1131.3693 - loss: 0.3068
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8720 - false_negatives: 989.9084 - false_positives: 1190.3359 - loss: 0.3220 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8776 - false_negatives: 949.1832 - false_positives: 1139.5038 - loss: 0.3068
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8720 - false_negatives: 998.5076 - false_positives: 1198.9546 - loss: 0.3220 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8775 - false_negatives: 957.5076 - false_positives: 1147.6515 - loss: 0.3069
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8720 - false_negatives: 1007.1128 - false_positives: 1207.5112 - loss: 0.3220 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8775 - false_negatives: 965.8271 - false_positives: 1155.7142 - loss: 0.3069
``` - + ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8719 - false_negatives: 1015.7164 - false_positives: 1216.0896 - loss: 0.3220 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8775 - false_negatives: 974.0821 - false_positives: 1163.8582 - loss: 0.3070
``` - + ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8719 - false_negatives: 1024.3112 - false_positives: 1224.6519 - loss: 0.3221 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8775 - false_negatives: 982.5482 - false_positives: 1171.9186 - loss: 0.3070
``` - + ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8719 - false_negatives: 1032.8529 - false_positives: 1233.2206 - loss: 0.3221 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8774 - false_negatives: 990.9559 - false_positives: 1180.0956 - loss: 0.3071
``` - + ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8719 - false_negatives: 1041.4380 - false_positives: 1241.7957 - loss: 0.3221 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8774 - false_negatives: 999.3942 - false_positives: 1188.1970 - loss: 0.3072
``` - + ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8718 - false_negatives: 1050.0000 - false_positives: 1250.3695 - loss: 0.3221 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8774 - false_negatives: 1007.8116 - false_positives: 1196.2971 - loss: 0.3072
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8718 - false_negatives: 1058.6331 - false_positives: 1258.8561 - loss: 0.3221 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8774 - false_negatives: 1016.2374 - false_positives: 1204.4028 - loss: 0.3073
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8718 - false_negatives: 1067.2072 - false_positives: 1267.3500 - loss: 0.3221 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8773 - false_negatives: 1024.6714 - false_positives: 1212.4928 - loss: 0.3073
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8718 - false_negatives: 1075.7660 - false_positives: 1275.8511 - loss: 0.3221 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8773 - false_negatives: 1033.1418 - false_positives: 1220.5319 - loss: 0.3074
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 1084.3451 - false_positives: 1284.3522 - loss: 0.3221 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8773 - false_negatives: 1041.5493 - false_positives: 1228.6691 - loss: 0.3075
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 1092.9580 - false_positives: 1292.8462 - loss: 0.3221 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8772 - false_negatives: 1050.2238 - false_positives: 1236.7063 - loss: 0.3075
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 1101.6041 - false_positives: 1301.3195 - loss: 0.3221 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8772 - false_negatives: 1058.8264 - false_positives: 1244.8750 - loss: 0.3076
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 1110.2827 - false_positives: 1309.7931 - loss: 0.3221 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8772 - false_negatives: 1067.4344 - false_positives: 1253.0138 - loss: 0.3077
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 1118.9384 - false_positives: 1318.3082 - loss: 0.3221 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8771 - false_negatives: 1076.0068 - false_positives: 1261.1644 - loss: 0.3077
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8716 - false_negatives: 1127.5986 - false_positives: 1326.7891 - loss: 0.3221 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8771 - false_negatives: 1084.5986 - false_positives: 1269.3401 - loss: 0.3078
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8716 - false_negatives: 1136.2162 - false_positives: 1335.3041 - loss: 0.3221 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8771 - false_negatives: 1093.1689 - false_positives: 1277.5203 - loss: 0.3079
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8716 - false_negatives: 1145.0000 - false_positives: 1343.7920 - loss: 0.3221 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8770 - false_negatives: 1101.7517 - false_positives: 1285.6644 - loss: 0.3079
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8716 - false_negatives: 1153.7000 - false_positives: 1352.3933 - loss: 0.3221 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8770 - false_negatives: 1110.4000 - false_positives: 1293.7267 - loss: 0.3080
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8715 - false_negatives: 1162.5033 - false_positives: 1360.9205 - loss: 0.3221 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8770 - false_negatives: 1119.0133 - false_positives: 1301.8477 - loss: 0.3081
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8715 - false_negatives: 1171.2632 - false_positives: 1369.5658 - loss: 0.3221 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8770 - false_negatives: 1127.6908 - false_positives: 1309.9144 - loss: 0.3081
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8715 - false_negatives: 1180.0000 - false_positives: 1378.2026 - loss: 0.3221 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8769 - false_negatives: 1136.3268 - false_positives: 1318.1046 - loss: 0.3082
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8714 - false_negatives: 1188.7533 - false_positives: 1386.7533 - loss: 0.3221 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8769 - false_negatives: 1145.0585 - false_positives: 1326.2402 - loss: 0.3083
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8714 - false_negatives: 1197.5096 - false_positives: 1395.3032 - loss: 0.3221 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8769 - false_negatives: 1153.7612 - false_positives: 1334.3806 - loss: 0.3083
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8714 - false_negatives: 1206.3013 - false_positives: 1403.8525 - loss: 0.3221 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8768 - false_negatives: 1162.4423 - false_positives: 1342.4807 - loss: 0.3084
``` -Epoch 7: val_loss did not improve from 0.32718 +Epoch 7: val_loss improved from 0.35041 to 0.32680, saving model to FullModelCheckpoint.keras  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8713 - false_negatives: 1223.6139 - false_positives: 1420.6393 - loss: 0.3221 - val_binary_accuracy: 0.8594 - val_false_negatives: 238.0000 - val_false_positives: 465.0000 - val_loss: 0.3308 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8768 - false_negatives: 1179.5253 - false_positives: 1358.4114 - loss: 0.3085 - val_binary_accuracy: 0.8590 - val_false_negatives: 364.0000 - val_false_positives: 341.0000 - val_loss: 0.3268
@@ -8150,1102 +8138,1102 @@ Epoch 8/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.9180 - false_negatives: 13.0000 - false_positives: 8.0000 - loss: 0.2632 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 90ms/step - binary_accuracy: 0.8672 - false_negatives: 18.0000 - false_positives: 16.0000 - loss: 0.2905
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 75ms/step - binary_accuracy: 0.9092 - false_negatives: 19.0000 - false_positives: 17.0000 - loss: 0.2657 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8701 - false_negatives: 24.0000 - false_positives: 25.5000 - loss: 0.2952
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9069 - false_negatives: 26.3333 - false_positives: 22.6667 - loss: 0.2704 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8765 - false_negatives: 28.0000 - false_positives: 33.3333 - loss: 0.2899
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9060 - false_negatives: 31.5000 - false_positives: 30.0000 - loss: 0.2737 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8805 - false_negatives: 31.5000 - false_positives: 42.0000 - loss: 0.2852
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9043 - false_negatives: 39.8000 - false_positives: 35.6000 - loss: 0.2775 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8829 - false_negatives: 35.8000 - false_positives: 50.6000 - loss: 0.2832
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9024 - false_negatives: 45.5000 - false_positives: 44.8333 - loss: 0.2814 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8848 - false_negatives: 42.1667 - false_positives: 56.8333 - loss: 0.2820
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9009 - false_negatives: 51.4286 - false_positives: 53.5714 - loss: 0.2840 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8851 - false_negatives: 47.7143 - false_positives: 66.1429 - loss: 0.2825
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9005 - false_negatives: 57.1250 - false_positives: 61.0000 - loss: 0.2846 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8852 - false_negatives: 53.7500 - false_positives: 75.1250 - loss: 0.2833
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9000 - false_negatives: 62.2222 - false_positives: 69.3333 - loss: 0.2854 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8850 - false_negatives: 59.7778 - false_positives: 84.5556 - loss: 0.2840
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8994 - false_negatives: 68.3000 - false_positives: 77.2000 - loss: 0.2862 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8852 - false_negatives: 65.4000 - false_positives: 93.5000 - loss: 0.2843
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8989 - false_negatives: 73.6364 - false_positives: 86.0000 - loss: 0.2865 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8854 - false_negatives: 71.0909 - false_positives: 102.1818 - loss: 0.2849
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8984 - false_negatives: 79.4167 - false_positives: 94.1667 - loss: 0.2869 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8857 - false_negatives: 76.5833 - false_positives: 110.5833 - loss: 0.2853
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8981 - false_negatives: 84.8462 - false_positives: 102.3077 - loss: 0.2871 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8861 - false_negatives: 82.2308 - false_positives: 118.6154 - loss: 0.2858
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 90.0714 - false_positives: 110.2143 - loss: 0.2869 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8864 - false_negatives: 87.5714 - false_positives: 126.9286 - loss: 0.2859
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8979 - false_negatives: 95.4000 - false_positives: 118.2000 - loss: 0.2868 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8868 - false_negatives: 92.6000 - false_positives: 134.9333 - loss: 0.2858
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 100.6875 - false_positives: 126.0000 - loss: 0.2867 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8872 - false_negatives: 97.6875 - false_positives: 143.0000 - loss: 0.2857
``` - + ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.8978 - false_negatives: 105.9412 - false_positives: 133.5294 - loss: 0.2863 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8876 - false_negatives: 102.8824 - false_positives: 150.9412 - loss: 0.2856
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 111.2222 - false_positives: 141.1111 - loss: 0.2859 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8879 - false_negatives: 108.0556 - false_positives: 158.8333 - loss: 0.2854
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 116.4211 - false_positives: 148.7895 - loss: 0.2855 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8884 - false_negatives: 113.1579 - false_positives: 166.3684 - loss: 0.2852
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 121.8000 - false_positives: 156.2500 - loss: 0.2850 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8888 - false_negatives: 117.9500 - false_positives: 174.0500 - loss: 0.2849
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 126.8571 - false_positives: 164.1905 - loss: 0.2847 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8892 - false_negatives: 122.8095 - false_positives: 181.7143 - loss: 0.2846
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 132.5909 - false_positives: 171.7273 - loss: 0.2845 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8895 - false_negatives: 127.6818 - false_positives: 189.2273 - loss: 0.2843
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 137.9130 - false_positives: 179.3913 - loss: 0.2842 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8899 - false_negatives: 132.5217 - false_positives: 196.8696 - loss: 0.2840
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 143.2500 - false_positives: 187.1250 - loss: 0.2838 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8902 - false_negatives: 137.5000 - false_positives: 204.4167 - loss: 0.2838
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 148.6400 - false_positives: 194.9600 - loss: 0.2835 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8905 - false_negatives: 142.5200 - false_positives: 211.8400 - loss: 0.2836
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 153.8077 - false_positives: 203.1154 - loss: 0.2833 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8908 - false_negatives: 147.3077 - false_positives: 219.2308 - loss: 0.2832
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 159.3704 - false_positives: 210.9630 - loss: 0.2830 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8912 - false_negatives: 151.8889 - false_positives: 226.8148 - loss: 0.2830
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 164.7500 - false_positives: 218.8214 - loss: 0.2828 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8914 - false_negatives: 157.0357 - false_positives: 234.1071 - loss: 0.2828
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 170.1724 - false_positives: 226.7241 - loss: 0.2825 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8916 - false_negatives: 162.0345 - false_positives: 241.8621 - loss: 0.2826
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 175.6333 - false_positives: 234.5000 - loss: 0.2823 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 167.0333 - false_positives: 249.8000 - loss: 0.2825
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 181.0000 - false_positives: 242.3871 - loss: 0.2820 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 172.0645 - false_positives: 257.5484 - loss: 0.2823
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 186.6250 - false_positives: 250.1562 - loss: 0.2818 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8921 - false_negatives: 177.2500 - false_positives: 265.4375 - loss: 0.2822
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 192.1212 - false_positives: 257.8485 - loss: 0.2816 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8923 - false_negatives: 182.4545 - false_positives: 273.3030 - loss: 0.2821
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 197.6471 - false_positives: 265.5882 - loss: 0.2815 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8924 - false_negatives: 187.7647 - false_positives: 281.0588 - loss: 0.2819
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 203.1143 - false_positives: 273.3714 - loss: 0.2813 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8925 - false_negatives: 192.9429 - false_positives: 289.0000 - loss: 0.2818
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 208.7222 - false_positives: 280.9167 - loss: 0.2811 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8926 - false_negatives: 198.5278 - false_positives: 296.6945 - loss: 0.2817
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 214.2432 - false_positives: 288.7297 - loss: 0.2810 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8927 - false_negatives: 203.8919 - false_positives: 304.5946 - loss: 0.2816
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 219.8421 - false_positives: 296.3947 - loss: 0.2809 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8928 - false_negatives: 209.4737 - false_positives: 312.3947 - loss: 0.2816
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 225.4359 - false_positives: 304.1282 - loss: 0.2808 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 215.1026 - false_positives: 320.3333 - loss: 0.2816
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 231.0750 - false_positives: 311.9000 - loss: 0.2807 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8928 - false_negatives: 220.9000 - false_positives: 328.2250 - loss: 0.2816
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 236.7805 - false_positives: 319.6585 - loss: 0.2806 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8929 - false_negatives: 226.6341 - false_positives: 336.0244 - loss: 0.2816
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8971 - false_negatives: 242.4286 - false_positives: 327.5714 - loss: 0.2806 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8929 - false_negatives: 232.2857 - false_positives: 344.0238 - loss: 0.2816
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8971 - false_negatives: 248.5581 - false_positives: 335.2325 - loss: 0.2805 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 237.9767 - false_positives: 352.0465 - loss: 0.2816
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8970 - false_negatives: 254.4773 - false_positives: 343.2046 - loss: 0.2805 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 243.5682 - false_positives: 360.0909 - loss: 0.2816
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8969 - false_negatives: 260.6000 - false_positives: 351.0889 - loss: 0.2805 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 249.3333 - false_positives: 368.0222 - loss: 0.2816
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8968 - false_negatives: 266.5435 - false_positives: 359.0000 - loss: 0.2805 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 255.0652 - false_positives: 376.1087 - loss: 0.2816
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8968 - false_negatives: 272.5957 - false_positives: 366.7234 - loss: 0.2804 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 261.1277 - false_positives: 384.0425 - loss: 0.2816
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8967 - false_negatives: 278.5000 - false_positives: 374.7292 - loss: 0.2804 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 267.1042 - false_positives: 392.3542 - loss: 0.2817
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8967 - false_negatives: 284.6735 - false_positives: 382.4694 - loss: 0.2804 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8930 - false_negatives: 273.2245 - false_positives: 400.4694 - loss: 0.2817
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8966 - false_negatives: 290.6600 - false_positives: 390.5800 - loss: 0.2805 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8929 - false_negatives: 279.3200 - false_positives: 408.8400 - loss: 0.2818
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8965 - false_negatives: 296.7843 - false_positives: 398.5490 - loss: 0.2805 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8929 - false_negatives: 285.5882 - false_positives: 417.1765 - loss: 0.2819
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8964 - false_negatives: 302.9423 - false_positives: 406.3846 - loss: 0.2806 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8928 - false_negatives: 291.9231 - false_positives: 425.5577 - loss: 0.2820
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8964 - false_negatives: 309.0189 - false_positives: 414.4717 - loss: 0.2806 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8927 - false_negatives: 298.3396 - false_positives: 434.0189 - loss: 0.2821
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8963 - false_negatives: 315.3333 - false_positives: 422.4074 - loss: 0.2807 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8927 - false_negatives: 304.8518 - false_positives: 442.4074 - loss: 0.2822
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8962 - false_negatives: 321.5818 - false_positives: 430.6364 - loss: 0.2808 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8926 - false_negatives: 311.2909 - false_positives: 450.8182 - loss: 0.2823
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8961 - false_negatives: 327.9286 - false_positives: 438.7679 - loss: 0.2808 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8925 - false_negatives: 317.8214 - false_positives: 459.0357 - loss: 0.2824
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8960 - false_negatives: 334.2982 - false_positives: 446.9123 - loss: 0.2809 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8925 - false_negatives: 324.1930 - false_positives: 467.5789 - loss: 0.2824
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8959 - false_negatives: 340.8448 - false_positives: 454.9483 - loss: 0.2810 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8924 - false_negatives: 330.9828 - false_positives: 475.8965 - loss: 0.2826
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8958 - false_negatives: 347.3051 - false_positives: 463.2373 - loss: 0.2811 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8923 - false_negatives: 337.6271 - false_positives: 484.4068 - loss: 0.2827
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8957 - false_negatives: 354.0667 - false_positives: 471.3500 - loss: 0.2812 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8922 - false_negatives: 344.2500 - false_positives: 492.8000 - loss: 0.2828
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8956 - false_negatives: 360.7705 - false_positives: 479.6885 - loss: 0.2814 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8922 - false_negatives: 350.8033 - false_positives: 501.1803 - loss: 0.2829
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8954 - false_negatives: 367.5968 - false_positives: 487.9839 - loss: 0.2815 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8921 - false_negatives: 357.4516 - false_positives: 509.4355 - loss: 0.2830
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8953 - false_negatives: 374.3175 - false_positives: 496.3016 - loss: 0.2817 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8920 - false_negatives: 364.0952 - false_positives: 517.8412 - loss: 0.2831
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8952 - false_negatives: 381.0938 - false_positives: 504.6406 - loss: 0.2819 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8919 - false_negatives: 371.0312 - false_positives: 526.1094 - loss: 0.2832
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 387.8923 - false_positives: 513.0615 - loss: 0.2820 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8919 - false_negatives: 377.8154 - false_positives: 534.6154 - loss: 0.2833
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 394.7273 - false_positives: 521.4545 - loss: 0.2822 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8918 - false_negatives: 384.7879 - false_positives: 542.9545 - loss: 0.2834
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 401.6269 - false_positives: 529.8209 - loss: 0.2823 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8917 - false_negatives: 391.7015 - false_positives: 551.3731 - loss: 0.2835
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 408.5882 - false_positives: 538.2206 - loss: 0.2825 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8916 - false_negatives: 398.7500 - false_positives: 559.7941 - loss: 0.2837
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 415.5072 - false_positives: 546.6522 - loss: 0.2827 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8915 - false_negatives: 405.7391 - false_positives: 568.1304 - loss: 0.2838
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8945 - false_negatives: 422.4714 - false_positives: 555.0428 - loss: 0.2829 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8914 - false_negatives: 412.7571 - false_positives: 576.4000 - loss: 0.2839
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8944 - false_negatives: 429.4225 - false_positives: 563.4084 - loss: 0.2830 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8914 - false_negatives: 419.7465 - false_positives: 584.6057 - loss: 0.2840
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8943 - false_negatives: 436.3333 - false_positives: 571.6945 - loss: 0.2832 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8913 - false_negatives: 426.6945 - false_positives: 592.8611 - loss: 0.2841
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 443.2603 - false_positives: 579.9041 - loss: 0.2833 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8912 - false_negatives: 433.9726 - false_positives: 600.9452 - loss: 0.2842
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 450.2433 - false_positives: 588.0946 - loss: 0.2835 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8911 - false_negatives: 441.0811 - false_positives: 609.4459 - loss: 0.2843
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8940 - false_negatives: 457.2400 - false_positives: 596.2267 - loss: 0.2836 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8910 - false_negatives: 448.4400 - false_positives: 617.8000 - loss: 0.2844
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8939 - false_negatives: 464.2500 - false_positives: 604.3816 - loss: 0.2838 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8909 - false_negatives: 455.7500 - false_positives: 626.1184 - loss: 0.2846
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8938 - false_negatives: 471.4935 - false_positives: 612.4415 - loss: 0.2839 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8908 - false_negatives: 463.0649 - false_positives: 634.4026 - loss: 0.2847
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8937 - false_negatives: 478.6154 - false_positives: 620.7051 - loss: 0.2841 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8908 - false_negatives: 470.3590 - false_positives: 642.6667 - loss: 0.2848
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8936 - false_negatives: 485.8228 - false_positives: 628.9241 - loss: 0.2842 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8907 - false_negatives: 477.7089 - false_positives: 650.7722 - loss: 0.2849
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8935 - false_negatives: 493.1125 - false_positives: 637.0500 - loss: 0.2844 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8906 - false_negatives: 485.0250 - false_positives: 659.0000 - loss: 0.2850
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8934 - false_negatives: 500.3827 - false_positives: 645.1975 - loss: 0.2845 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8905 - false_negatives: 492.4938 - false_positives: 667.0864 - loss: 0.2852
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8933 - false_negatives: 507.7927 - false_positives: 653.1951 - loss: 0.2846 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8904 - false_negatives: 499.9024 - false_positives: 675.3536 - loss: 0.2853
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 515.1085 - false_positives: 661.3735 - loss: 0.2848 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8903 - false_negatives: 507.3253 - false_positives: 683.5422 - loss: 0.2854
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 522.6905 - false_positives: 669.3929 - loss: 0.2849 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8903 - false_negatives: 514.8214 - false_positives: 691.7024 - loss: 0.2855
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 530.2000 - false_positives: 677.4824 - loss: 0.2851 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8902 - false_negatives: 522.3530 - false_positives: 699.8823 - loss: 0.2857
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 537.6977 - false_positives: 685.5233 - loss: 0.2852 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8901 - false_negatives: 529.9651 - false_positives: 708.0233 - loss: 0.2858
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 545.2184 - false_positives: 693.4943 - loss: 0.2853 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8900 - false_negatives: 537.5632 - false_positives: 716.1379 - loss: 0.2859
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 552.7955 - false_positives: 701.4659 - loss: 0.2855 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8899 - false_negatives: 545.2045 - false_positives: 724.2159 - loss: 0.2860
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 560.3146 - false_positives: 709.5955 - loss: 0.2856 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8899 - false_negatives: 552.8539 - false_positives: 732.2697 - loss: 0.2862
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 568.1889 - false_positives: 717.5889 - loss: 0.2858 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8898 - false_negatives: 560.4889 - false_positives: 740.3333 - loss: 0.2863
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 575.9561 - false_positives: 725.7692 - loss: 0.2859 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8897 - false_negatives: 568.2967 - false_positives: 748.2637 - loss: 0.2864
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 583.7283 - false_positives: 733.9348 - loss: 0.2861 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8896 - false_negatives: 575.9783 - false_positives: 756.3804 - loss: 0.2865
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 591.5806 - false_positives: 742.0107 - loss: 0.2862 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8895 - false_negatives: 583.8279 - false_positives: 764.3763 - loss: 0.2867
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 599.4149 - false_positives: 750.2128 - loss: 0.2864 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8895 - false_negatives: 591.6702 - false_positives: 772.3192 - loss: 0.2868
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 607.3790 - false_positives: 758.2842 - loss: 0.2866 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8894 - false_negatives: 599.4631 - false_positives: 780.3263 - loss: 0.2869
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 615.2604 - false_positives: 766.4688 - loss: 0.2867 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8893 - false_negatives: 607.3542 - false_positives: 788.3125 - loss: 0.2871
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8917 - false_negatives: 623.1959 - false_positives: 774.5670 - loss: 0.2869 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8892 - false_negatives: 615.2371 - false_positives: 796.2165 - loss: 0.2872
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8916 - false_negatives: 631.1122 - false_positives: 782.6837 - loss: 0.2870 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8892 - false_negatives: 623.1224 - false_positives: 804.0510 - loss: 0.2873
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 639.1414 - false_positives: 790.7273 - loss: 0.2872 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8891 - false_negatives: 630.9091 - false_positives: 811.8889 - loss: 0.2874
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8914 - false_negatives: 647.1200 - false_positives: 798.9500 - loss: 0.2873 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8890 - false_negatives: 638.7400 - false_positives: 819.6700 - loss: 0.2875
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 655.2079 - false_positives: 807.0594 - loss: 0.2875 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8890 - false_negatives: 646.5049 - false_positives: 827.5148 - loss: 0.2876
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8912 - false_negatives: 663.2647 - false_positives: 815.2549 - loss: 0.2877 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8889 - false_negatives: 654.4314 - false_positives: 835.2745 - loss: 0.2877
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8911 - false_negatives: 671.3690 - false_positives: 823.3787 - loss: 0.2878 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8888 - false_negatives: 662.2427 - false_positives: 843.2913 - loss: 0.2879
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8910 - false_negatives: 679.4423 - false_positives: 831.5289 - loss: 0.2880 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8888 - false_negatives: 670.1923 - false_positives: 851.2211 - loss: 0.2880
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8909 - false_negatives: 687.5143 - false_positives: 839.5809 - loss: 0.2881 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8887 - false_negatives: 678.1334 - false_positives: 859.0952 - loss: 0.2881
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8908 - false_negatives: 695.5189 - false_positives: 847.6509 - loss: 0.2882 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8886 - false_negatives: 686.0377 - false_positives: 866.9528 - loss: 0.2882
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8907 - false_negatives: 703.5234 - false_positives: 855.6636 - loss: 0.2884 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8886 - false_negatives: 693.9159 - false_positives: 874.7664 - loss: 0.2883
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8906 - false_negatives: 711.4537 - false_positives: 863.6296 - loss: 0.2885 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8885 - false_negatives: 701.8704 - false_positives: 882.5648 - loss: 0.2884
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8905 - false_negatives: 719.4495 - false_positives: 871.5321 - loss: 0.2886 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8884 - false_negatives: 709.7982 - false_positives: 890.4220 - loss: 0.2886
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8904 - false_negatives: 727.3909 - false_positives: 879.5455 - loss: 0.2888 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8884 - false_negatives: 717.8091 - false_positives: 898.1818 - loss: 0.2887
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8904 - false_negatives: 735.5045 - false_positives: 887.4504 - loss: 0.2889 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8883 - false_negatives: 725.7657 - false_positives: 905.9730 - loss: 0.2888
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8903 - false_negatives: 743.5893 - false_positives: 895.3839 - loss: 0.2890 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8883 - false_negatives: 733.7054 - false_positives: 913.6875 - loss: 0.2889
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8902 - false_negatives: 751.6283 - false_positives: 903.3186 - loss: 0.2891 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8882 - false_negatives: 741.5840 - false_positives: 921.4248 - loss: 0.2890
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8901 - false_negatives: 759.7193 - false_positives: 911.1667 - loss: 0.2892 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8882 - false_negatives: 749.4737 - false_positives: 929.1404 - loss: 0.2891
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8900 - false_negatives: 767.7652 - false_positives: 919.0348 - loss: 0.2894 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8881 - false_negatives: 757.3130 - false_positives: 936.8435 - loss: 0.2892
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8900 - false_negatives: 775.8965 - false_positives: 926.7845 - loss: 0.2895 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8880 - false_negatives: 765.2328 - false_positives: 944.5345 - loss: 0.2893
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8899 - false_negatives: 784.0000 - false_positives: 934.6154 - loss: 0.2896 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8880 - false_negatives: 773.0598 - false_positives: 952.2991 - loss: 0.2894
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8898 - false_negatives: 792.0508 - false_positives: 942.4237 - loss: 0.2897 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8879 - false_negatives: 780.9492 - false_positives: 959.9915 - loss: 0.2895
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8897 - false_negatives: 800.1429 - false_positives: 950.1429 - loss: 0.2898 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8879 - false_negatives: 788.7731 - false_positives: 967.7647 - loss: 0.2896
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8897 - false_negatives: 808.2167 - false_positives: 957.9333 - loss: 0.2899 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8878 - false_negatives: 796.6000 - false_positives: 975.5167 - loss: 0.2897
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8896 - false_negatives: 816.3389 - false_positives: 965.6529 - loss: 0.2900 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8878 - false_negatives: 804.4215 - false_positives: 983.2314 - loss: 0.2898
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8895 - false_negatives: 824.4344 - false_positives: 973.3607 - loss: 0.2901 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8878 - false_negatives: 812.2377 - false_positives: 990.9672 - loss: 0.2899
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8895 - false_negatives: 832.5772 - false_positives: 981.0406 - loss: 0.2902 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8877 - false_negatives: 820.1382 - false_positives: 998.6829 - loss: 0.2900
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8894 - false_negatives: 840.7258 - false_positives: 988.8065 - loss: 0.2903 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8877 - false_negatives: 828.0242 - false_positives: 1006.3306 - loss: 0.2900
``` - + ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8893 - false_negatives: 848.8560 - false_positives: 996.6160 - loss: 0.2904 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives: 835.8480 - false_positives: 1014.0560 - loss: 0.2901
``` - + ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8892 - false_negatives: 857.0159 - false_positives: 1004.3571 - loss: 0.2905 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives: 843.7619 - false_positives: 1021.7143 - loss: 0.2902
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8892 - false_negatives: 865.1417 - false_positives: 1012.1024 - loss: 0.2905 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives: 851.6378 - false_positives: 1029.4331 - loss: 0.2903
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8891 - false_negatives: 873.3125 - false_positives: 1019.8125 - loss: 0.2906 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives: 859.5938 - false_positives: 1037.0781 - loss: 0.2904
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8890 - false_negatives: 881.4341 - false_positives: 1027.5426 - loss: 0.2907 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8874 - false_negatives: 867.4728 - false_positives: 1044.7596 - loss: 0.2905
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8890 - false_negatives: 889.6308 - false_positives: 1035.1615 - loss: 0.2908 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8874 - false_negatives: 875.3461 - false_positives: 1052.4077 - loss: 0.2906
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8889 - false_negatives: 897.7481 - false_positives: 1042.9465 - loss: 0.2909 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8873 - false_negatives: 883.1756 - false_positives: 1060.0916 - loss: 0.2907
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8889 - false_negatives: 905.8864 - false_positives: 1050.6666 - loss: 0.2910 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8873 - false_negatives: 891.0303 - false_positives: 1067.7500 - loss: 0.2908
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8888 - false_negatives: 914.0075 - false_positives: 1058.3308 - loss: 0.2911 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8873 - false_negatives: 898.8571 - false_positives: 1075.3834 - loss: 0.2908
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8887 - false_negatives: 922.1194 - false_positives: 1066.0149 - loss: 0.2911 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8872 - false_negatives: 906.6791 - false_positives: 1082.9701 - loss: 0.2909
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8887 - false_negatives: 930.2593 - false_positives: 1073.6593 - loss: 0.2912 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8872 - false_negatives: 914.4741 - false_positives: 1090.6000 - loss: 0.2910
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8886 - false_negatives: 938.3750 - false_positives: 1081.3456 - loss: 0.2913 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8872 - false_negatives: 922.2500 - false_positives: 1098.2133 - loss: 0.2911
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8886 - false_negatives: 946.5328 - false_positives: 1088.9708 - loss: 0.2914 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8871 - false_negatives: 930.0365 - false_positives: 1105.7883 - loss: 0.2911
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8885 - false_negatives: 954.6377 - false_positives: 1096.6884 - loss: 0.2914 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8871 - false_negatives: 937.7826 - false_positives: 1113.3914 - loss: 0.2912
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8884 - false_negatives: 962.8561 - false_positives: 1104.3597 - loss: 0.2915 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8870 - false_negatives: 945.5971 - false_positives: 1120.9856 - loss: 0.2913
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8884 - false_negatives: 971.0214 - false_positives: 1112.0643 - loss: 0.2916 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8870 - false_negatives: 953.4000 - false_positives: 1128.6000 - loss: 0.2914
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8883 - false_negatives: 979.2128 - false_positives: 1119.6951 - loss: 0.2917 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8870 - false_negatives: 961.2269 - false_positives: 1136.1560 - loss: 0.2914
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8883 - false_negatives: 987.3591 - false_positives: 1127.3029 - loss: 0.2917 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8869 - false_negatives: 969.0352 - false_positives: 1143.7324 - loss: 0.2915
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8882 - false_negatives: 995.4895 - false_positives: 1134.8601 - loss: 0.2918 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8869 - false_negatives: 976.8252 - false_positives: 1151.3286 - loss: 0.2916
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8882 - false_negatives: 1003.6042 - false_positives: 1142.3959 - loss: 0.2919 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8869 - false_negatives: 984.6597 - false_positives: 1158.9236 - loss: 0.2916
``` - + ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8881 - false_negatives: 1011.7379 - false_positives: 1149.9310 - loss: 0.2919 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8868 - false_negatives: 992.4552 - false_positives: 1166.6345 - loss: 0.2917
``` - + ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8881 - false_negatives: 1019.8630 - false_positives: 1157.4863 - loss: 0.2920 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8868 - false_negatives: 1000.3835 - false_positives: 1174.2671 - loss: 0.2918
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8880 - false_negatives: 1028.0476 - false_positives: 1165.0204 - loss: 0.2921 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8868 - false_negatives: 1008.2381 - false_positives: 1181.9865 - loss: 0.2918
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8880 - false_negatives: 1036.1959 - false_positives: 1172.6284 - loss: 0.2921 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8867 - false_negatives: 1016.0676 - false_positives: 1189.6487 - loss: 0.2919
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8879 - false_negatives: 1044.3423 - false_positives: 1180.2349 - loss: 0.2922 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8867 - false_negatives: 1023.9396 - false_positives: 1197.2617 - loss: 0.2920
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8879 - false_negatives: 1052.5200 - false_positives: 1187.8199 - loss: 0.2923 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8867 - false_negatives: 1031.8199 - false_positives: 1204.8800 - loss: 0.2920
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8878 - false_negatives: 1060.7218 - false_positives: 1195.4172 - loss: 0.2923 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8866 - false_negatives: 1039.7086 - false_positives: 1212.4702 - loss: 0.2921
```  ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8878 - false_negatives: 1068.9276 - false_positives: 1203.0658 - loss: 0.2924 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8866 - false_negatives: 1047.5856 - false_positives: 1220.0724 - loss: 0.2922
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8877 - false_negatives: 1077.1569 - false_positives: 1210.6929 - loss: 0.2925 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8866 - false_negatives: 1055.4902 - false_positives: 1227.6666 - loss: 0.2922
```  ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8877 - false_negatives: 1085.3701 - false_positives: 1218.3116 - loss: 0.2925 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8865 - false_negatives: 1063.4415 - false_positives: 1235.1884 - loss: 0.2923
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8876 - false_negatives: 1093.5807 - false_positives: 1225.9032 - loss: 0.2926 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8865 - false_negatives: 1071.3549 - false_positives: 1242.7612 - loss: 0.2924
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8876 - false_negatives: 1101.7756 - false_positives: 1233.4935 - loss: 0.2926 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8865 - false_negatives: 1079.3206 - false_positives: 1250.2693 - loss: 0.2924
``` -Epoch 8: val_loss did not improve from 0.32718 +Epoch 8: val_loss did not improve from 0.32680  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8875 - false_negatives: 1117.8925 - false_positives: 1248.4873 - loss: 0.2927 - val_binary_accuracy: 0.7710 - val_false_negatives: 1082.0000 - val_false_positives: 63.0000 - val_loss: 0.5049 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8864 - false_negatives: 1094.9873 - false_positives: 1265.0632 - loss: 0.2926 - val_binary_accuracy: 0.8460 - val_false_negatives: 548.0000 - val_false_positives: 222.0000 - val_loss: 0.3432
@@ -9255,1102 +9243,1102 @@ Epoch 9/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 94ms/step - binary_accuracy: 0.7266 - false_negatives: 66.0000 - false_positives: 4.0000 - loss: 0.5482 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 93ms/step - binary_accuracy: 0.8398 - false_negatives: 36.0000 - false_positives: 5.0000 - loss: 0.3585
```  ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.7568 - false_negatives: 67.5000 - false_positives: 22.0000 - loss: 0.5064 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8555 - false_negatives: 39.5000 - false_positives: 14.0000 - loss: 0.3325
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.7797 - false_negatives: 71.6667 - false_positives: 32.6667 - loss: 0.4753 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8628 - false_negatives: 46.3333 - false_positives: 20.6667 - loss: 0.3187
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.7950 - false_negatives: 76.5000 - false_positives: 42.5000 - loss: 0.4519 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8664 - false_negatives: 51.2500 - false_positives: 30.5000 - loss: 0.3118
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8055 - false_negatives: 81.8000 - false_positives: 52.4000 - loss: 0.4355 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8695 - false_negatives: 56.8000 - false_positives: 38.8000 - loss: 0.3067
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8135 - false_negatives: 87.5000 - false_positives: 61.8333 - loss: 0.4221 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8722 - false_negatives: 61.3333 - false_positives: 47.6667 - loss: 0.3025
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8205 - false_negatives: 92.7143 - false_positives: 70.5714 - loss: 0.4100 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 67.5714 - false_positives: 55.1429 - loss: 0.2998
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8265 - false_negatives: 97.1250 - false_positives: 79.3750 - loss: 0.3993 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8754 - false_negatives: 73.6250 - false_positives: 63.3750 - loss: 0.2982
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8315 - false_negatives: 102.6667 - false_positives: 87.1111 - loss: 0.3901 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8767 - false_negatives: 78.8889 - false_positives: 71.7778 - loss: 0.2964
``` - + ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8356 - false_negatives: 107.7000 - false_positives: 95.7000 - loss: 0.3826 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8778 - false_negatives: 84.7000 - false_positives: 79.6000 - loss: 0.2949
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8390 - false_negatives: 113.8182 - false_positives: 103.5455 - loss: 0.3765 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8787 - false_negatives: 90.0909 - false_positives: 88.0000 - loss: 0.2940
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8422 - false_negatives: 119.4167 - false_positives: 111.4167 - loss: 0.3708 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 95.5833 - false_positives: 95.9167 - loss: 0.2928
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8448 - false_negatives: 125.0000 - false_positives: 119.6154 - loss: 0.3659 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8805 - false_negatives: 101.0000 - false_positives: 103.6154 - loss: 0.2915
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8473 - false_negatives: 130.7143 - false_positives: 127.3571 - loss: 0.3613 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8812 - false_negatives: 106.5000 - false_positives: 111.5714 - loss: 0.2904
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8496 - false_negatives: 136.2000 - false_positives: 135.0000 - loss: 0.3570 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8820 - false_negatives: 111.5333 - false_positives: 119.3333 - loss: 0.2893
```  ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8517 - false_negatives: 141.7500 - false_positives: 142.3125 - loss: 0.3529 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8828 - false_negatives: 116.3750 - false_positives: 127.0000 - loss: 0.2883
```  ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8536 - false_negatives: 147.4706 - false_positives: 149.4118 - loss: 0.3494 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8835 - false_negatives: 121.1176 - false_positives: 134.7647 - loss: 0.2872
```  ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8554 - false_negatives: 152.7222 - false_positives: 156.8333 - loss: 0.3462 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8842 - false_negatives: 126.2222 - false_positives: 142.3889 - loss: 0.2864
```  ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8571 - false_negatives: 158.4737 - false_positives: 163.7368 - loss: 0.3432 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8848 - false_negatives: 131.1579 - false_positives: 149.9474 - loss: 0.2857
```  ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8585 - false_negatives: 164.0500 - false_positives: 171.2500 - loss: 0.3406 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8854 - false_negatives: 135.8500 - false_positives: 157.5000 - loss: 0.2850
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8599 - false_negatives: 169.8571 - false_positives: 178.5714 - loss: 0.3383 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8860 - false_negatives: 140.6667 - false_positives: 164.9524 - loss: 0.2843
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8611 - false_negatives: 175.4545 - false_positives: 186.1818 - loss: 0.3361 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8866 - false_negatives: 145.1364 - false_positives: 172.3182 - loss: 0.2835
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8621 - false_negatives: 181.1739 - false_positives: 193.9565 - loss: 0.3340 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8872 - false_negatives: 149.4783 - false_positives: 179.5217 - loss: 0.2827
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8632 - false_negatives: 186.7083 - false_positives: 201.7500 - loss: 0.3321 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8878 - false_negatives: 153.9167 - false_positives: 186.5000 - loss: 0.2819
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8642 - false_negatives: 192.2400 - false_positives: 209.2400 - loss: 0.3302 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8884 - false_negatives: 158.2000 - false_positives: 193.4800 - loss: 0.2811
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8651 - false_negatives: 197.6154 - false_positives: 216.8846 - loss: 0.3285 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8889 - false_negatives: 162.9615 - false_positives: 200.3077 - loss: 0.2804
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8660 - false_negatives: 202.8889 - false_positives: 224.7407 - loss: 0.3268 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8894 - false_negatives: 167.4444 - false_positives: 207.5926 - loss: 0.2798
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8668 - false_negatives: 208.7500 - false_positives: 232.2143 - loss: 0.3253 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8899 - false_negatives: 172.0000 - false_positives: 214.6786 - loss: 0.2792
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8675 - false_negatives: 214.3448 - false_positives: 240.0000 - loss: 0.3239 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8903 - false_negatives: 176.6207 - false_positives: 221.6552 - loss: 0.2785
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8682 - false_negatives: 219.8667 - false_positives: 247.8667 - loss: 0.3225 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8907 - false_negatives: 181.1000 - false_positives: 228.7333 - loss: 0.2779
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8689 - false_negatives: 225.3871 - false_positives: 255.5806 - loss: 0.3212 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8912 - false_negatives: 185.6774 - false_positives: 235.5484 - loss: 0.2773
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8696 - false_negatives: 230.7500 - false_positives: 263.5938 - loss: 0.3200 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 190.0938 - false_positives: 242.8438 - loss: 0.2768
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8702 - false_negatives: 236.2727 - false_positives: 271.3636 - loss: 0.3189 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 195.0303 - false_positives: 249.9394 - loss: 0.2763
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8707 - false_negatives: 241.7647 - false_positives: 279.2059 - loss: 0.3178 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 74ms/step - binary_accuracy: 0.8921 - false_negatives: 199.8824 - false_positives: 257.1471 - loss: 0.2759
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8713 - false_negatives: 247.2857 - false_positives: 287.1429 - loss: 0.3169 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8924 - false_negatives: 204.6857 - false_positives: 264.4857 - loss: 0.2756
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8717 - false_negatives: 252.9722 - false_positives: 295.1111 - loss: 0.3160 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8926 - false_negatives: 209.3611 - false_positives: 272.1111 - loss: 0.2752
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8722 - false_negatives: 258.6757 - false_positives: 303.2433 - loss: 0.3151 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8928 - false_negatives: 214.5946 - false_positives: 279.6216 - loss: 0.2750
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8726 - false_negatives: 264.5263 - false_positives: 311.2895 - loss: 0.3144 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 219.6579 - false_positives: 287.3947 - loss: 0.2748
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8730 - false_negatives: 270.1795 - false_positives: 319.7436 - loss: 0.3136 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 224.7436 - false_positives: 295.1538 - loss: 0.2746
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8733 - false_negatives: 276.0250 - false_positives: 327.9500 - loss: 0.3130 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8933 - false_negatives: 229.7000 - false_positives: 302.8500 - loss: 0.2743
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8737 - false_negatives: 281.6829 - false_positives: 336.0976 - loss: 0.3123 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8935 - false_negatives: 234.7073 - false_positives: 310.5610 - loss: 0.2741
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8741 - false_negatives: 287.3571 - false_positives: 344.1905 - loss: 0.3117 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8936 - false_negatives: 239.6905 - false_positives: 318.2857 - loss: 0.2739
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8744 - false_negatives: 293.0233 - false_positives: 352.3954 - loss: 0.3111 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8937 - false_negatives: 244.7442 - false_positives: 326.0930 - loss: 0.2738
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8747 - false_negatives: 298.9546 - false_positives: 360.3864 - loss: 0.3106 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8938 - false_negatives: 249.6818 - false_positives: 334.0227 - loss: 0.2736
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8750 - false_negatives: 304.6667 - false_positives: 368.6000 - loss: 0.3100 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8940 - false_negatives: 254.8889 - false_positives: 341.7333 - loss: 0.2735
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8753 - false_negatives: 310.4565 - false_positives: 376.6304 - loss: 0.3095 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8941 - false_negatives: 259.9783 - false_positives: 349.7391 - loss: 0.2733
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8756 - false_negatives: 316.1277 - false_positives: 384.7234 - loss: 0.3090 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8941 - false_negatives: 265.1277 - false_positives: 357.6170 - loss: 0.2732
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8759 - false_negatives: 322.0208 - false_positives: 392.7917 - loss: 0.3086 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8942 - false_negatives: 270.2083 - false_positives: 365.5208 - loss: 0.2731
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8761 - false_negatives: 327.7143 - false_positives: 401.2245 - loss: 0.3081 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8943 - false_negatives: 275.4286 - false_positives: 373.4490 - loss: 0.2730
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8763 - false_negatives: 333.9600 - false_positives: 409.4600 - loss: 0.3078 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8944 - false_negatives: 280.8400 - false_positives: 381.1800 - loss: 0.2729
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8765 - false_negatives: 340.0392 - false_positives: 417.9608 - loss: 0.3074 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8945 - false_negatives: 286.1569 - false_positives: 389.0588 - loss: 0.2728
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8767 - false_negatives: 346.2308 - false_positives: 426.4038 - loss: 0.3071 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8945 - false_negatives: 291.6731 - false_positives: 396.8077 - loss: 0.2728
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8769 - false_negatives: 352.3396 - false_positives: 434.8491 - loss: 0.3068 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8946 - false_negatives: 297.1698 - false_positives: 404.6415 - loss: 0.2728
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8771 - false_negatives: 358.4630 - false_positives: 443.2037 - loss: 0.3064 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8946 - false_negatives: 302.6296 - false_positives: 412.4259 - loss: 0.2727
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8772 - false_negatives: 364.5636 - false_positives: 451.5636 - loss: 0.3061 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 308.1636 - false_positives: 420.2182 - loss: 0.2727
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8774 - false_negatives: 370.6964 - false_positives: 459.8750 - loss: 0.3058 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 313.8036 - false_positives: 428.0893 - loss: 0.2727
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8776 - false_negatives: 376.8246 - false_positives: 468.2105 - loss: 0.3055 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 319.6491 - false_positives: 435.9298 - loss: 0.2727
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8777 - false_negatives: 382.9310 - false_positives: 476.5517 - loss: 0.3052 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 325.5345 - false_positives: 443.7758 - loss: 0.2727
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8779 - false_negatives: 389.1695 - false_positives: 484.7119 - loss: 0.3050 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 331.6610 - false_positives: 451.6102 - loss: 0.2727
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8780 - false_negatives: 395.3167 - false_positives: 493.2333 - loss: 0.3047 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 337.8167 - false_positives: 459.4833 - loss: 0.2728
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8781 - false_negatives: 401.7377 - false_positives: 501.5574 - loss: 0.3045 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 343.9016 - false_positives: 467.5574 - loss: 0.2729
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8782 - false_negatives: 408.1129 - false_positives: 510.0161 - loss: 0.3043 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8947 - false_negatives: 350.2419 - false_positives: 475.4677 - loss: 0.2730
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8783 - false_negatives: 414.6825 - false_positives: 518.4921 - loss: 0.3041 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8946 - false_negatives: 356.5555 - false_positives: 483.6032 - loss: 0.2731
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8784 - false_negatives: 421.1250 - false_positives: 527.1406 - loss: 0.3039 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8946 - false_negatives: 363.0625 - false_positives: 491.6719 - loss: 0.2732
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8785 - false_negatives: 427.6308 - false_positives: 535.6923 - loss: 0.3037 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8945 - false_negatives: 369.5231 - false_positives: 499.8154 - loss: 0.2733
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8786 - false_negatives: 434.0909 - false_positives: 544.2727 - loss: 0.3035 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8945 - false_negatives: 376.1364 - false_positives: 507.8636 - loss: 0.2734
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8787 - false_negatives: 440.7314 - false_positives: 552.7015 - loss: 0.3034 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8944 - false_negatives: 382.6866 - false_positives: 515.9702 - loss: 0.2736
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8788 - false_negatives: 447.2353 - false_positives: 561.3823 - loss: 0.3032 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8944 - false_negatives: 389.3088 - false_positives: 524.0735 - loss: 0.2737
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8788 - false_negatives: 454.0724 - false_positives: 569.9710 - loss: 0.3031 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8943 - false_negatives: 395.8551 - false_positives: 532.2174 - loss: 0.2738
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8789 - false_negatives: 460.8571 - false_positives: 578.5857 - loss: 0.3030 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8943 - false_negatives: 402.5143 - false_positives: 540.1857 - loss: 0.2739
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8789 - false_negatives: 467.6761 - false_positives: 587.3099 - loss: 0.3029 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8942 - false_negatives: 409.0845 - false_positives: 548.4366 - loss: 0.2740
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8790 - false_negatives: 474.6250 - false_positives: 595.8750 - loss: 0.3028 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8942 - false_negatives: 415.8472 - false_positives: 556.5555 - loss: 0.2741
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8790 - false_negatives: 481.5479 - false_positives: 604.6301 - loss: 0.3027 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8941 - false_negatives: 422.5205 - false_positives: 564.7672 - loss: 0.2743
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8790 - false_negatives: 488.4595 - false_positives: 613.3378 - loss: 0.3026 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8941 - false_negatives: 429.3649 - false_positives: 572.8919 - loss: 0.2744
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8791 - false_negatives: 495.4133 - false_positives: 621.9333 - loss: 0.3025 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8940 - false_negatives: 436.0933 - false_positives: 580.9733 - loss: 0.2745
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8791 - false_negatives: 502.3816 - false_positives: 630.5132 - loss: 0.3024 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8939 - false_negatives: 442.8289 - false_positives: 589.0789 - loss: 0.2746
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8791 - false_negatives: 509.3506 - false_positives: 639.0260 - loss: 0.3023 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8939 - false_negatives: 449.5714 - false_positives: 597.0519 - loss: 0.2747
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8792 - false_negatives: 516.3461 - false_positives: 647.5000 - loss: 0.3022 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8938 - false_negatives: 456.2692 - false_positives: 605.0385 - loss: 0.2748
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8792 - false_negatives: 523.5316 - false_positives: 655.8608 - loss: 0.3021 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8938 - false_negatives: 463.0127 - false_positives: 612.8860 - loss: 0.2749
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8792 - false_negatives: 530.6625 - false_positives: 664.3000 - loss: 0.3020 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8938 - false_negatives: 469.6250 - false_positives: 620.7875 - loss: 0.2750
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8793 - false_negatives: 537.8271 - false_positives: 672.6420 - loss: 0.3019 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8937 - false_negatives: 476.4815 - false_positives: 628.5309 - loss: 0.2751
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8793 - false_negatives: 545.0000 - false_positives: 681.0000 - loss: 0.3018 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8937 - false_negatives: 483.2195 - false_positives: 636.4146 - loss: 0.2752
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8793 - false_negatives: 552.2048 - false_positives: 689.2410 - loss: 0.3017 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8936 - false_negatives: 489.9879 - false_positives: 644.2289 - loss: 0.2753
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 559.3690 - false_positives: 697.5714 - loss: 0.3016 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8936 - false_negatives: 496.7976 - false_positives: 652.0595 - loss: 0.2754
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 566.8588 - false_positives: 705.7529 - loss: 0.3016 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8936 - false_negatives: 503.5882 - false_positives: 660.0706 - loss: 0.2755
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 574.2325 - false_positives: 714.2907 - loss: 0.3015 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8935 - false_negatives: 510.5116 - false_positives: 667.9302 - loss: 0.2756
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 581.6552 - false_positives: 722.7241 - loss: 0.3015 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8934 - false_negatives: 517.4138 - false_positives: 675.9425 - loss: 0.2757
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 589.2273 - false_positives: 731.0795 - loss: 0.3014 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8934 - false_negatives: 524.3864 - false_positives: 683.8068 - loss: 0.2758
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 596.7865 - false_positives: 739.4269 - loss: 0.3014 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8934 - false_negatives: 531.3483 - false_positives: 691.6517 - loss: 0.2760
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 604.3889 - false_positives: 747.7444 - loss: 0.3013 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8933 - false_negatives: 538.2444 - false_positives: 699.4445 - loss: 0.2761
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 612.0549 - false_positives: 756.0549 - loss: 0.3013 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8933 - false_negatives: 545.1208 - false_positives: 707.1758 - loss: 0.2762
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 619.6739 - false_positives: 764.4348 - loss: 0.3013 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 551.9348 - false_positives: 714.8587 - loss: 0.2762
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 627.4301 - false_positives: 772.6882 - loss: 0.3012 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 558.8925 - false_positives: 722.4516 - loss: 0.2763
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 635.1064 - false_positives: 780.9894 - loss: 0.3012 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 565.7766 - false_positives: 730.1915 - loss: 0.2764
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 642.7895 - false_positives: 789.1895 - loss: 0.3012 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 572.8316 - false_positives: 737.8210 - loss: 0.2765
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 650.4271 - false_positives: 797.4062 - loss: 0.3011 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 579.7917 - false_positives: 745.4479 - loss: 0.2766
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 658.0309 - false_positives: 805.5980 - loss: 0.3011 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 586.8557 - false_positives: 752.9691 - loss: 0.2767
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 665.7551 - false_positives: 813.7245 - loss: 0.3011 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 593.8367 - false_positives: 760.6429 - loss: 0.2768
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 673.4343 - false_positives: 822.0202 - loss: 0.3011 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 600.9596 - false_positives: 768.2626 - loss: 0.2769
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 681.2600 - false_positives: 830.2400 - loss: 0.3010 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 608.0200 - false_positives: 775.9300 - loss: 0.2769
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 689.0000 - false_positives: 838.4752 - loss: 0.3010 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 615.1287 - false_positives: 783.5643 - loss: 0.2770
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 696.7157 - false_positives: 846.6765 - loss: 0.3010 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 622.2647 - false_positives: 791.1569 - loss: 0.2771
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 704.4466 - false_positives: 854.7961 - loss: 0.3010 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 629.3787 - false_positives: 798.7767 - loss: 0.2772
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 712.1058 - false_positives: 862.9519 - loss: 0.3010 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 636.5289 - false_positives: 806.3558 - loss: 0.2773
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 719.8095 - false_positives: 871.0286 - loss: 0.3010 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 643.5905 - false_positives: 813.8953 - loss: 0.2774
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 727.5000 - false_positives: 879.1604 - loss: 0.3010 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 650.6132 - false_positives: 821.3679 - loss: 0.2774
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 735.2150 - false_positives: 887.2523 - loss: 0.3009 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 657.6262 - false_positives: 828.8037 - loss: 0.2775
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 742.8981 - false_positives: 895.3796 - loss: 0.3009 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 664.6019 - false_positives: 836.2222 - loss: 0.2776
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 750.5596 - false_positives: 903.5046 - loss: 0.3009 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 671.5963 - false_positives: 843.6331 - loss: 0.2776
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 758.2455 - false_positives: 911.5818 - loss: 0.3009 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 678.5909 - false_positives: 851.0546 - loss: 0.2777
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 765.9370 - false_positives: 919.6577 - loss: 0.3009 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 685.5946 - false_positives: 858.5135 - loss: 0.2777
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 773.6071 - false_positives: 927.7143 - loss: 0.3009 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 692.6161 - false_positives: 865.9018 - loss: 0.2778
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8794 - false_negatives: 781.2301 - false_positives: 935.7610 - loss: 0.3008 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 699.5840 - false_positives: 873.3983 - loss: 0.2779
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 788.9211 - false_positives: 943.7982 - loss: 0.3008 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 706.7632 - false_positives: 880.8158 - loss: 0.2779
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 796.5565 - false_positives: 951.9218 - loss: 0.3008 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 713.9304 - false_positives: 888.3304 - loss: 0.2780
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 804.3362 - false_positives: 959.9310 - loss: 0.3008 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 721.1379 - false_positives: 895.8017 - loss: 0.2781
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 812.0513 - false_positives: 967.9146 - loss: 0.3008 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 728.3504 - false_positives: 903.2906 - loss: 0.2782
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 819.7797 - false_positives: 975.9068 - loss: 0.3008 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 735.5508 - false_positives: 910.7712 - loss: 0.2782
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 827.5630 - false_positives: 983.8151 - loss: 0.3007 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 742.8403 - false_positives: 918.1933 - loss: 0.2783
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 835.3167 - false_positives: 991.7833 - loss: 0.3007 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 750.0583 - false_positives: 925.6166 - loss: 0.2784
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 843.1074 - false_positives: 999.7108 - loss: 0.3007 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 757.2397 - false_positives: 933.0165 - loss: 0.2784
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 850.8525 - false_positives: 1007.5984 - loss: 0.3007 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 764.4918 - false_positives: 940.3688 - loss: 0.2785
``` - + ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 858.5935 - false_positives: 1015.4634 - loss: 0.3007 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 771.7236 - false_positives: 947.7561 - loss: 0.2786
``` - + ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 866.3387 - false_positives: 1023.2984 - loss: 0.3006 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 779.0726 - false_positives: 955.0806 - loss: 0.2786
``` - + ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 874.0640 - false_positives: 1031.0959 - loss: 0.3006 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 786.3520 - false_positives: 962.5440 - loss: 0.2787
``` - + ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 881.7460 - false_positives: 1038.8651 - loss: 0.3006 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 793.7540 - false_positives: 969.9286 - loss: 0.2788
``` - + ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 889.4094 - false_positives: 1046.6063 - loss: 0.3006 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 801.1496 - false_positives: 977.3543 - loss: 0.2789
``` - + ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 897.1250 - false_positives: 1054.2891 - loss: 0.3005 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 808.5781 - false_positives: 984.7266 - loss: 0.2789
``` - + ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 904.7520 - false_positives: 1062.0465 - loss: 0.3005 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 816.0078 - false_positives: 992.0698 - loss: 0.2790
``` - + ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 912.5308 - false_positives: 1069.7076 - loss: 0.3005 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 823.3692 - false_positives: 999.4769 - loss: 0.2791
``` - + ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 920.2825 - false_positives: 1077.4810 - loss: 0.3005 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 830.8550 - false_positives: 1006.8320 - loss: 0.2791
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 928.0227 - false_positives: 1085.2273 - loss: 0.3004 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 838.3106 - false_positives: 1014.2879 - loss: 0.2792
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8795 - false_negatives: 935.8271 - false_positives: 1092.8872 - loss: 0.3004 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 845.7895 - false_positives: 1021.6992 - loss: 0.2793
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 943.6045 - false_positives: 1100.6343 - loss: 0.3004 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 853.2836 - false_positives: 1029.1194 - loss: 0.2793
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 951.4518 - false_positives: 1108.3112 - loss: 0.3004 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 860.7852 - false_positives: 1036.5037 - loss: 0.2794
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 959.2573 - false_positives: 1115.9854 - loss: 0.3004 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 868.2867 - false_positives: 1043.8604 - loss: 0.2795
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 967.0438 - false_positives: 1123.6277 - loss: 0.3003 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8918 - false_negatives: 875.7810 - false_positives: 1051.2117 - loss: 0.2795
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 974.8768 - false_positives: 1131.2102 - loss: 0.3003 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8917 - false_negatives: 883.3406 - false_positives: 1058.5289 - loss: 0.2796
```  ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 982.6619 - false_positives: 1138.8633 - loss: 0.3003 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8917 - false_negatives: 890.8489 - false_positives: 1065.9137 - loss: 0.2797
```  ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 990.5786 - false_positives: 1146.4357 - loss: 0.3003 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8917 - false_negatives: 898.4500 - false_positives: 1073.2357 - loss: 0.2797
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 998.4610 - false_positives: 1154.0071 - loss: 0.3003 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8916 - false_negatives: 906.0213 - false_positives: 1080.5391 - loss: 0.2798
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1006.3310 - false_positives: 1161.5704 - loss: 0.3002 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8916 - false_negatives: 913.5563 - false_positives: 1087.9225 - loss: 0.2798
``` - + ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1014.2028 - false_positives: 1169.0909 - loss: 0.3002 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8916 - false_negatives: 921.1678 - false_positives: 1095.2517 - loss: 0.2799
``` - + ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1022.0695 - false_positives: 1176.6111 - loss: 0.3002 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 928.7639 - false_positives: 1102.5347 - loss: 0.2800
``` - + ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1029.9794 - false_positives: 1184.1104 - loss: 0.3002 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 936.3380 - false_positives: 1109.8621 - loss: 0.2800
``` - + ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1037.8424 - false_positives: 1191.6506 - loss: 0.3002 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 943.9041 - false_positives: 1117.1644 - loss: 0.2801
``` - + ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1045.7142 - false_positives: 1199.1361 - loss: 0.3001 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8915 - false_negatives: 951.4966 - false_positives: 1124.4490 - loss: 0.2802
``` - + ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8796 - false_negatives: 1053.5338 - false_positives: 1206.6216 - loss: 0.3001 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8914 - false_negatives: 959.0405 - false_positives: 1131.7230 - loss: 0.2802
``` - + ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1061.3289 - false_positives: 1214.0739 - loss: 0.3001 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8914 - false_negatives: 966.6309 - false_positives: 1138.9933 - loss: 0.2803
``` - + ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1069.1200 - false_positives: 1221.5200 - loss: 0.3001 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8914 - false_negatives: 974.1800 - false_positives: 1146.2200 - loss: 0.2803
``` - + ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1076.9205 - false_positives: 1228.9602 - loss: 0.3000 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 981.7351 - false_positives: 1153.4238 - loss: 0.2804
``` - + ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1084.6974 - false_positives: 1236.3882 - loss: 0.3000 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 989.2303 - false_positives: 1160.6710 - loss: 0.2805
``` - + ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1092.4967 - false_positives: 1243.7909 - loss: 0.3000 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 996.7647 - false_positives: 1167.8431 - loss: 0.2805
``` - + ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1100.2467 - false_positives: 1251.2013 - loss: 0.3000 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 1004.2532 - false_positives: 1175.0714 - loss: 0.2806
```  ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1108.0322 - false_positives: 1258.5807 - loss: 0.2999 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8913 - false_negatives: 1011.6903 - false_positives: 1182.2968 - loss: 0.2806
```  ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8797 - false_negatives: 1115.7885 - false_positives: 1265.9935 - loss: 0.2999 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8912 - false_negatives: 1019.1987 - false_positives: 1189.4551 - loss: 0.2807
``` -Epoch 9: val_loss improved from 0.32718 to 0.32398, saving model to FullModelCheckpoint.keras +Epoch 9: val_loss did not improve from 0.32680  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8798 - false_negatives: 1131.0696 - false_positives: 1280.5380 - loss: 0.2999 - val_binary_accuracy: 0.8634 - val_false_negatives: 260.0000 - val_false_positives: 423.0000 - val_loss: 0.3240 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8912 - false_negatives: 1033.9684 - false_positives: 1203.5632 - loss: 0.2808 - val_binary_accuracy: 0.8588 - val_false_negatives: 330.0000 - val_false_positives: 376.0000 - val_loss: 0.3302
@@ -10360,1102 +10348,1102 @@ Epoch 10/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 93ms/step - binary_accuracy: 0.8828 - false_negatives: 19.0000 - false_positives: 11.0000 - loss: 0.2768 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 91ms/step - binary_accuracy: 0.8906 - false_negatives: 19.0000 - false_positives: 9.0000 - loss: 0.2946
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.8877 - false_negatives: 24.5000 - false_positives: 18.0000 - loss: 0.2675 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8936 - false_negatives: 23.5000 - false_positives: 17.0000 - loss: 0.2885
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8900 - false_negatives: 31.0000 - false_positives: 24.3333 - loss: 0.2658 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 29.0000 - false_positives: 24.3333 - loss: 0.2888
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8911 - false_negatives: 37.7500 - false_positives: 30.7500 - loss: 0.2625 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8969 - false_negatives: 34.7500 - false_positives: 30.0000 - loss: 0.2872
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8913 - false_negatives: 44.0000 - false_positives: 38.4000 - loss: 0.2632 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 38.6000 - false_positives: 36.6000 - loss: 0.2834
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8923 - false_negatives: 50.1667 - false_positives: 44.8333 - loss: 0.2626 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9011 - false_negatives: 43.1667 - false_positives: 42.5000 - loss: 0.2798
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8931 - false_negatives: 55.8571 - false_positives: 51.7143 - loss: 0.2616 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9024 - false_negatives: 46.5714 - false_positives: 49.7143 - loss: 0.2763
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8936 - false_negatives: 61.6250 - false_positives: 58.7500 - loss: 0.2609 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9035 - false_negatives: 50.7500 - false_positives: 56.2500 - loss: 0.2734
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8938 - false_negatives: 67.8889 - false_positives: 65.8889 - loss: 0.2609 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9046 - false_negatives: 54.5556 - false_positives: 62.7778 - loss: 0.2703
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8939 - false_negatives: 74.8000 - false_positives: 72.6000 - loss: 0.2612 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9055 - false_negatives: 58.3000 - false_positives: 69.3000 - loss: 0.2679
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 80.7273 - false_positives: 80.0000 - loss: 0.2613 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9062 - false_negatives: 62.8182 - false_positives: 75.6364 - loss: 0.2659
```  ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 87.7500 - false_positives: 86.4167 - loss: 0.2614 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9065 - false_negatives: 67.2500 - false_positives: 82.5000 - loss: 0.2641
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 94.1538 - false_positives: 93.6923 - loss: 0.2618 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9068 - false_negatives: 72.0769 - false_positives: 89.1538 - loss: 0.2627
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 101.0000 - false_positives: 100.5714 - loss: 0.2621 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9070 - false_negatives: 76.6429 - false_positives: 96.2143 - loss: 0.2613
``` - + ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8943 - false_negatives: 107.2667 - false_positives: 107.4000 - loss: 0.2622 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 81.7333 - false_positives: 103.2000 - loss: 0.2604
``` - + ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8944 - false_negatives: 112.8750 - false_positives: 115.1250 - loss: 0.2625 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 86.7500 - false_positives: 110.5625 - loss: 0.2597
``` - + ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8945 - false_negatives: 118.6471 - false_positives: 122.5294 - loss: 0.2627 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 91.7647 - false_positives: 117.7059 - loss: 0.2590
``` - + ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 124.2222 - false_positives: 130.1111 - loss: 0.2628 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 96.8333 - false_positives: 125.0000 - loss: 0.2586
``` - + ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 129.8947 - false_positives: 137.8421 - loss: 0.2630 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 101.8421 - false_positives: 132.0526 - loss: 0.2581
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 135.5000 - false_positives: 145.7000 - loss: 0.2633 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 107.0000 - false_positives: 139.1500 - loss: 0.2577
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 141.1429 - false_positives: 153.3333 - loss: 0.2635 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 112.1429 - false_positives: 146.3810 - loss: 0.2574
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 146.8636 - false_positives: 161.1364 - loss: 0.2637 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 117.3182 - false_positives: 153.4545 - loss: 0.2571
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 152.8261 - false_positives: 168.6522 - loss: 0.2640 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 122.3913 - false_positives: 160.6087 - loss: 0.2567
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 158.9167 - false_positives: 175.9583 - loss: 0.2642 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 127.5833 - false_positives: 167.5833 - loss: 0.2565
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 164.7200 - false_positives: 183.5200 - loss: 0.2643 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 132.4800 - false_positives: 174.9600 - loss: 0.2562
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 170.5769 - false_positives: 190.7692 - loss: 0.2644 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 137.5769 - false_positives: 182.1538 - loss: 0.2561
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 176.2593 - false_positives: 198.4444 - loss: 0.2646 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 142.5185 - false_positives: 189.4074 - loss: 0.2559
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 182.7857 - false_positives: 205.8571 - loss: 0.2648 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 147.2857 - false_positives: 196.6071 - loss: 0.2558
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 188.9310 - false_positives: 213.7931 - loss: 0.2650 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 152.2069 - false_positives: 203.6552 - loss: 0.2557
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 194.8333 - false_positives: 221.7000 - loss: 0.2653 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 157.0000 - false_positives: 210.9000 - loss: 0.2555
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 200.6774 - false_positives: 229.6452 - loss: 0.2655 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 161.8387 - false_positives: 218.0323 - loss: 0.2554
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 206.3438 - false_positives: 237.4062 - loss: 0.2657 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 166.4688 - false_positives: 225.2188 - loss: 0.2552
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 212.0000 - false_positives: 245.2424 - loss: 0.2658 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 171.0909 - false_positives: 232.3333 - loss: 0.2550
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 217.5294 - false_positives: 253.1765 - loss: 0.2660 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 175.6471 - false_positives: 239.5000 - loss: 0.2548
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 223.0857 - false_positives: 261.1429 - loss: 0.2661 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 180.2571 - false_positives: 246.4571 - loss: 0.2546
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 228.6111 - false_positives: 268.9722 - loss: 0.2662 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 184.6667 - false_positives: 253.4444 - loss: 0.2544
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 234.2432 - false_positives: 276.6216 - loss: 0.2663 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 189.2703 - false_positives: 260.3513 - loss: 0.2542
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 239.6053 - false_positives: 284.6316 - loss: 0.2664 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 193.7368 - false_positives: 267.6316 - loss: 0.2541
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 245.1282 - false_positives: 292.3846 - loss: 0.2665 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 198.3333 - false_positives: 274.7436 - loss: 0.2540
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 250.5250 - false_positives: 300.1750 - loss: 0.2666 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 203.0250 - false_positives: 281.8750 - loss: 0.2540
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 255.8781 - false_positives: 308.1219 - loss: 0.2667 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 207.7561 - false_positives: 288.9756 - loss: 0.2540
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 261.3095 - false_positives: 315.9048 - loss: 0.2667 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 212.4524 - false_positives: 296.1905 - loss: 0.2540
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 266.6744 - false_positives: 323.7442 - loss: 0.2668 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 217.3023 - false_positives: 303.2791 - loss: 0.2540
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 271.9773 - false_positives: 331.5454 - loss: 0.2668 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 222.1136 - false_positives: 310.5000 - loss: 0.2539
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 277.4000 - false_positives: 339.0667 - loss: 0.2669 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 226.9778 - false_positives: 317.8222 - loss: 0.2540
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 282.7391 - false_positives: 346.8696 - loss: 0.2669 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 231.8913 - false_positives: 325.1087 - loss: 0.2540
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 288.2766 - false_positives: 354.5107 - loss: 0.2670 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 236.8085 - false_positives: 332.3830 - loss: 0.2540
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 293.6667 - false_positives: 362.2500 - loss: 0.2670 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 241.6875 - false_positives: 339.5833 - loss: 0.2541
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 299.1837 - false_positives: 369.7143 - loss: 0.2670 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 246.7959 - false_positives: 346.6327 - loss: 0.2541
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 304.6600 - false_positives: 377.3600 - loss: 0.2671 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 251.8600 - false_positives: 353.7400 - loss: 0.2541
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 310.2941 - false_positives: 384.9412 - loss: 0.2671 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 257.0981 - false_positives: 360.7451 - loss: 0.2542
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 315.7692 - false_positives: 392.6731 - loss: 0.2672 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 262.2692 - false_positives: 367.9615 - loss: 0.2542
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8952 - false_negatives: 321.4717 - false_positives: 400.2264 - loss: 0.2672 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 267.7547 - false_positives: 375.1132 - loss: 0.2543
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8952 - false_negatives: 327.0370 - false_positives: 408.0000 - loss: 0.2673 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 273.2222 - false_positives: 382.3704 - loss: 0.2544
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8952 - false_negatives: 332.9455 - false_positives: 415.7091 - loss: 0.2673 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 278.6364 - false_positives: 389.5636 - loss: 0.2545
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8952 - false_negatives: 338.6964 - false_positives: 423.5000 - loss: 0.2674 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9067 - false_negatives: 284.2321 - false_positives: 396.6786 - loss: 0.2546
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 344.5614 - false_positives: 431.1579 - loss: 0.2674 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9066 - false_negatives: 289.7193 - false_positives: 403.9825 - loss: 0.2547
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 350.3793 - false_positives: 439.0000 - loss: 0.2675 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9066 - false_negatives: 295.4310 - false_positives: 411.2242 - loss: 0.2548
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 356.3390 - false_positives: 446.6780 - loss: 0.2676 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9065 - false_negatives: 301.0678 - false_positives: 418.4915 - loss: 0.2549
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 362.2167 - false_positives: 454.4000 - loss: 0.2676 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9065 - false_negatives: 306.6333 - false_positives: 425.8167 - loss: 0.2550
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 368.2131 - false_positives: 462.0492 - loss: 0.2677 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9064 - false_negatives: 312.3770 - false_positives: 433.0656 - loss: 0.2551
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8951 - false_negatives: 374.1452 - false_positives: 469.9677 - loss: 0.2677 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9063 - false_negatives: 318.0968 - false_positives: 440.4839 - loss: 0.2552
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 380.6349 - false_positives: 477.6984 - loss: 0.2679 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9062 - false_negatives: 323.9048 - false_positives: 447.8413 - loss: 0.2554
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8950 - false_negatives: 386.9688 - false_positives: 485.6250 - loss: 0.2680 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9062 - false_negatives: 329.6719 - false_positives: 455.3281 - loss: 0.2555
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 393.2615 - false_positives: 493.4462 - loss: 0.2681 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9061 - false_negatives: 335.6461 - false_positives: 462.6923 - loss: 0.2557
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 399.4849 - false_positives: 501.3636 - loss: 0.2682 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9060 - false_negatives: 341.5303 - false_positives: 470.3182 - loss: 0.2559
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8949 - false_negatives: 405.8507 - false_positives: 509.2388 - loss: 0.2683 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9059 - false_negatives: 347.6119 - false_positives: 477.8955 - loss: 0.2560
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 412.3235 - false_positives: 517.0441 - loss: 0.2684 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9058 - false_negatives: 353.5882 - false_positives: 485.6471 - loss: 0.2562
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 418.7536 - false_positives: 524.8406 - loss: 0.2686 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9057 - false_negatives: 359.7101 - false_positives: 493.3188 - loss: 0.2564
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 425.2143 - false_positives: 532.5428 - loss: 0.2687 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9056 - false_negatives: 366.0000 - false_positives: 500.9572 - loss: 0.2566
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 431.6902 - false_positives: 540.2817 - loss: 0.2688 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9055 - false_negatives: 372.3380 - false_positives: 508.5916 - loss: 0.2568
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8947 - false_negatives: 438.1389 - false_positives: 547.9167 - loss: 0.2690 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9053 - false_negatives: 378.6945 - false_positives: 516.1805 - loss: 0.2570
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 444.6164 - false_positives: 555.5206 - loss: 0.2691 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9052 - false_negatives: 385.1096 - false_positives: 523.6439 - loss: 0.2572
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 451.1622 - false_positives: 563.0541 - loss: 0.2692 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9051 - false_negatives: 391.4054 - false_positives: 531.2973 - loss: 0.2574
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8946 - false_negatives: 457.7867 - false_positives: 570.5067 - loss: 0.2693 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9050 - false_negatives: 397.9467 - false_positives: 538.8134 - loss: 0.2576
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8945 - false_negatives: 464.3158 - false_positives: 578.0526 - loss: 0.2694 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9049 - false_negatives: 404.3816 - false_positives: 546.3816 - loss: 0.2578
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8945 - false_negatives: 470.9481 - false_positives: 585.4415 - loss: 0.2695 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9048 - false_negatives: 410.9351 - false_positives: 553.8831 - loss: 0.2580
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8945 - false_negatives: 477.5000 - false_positives: 593.0000 - loss: 0.2696 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9047 - false_negatives: 417.4487 - false_positives: 561.3846 - loss: 0.2581
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8944 - false_negatives: 484.2405 - false_positives: 600.4177 - loss: 0.2698 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9046 - false_negatives: 424.0633 - false_positives: 568.8354 - loss: 0.2583
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8944 - false_negatives: 490.9250 - false_positives: 607.8500 - loss: 0.2699 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9045 - false_negatives: 430.5750 - false_positives: 576.3500 - loss: 0.2585
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8944 - false_negatives: 497.5926 - false_positives: 615.2469 - loss: 0.2700 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9044 - false_negatives: 437.1852 - false_positives: 583.8148 - loss: 0.2587
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8943 - false_negatives: 504.2683 - false_positives: 622.6342 - loss: 0.2701 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9043 - false_negatives: 443.7805 - false_positives: 591.2317 - loss: 0.2589
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8943 - false_negatives: 510.9398 - false_positives: 630.1205 - loss: 0.2702 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9042 - false_negatives: 450.3494 - false_positives: 598.5181 - loss: 0.2591
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8943 - false_negatives: 517.7500 - false_positives: 637.4643 - loss: 0.2703 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9042 - false_negatives: 456.8929 - false_positives: 605.8452 - loss: 0.2592
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 524.4588 - false_positives: 645.0236 - loss: 0.2704 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9041 - false_negatives: 463.3882 - false_positives: 613.1412 - loss: 0.2594
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 531.2791 - false_positives: 652.4883 - loss: 0.2705 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9040 - false_negatives: 469.8140 - false_positives: 620.4767 - loss: 0.2595
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8942 - false_negatives: 538.0115 - false_positives: 659.9080 - loss: 0.2706 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9039 - false_negatives: 476.4023 - false_positives: 627.6782 - loss: 0.2597
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 544.8182 - false_positives: 667.2386 - loss: 0.2707 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9038 - false_negatives: 482.9091 - false_positives: 635.1136 - loss: 0.2598
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 551.5843 - false_positives: 674.6068 - loss: 0.2708 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9037 - false_negatives: 489.6966 - false_positives: 642.4269 - loss: 0.2600
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 558.3666 - false_positives: 681.9222 - loss: 0.2709 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9037 - false_negatives: 496.4778 - false_positives: 649.8333 - loss: 0.2601
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8941 - false_negatives: 565.1868 - false_positives: 689.2088 - loss: 0.2710 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9036 - false_negatives: 503.3077 - false_positives: 657.2308 - loss: 0.2603
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8940 - false_negatives: 571.9783 - false_positives: 696.5217 - loss: 0.2711 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9035 - false_negatives: 510.1631 - false_positives: 664.5978 - loss: 0.2605
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8940 - false_negatives: 578.7850 - false_positives: 703.7742 - loss: 0.2712 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9034 - false_negatives: 517.0000 - false_positives: 671.9785 - loss: 0.2606
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8940 - false_negatives: 585.5958 - false_positives: 711.0958 - loss: 0.2712 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9033 - false_negatives: 523.9255 - false_positives: 679.2872 - loss: 0.2608
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8940 - false_negatives: 592.5684 - false_positives: 718.3369 - loss: 0.2713 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9032 - false_negatives: 530.8000 - false_positives: 686.5579 - loss: 0.2610
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8939 - false_negatives: 599.5000 - false_positives: 725.5938 - loss: 0.2714 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9031 - false_negatives: 537.6354 - false_positives: 693.8125 - loss: 0.2611
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8939 - false_negatives: 606.4330 - false_positives: 732.8557 - loss: 0.2715 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9030 - false_negatives: 544.4742 - false_positives: 701.0206 - loss: 0.2613
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8939 - false_negatives: 613.3163 - false_positives: 740.1021 - loss: 0.2716 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9030 - false_negatives: 551.2755 - false_positives: 708.1735 - loss: 0.2614
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8938 - false_negatives: 620.3232 - false_positives: 747.3232 - loss: 0.2717 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9029 - false_negatives: 558.2020 - false_positives: 715.2626 - loss: 0.2615
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8938 - false_negatives: 627.2600 - false_positives: 754.6900 - loss: 0.2718 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9028 - false_negatives: 565.0700 - false_positives: 722.3800 - loss: 0.2617
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8938 - false_negatives: 634.3762 - false_positives: 761.9406 - loss: 0.2718 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9028 - false_negatives: 571.9604 - false_positives: 729.4456 - loss: 0.2618
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8937 - false_negatives: 641.4804 - false_positives: 769.3333 - loss: 0.2719 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9027 - false_negatives: 578.8333 - false_positives: 736.5098 - loss: 0.2619
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8937 - false_negatives: 648.6407 - false_positives: 776.6310 - loss: 0.2720 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9026 - false_negatives: 585.6505 - false_positives: 743.5825 - loss: 0.2620
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8937 - false_negatives: 655.7885 - false_positives: 783.9615 - loss: 0.2721 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9026 - false_negatives: 592.5577 - false_positives: 750.6250 - loss: 0.2622
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8936 - false_negatives: 662.9619 - false_positives: 791.2476 - loss: 0.2722 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9025 - false_negatives: 599.4476 - false_positives: 757.7048 - loss: 0.2623
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8936 - false_negatives: 670.1226 - false_positives: 798.4905 - loss: 0.2723 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9024 - false_negatives: 606.4623 - false_positives: 764.7170 - loss: 0.2624
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8936 - false_negatives: 677.2897 - false_positives: 805.7664 - loss: 0.2723 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9023 - false_negatives: 613.4953 - false_positives: 771.8037 - loss: 0.2625
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8935 - false_negatives: 684.4445 - false_positives: 813.0370 - loss: 0.2724 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9023 - false_negatives: 620.5648 - false_positives: 778.8426 - loss: 0.2627
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8935 - false_negatives: 691.6973 - false_positives: 820.2661 - loss: 0.2725 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9022 - false_negatives: 627.7064 - false_positives: 785.8073 - loss: 0.2628
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8935 - false_negatives: 698.8636 - false_positives: 827.5728 - loss: 0.2725 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9021 - false_negatives: 634.8091 - false_positives: 792.8000 - loss: 0.2629
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8934 - false_negatives: 706.2162 - false_positives: 834.7928 - loss: 0.2726 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9021 - false_negatives: 641.9550 - false_positives: 799.7387 - loss: 0.2630
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8934 - false_negatives: 713.4911 - false_positives: 842.0982 - loss: 0.2727 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9020 - false_negatives: 649.0179 - false_positives: 806.7411 - loss: 0.2631
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8934 - false_negatives: 720.7610 - false_positives: 849.3452 - loss: 0.2728 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9019 - false_negatives: 656.1239 - false_positives: 813.6548 - loss: 0.2632
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8933 - false_negatives: 728.0877 - false_positives: 856.5702 - loss: 0.2728 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9019 - false_negatives: 663.1140 - false_positives: 820.6667 - loss: 0.2633
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8933 - false_negatives: 735.4000 - false_positives: 863.8435 - loss: 0.2729 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9018 - false_negatives: 670.1739 - false_positives: 827.6087 - loss: 0.2634
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 742.8276 - false_positives: 871.0690 - loss: 0.2730 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9018 - false_negatives: 677.2931 - false_positives: 834.5517 - loss: 0.2636
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 750.2137 - false_positives: 878.4615 - loss: 0.2731 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9017 - false_negatives: 684.4530 - false_positives: 841.4530 - loss: 0.2637
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8932 - false_negatives: 757.6695 - false_positives: 885.7797 - loss: 0.2732 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9016 - false_negatives: 691.6017 - false_positives: 848.3644 - loss: 0.2638
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 765.1260 - false_positives: 893.1008 - loss: 0.2732 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9016 - false_negatives: 698.7647 - false_positives: 855.2605 - loss: 0.2639
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8931 - false_negatives: 772.5583 - false_positives: 900.4833 - loss: 0.2733 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9015 - false_negatives: 705.9083 - false_positives: 862.1166 - loss: 0.2640
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 780.0082 - false_positives: 907.8347 - loss: 0.2734 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9015 - false_negatives: 713.0826 - false_positives: 868.9421 - loss: 0.2641
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 787.4590 - false_positives: 915.1475 - loss: 0.2735 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9014 - false_negatives: 720.2541 - false_positives: 875.8033 - loss: 0.2641
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8930 - false_negatives: 794.9187 - false_positives: 922.4309 - loss: 0.2736 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9014 - false_negatives: 727.3984 - false_positives: 882.6504 - loss: 0.2642
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 802.3226 - false_positives: 929.7097 - loss: 0.2737 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9013 - false_negatives: 734.5565 - false_positives: 889.4919 - loss: 0.2643
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 809.7120 - false_positives: 936.9600 - loss: 0.2737 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9012 - false_negatives: 741.6880 - false_positives: 896.3200 - loss: 0.2644
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8929 - false_negatives: 817.0476 - false_positives: 944.2222 - loss: 0.2738 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9012 - false_negatives: 748.8095 - false_positives: 903.1508 - loss: 0.2645
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 824.4330 - false_positives: 951.4882 - loss: 0.2739 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9011 - false_negatives: 756.0079 - false_positives: 909.9685 - loss: 0.2646
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 831.8125 - false_positives: 958.7344 - loss: 0.2739 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9011 - false_negatives: 763.1406 - false_positives: 916.8672 - loss: 0.2647
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8928 - false_negatives: 839.1395 - false_positives: 966.0000 - loss: 0.2740 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9010 - false_negatives: 770.4418 - false_positives: 923.6977 - loss: 0.2648
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 846.5077 - false_positives: 973.2308 - loss: 0.2741 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9010 - false_negatives: 777.6769 - false_positives: 930.6539 - loss: 0.2649
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 853.8550 - false_positives: 980.4504 - loss: 0.2741 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9009 - false_negatives: 784.9389 - false_positives: 937.6107 - loss: 0.2650
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8927 - false_negatives: 861.1894 - false_positives: 987.8030 - loss: 0.2742 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9009 - false_negatives: 792.1970 - false_positives: 944.5606 - loss: 0.2651
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 868.6541 - false_positives: 995.0677 - loss: 0.2743 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9008 - false_negatives: 799.5188 - false_positives: 951.5564 - loss: 0.2651
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 876.0522 - false_positives: 1002.4776 - loss: 0.2743 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9007 - false_negatives: 806.8358 - false_positives: 958.5373 - loss: 0.2652
``` - + ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8926 - false_negatives: 883.4593 - false_positives: 1009.8297 - loss: 0.2744 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9007 - false_negatives: 814.1630 - false_positives: 965.5333 - loss: 0.2653
``` - + ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 890.8897 - false_positives: 1017.2059 - loss: 0.2745 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9006 - false_negatives: 821.5441 - false_positives: 972.4780 - loss: 0.2654
``` - + ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 898.3285 - false_positives: 1024.5620 - loss: 0.2745 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9006 - false_negatives: 828.9416 - false_positives: 979.4379 - loss: 0.2655
``` - + ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8925 - false_negatives: 905.7681 - false_positives: 1031.9275 - loss: 0.2746 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9005 - false_negatives: 836.3478 - false_positives: 986.3551 - loss: 0.2656
``` - + ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 913.1799 - false_positives: 1039.2662 - loss: 0.2747 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9005 - false_negatives: 843.7410 - false_positives: 993.2662 - loss: 0.2657
``` - + ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 920.5928 - false_positives: 1046.6000 - loss: 0.2747 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9004 - false_negatives: 851.1000 - false_positives: 1000.1786 - loss: 0.2658
```  ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8924 - false_negatives: 928.0355 - false_positives: 1053.9149 - loss: 0.2748 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9004 - false_negatives: 858.4965 - false_positives: 1007.0922 - loss: 0.2659
```  ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 935.3943 - false_positives: 1061.2535 - loss: 0.2749 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9003 - false_negatives: 865.9225 - false_positives: 1013.9578 - loss: 0.2659
```  ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 942.8671 - false_positives: 1068.5385 - loss: 0.2749 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9003 - false_negatives: 873.3217 - false_positives: 1020.8252 - loss: 0.2660
```  ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8923 - false_negatives: 950.2847 - false_positives: 1075.9028 - loss: 0.2750 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9002 - false_negatives: 880.6945 - false_positives: 1027.6736 - loss: 0.2661
```  ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 957.7586 - false_positives: 1083.2207 - loss: 0.2750 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9002 - false_negatives: 888.0552 - false_positives: 1034.5104 - loss: 0.2662
```  ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 965.1849 - false_positives: 1090.5616 - loss: 0.2751 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9001 - false_negatives: 895.3561 - false_positives: 1041.3562 - loss: 0.2662
```  ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8922 - false_negatives: 972.6735 - false_positives: 1097.8707 - loss: 0.2751 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9001 - false_negatives: 902.6462 - false_positives: 1048.1837 - loss: 0.2663
```  ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 980.1757 - false_positives: 1105.1824 - loss: 0.2752 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9000 - false_negatives: 910.0135 - false_positives: 1054.9528 - loss: 0.2664
```  ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 987.6577 - false_positives: 1112.4698 - loss: 0.2753 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9000 - false_negatives: 917.3020 - false_positives: 1061.8792 - loss: 0.2665
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 995.1000 - false_positives: 1119.7733 - loss: 0.2753 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8999 - false_negatives: 924.6600 - false_positives: 1068.7333 - loss: 0.2665
```  ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8921 - false_negatives: 1002.5563 - false_positives: 1127.0464 - loss: 0.2753 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8999 - false_negatives: 931.9933 - false_positives: 1075.6093 - loss: 0.2666
``` - + ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 1009.9408 - false_positives: 1134.3684 - loss: 0.2754 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8998 - false_negatives: 939.3421 - false_positives: 1082.4934 - loss: 0.2667
``` - + ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 1017.4183 - false_positives: 1141.6144 - loss: 0.2754 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8998 - false_negatives: 946.6536 - false_positives: 1089.3660 - loss: 0.2667
``` - + ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8920 - false_negatives: 1024.8376 - false_positives: 1148.8961 - loss: 0.2755 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8997 - false_negatives: 953.9740 - false_positives: 1096.1884 - loss: 0.2668
``` - + ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 1032.3226 - false_positives: 1156.1096 - loss: 0.2755 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8997 - false_negatives: 961.2516 - false_positives: 1103.0903 - loss: 0.2669
``` - + ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8919 - false_negatives: 1039.7565 - false_positives: 1163.3397 - loss: 0.2756 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8997 - false_negatives: 968.6346 - false_positives: 1109.9103 - loss: 0.2669
``` -Epoch 10: val_loss did not improve from 0.32398 +Epoch 10: val_loss did not improve from 0.32680 - + ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.8919 - false_negatives: 1054.3798 - false_positives: 1177.5253 - loss: 0.2756 - val_binary_accuracy: 0.8642 - val_false_negatives: 289.0000 - val_false_positives: 390.0000 - val_loss: 0.3252 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8996 - false_negatives: 983.1202 - false_positives: 1123.3418 - loss: 0.2671 - val_binary_accuracy: 0.8558 - val_false_negatives: 445.0000 - val_false_positives: 276.0000 - val_loss: 0.3413
@@ -11465,16283 +11453,15344 @@ Epoch 11/20 ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 92ms/step - binary_accuracy: 0.8789 - false_negatives: 20.0000 - false_positives: 11.0000 - loss: 0.3039 + 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 90ms/step - binary_accuracy: 0.8906 - false_negatives: 22.0000 - false_positives: 6.0000 - loss: 0.2937
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 75ms/step - binary_accuracy: 0.8789 - false_negatives: 26.5000 - false_positives: 20.0000 - loss: 0.3014 + 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.8984 - false_negatives: 25.5000 - false_positives: 12.5000 - loss: 0.2747
```  ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8845 - false_negatives: 30.3333 - false_positives: 27.3333 - loss: 0.2947 + 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.9006 - false_negatives: 30.3333 - false_positives: 19.3333 - loss: 0.2678
```  ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8895 - false_negatives: 34.5000 - false_positives: 33.2500 - loss: 0.2878 + 4/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9025 - false_negatives: 34.2500 - false_positives: 26.5000 - loss: 0.2628
```  ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.8925 - false_negatives: 39.2000 - false_positives: 39.4000 - loss: 0.2832 + 5/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9039 - false_negatives: 38.2000 - false_positives: 33.6000 - loss: 0.2579
```  ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.8948 - false_negatives: 45.1667 - false_positives: 44.3333 - loss: 0.2791 + 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9053 - false_negatives: 42.1667 - false_positives: 40.1667 - loss: 0.2549
```  ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8966 - false_negatives: 50.8571 - false_positives: 49.5714 - loss: 0.2765 + 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9062 - false_negatives: 46.4286 - false_positives: 46.7143 - loss: 0.2526
```  ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 56.5000 - false_positives: 55.3750 - loss: 0.2745 + 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 50.7500 - false_positives: 53.2500 - loss: 0.2504
```  ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8987 - false_negatives: 62.8889 - false_positives: 60.6667 - loss: 0.2731 + 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9074 - false_negatives: 55.8889 - false_positives: 59.3333 - loss: 0.2489
```  ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8993 - false_negatives: 68.5000 - false_positives: 67.2000 - loss: 0.2726 + 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9075 - false_negatives: 61.1000 - false_positives: 66.0000 - loss: 0.2479
```  ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8996 - false_negatives: 74.5455 - false_positives: 73.6364 - loss: 0.2722 + 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.9076 - false_negatives: 66.4545 - false_positives: 72.5455 - loss: 0.2476
```  ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8996 - false_negatives: 80.3333 - false_positives: 81.1667 - loss: 0.2719 + 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9077 - false_negatives: 72.0000 - false_positives: 78.8333 - loss: 0.2473
```  ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8996 - false_negatives: 86.4615 - false_positives: 88.4615 - loss: 0.2717 + 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.9079 - false_negatives: 77.1538 - false_positives: 85.0769 - loss: 0.2470
```  ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 92.4286 - false_positives: 96.0000 - loss: 0.2714 + 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.9082 - false_negatives: 82.2143 - false_positives: 90.9286 - loss: 0.2462
```  ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 97.8667 - false_positives: 103.6667 - loss: 0.2711 + 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.9083 - false_negatives: 87.3333 - false_positives: 97.2000 - loss: 0.2457
``` - + ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8995 - false_negatives: 103.8750 - false_positives: 110.7500 - loss: 0.2708 + 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 71ms/step - binary_accuracy: 0.9085 - false_negatives: 92.7500 - false_positives: 103.0000 - loss: 0.2453
``` - + ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8994 - false_negatives: 109.3529 - false_positives: 118.7647 - loss: 0.2707 + 17/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9086 - false_negatives: 97.7059 - false_positives: 109.5294 - loss: 0.2451
``` - + ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.8993 - false_negatives: 115.6111 - false_positives: 126.3889 - loss: 0.2708 + 18/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9085 - false_negatives: 103.5000 - false_positives: 116.0000 - loss: 0.2453
``` - + ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.8991 - false_negatives: 121.6316 - false_positives: 134.0526 - loss: 0.2708 + 19/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9085 - false_negatives: 108.7895 - false_positives: 122.7368 - loss: 0.2452
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8991 - false_negatives: 127.1500 - false_positives: 141.8500 - loss: 0.2706 + 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9085 - false_negatives: 113.8500 - false_positives: 129.6000 - loss: 0.2451
```  ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8990 - false_negatives: 132.7619 - false_positives: 149.4762 - loss: 0.2705 + 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9084 - false_negatives: 119.3333 - false_positives: 136.0952 - loss: 0.2450
```  ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8990 - false_negatives: 138.0455 - false_positives: 157.2727 - loss: 0.2702 + 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 71ms/step - binary_accuracy: 0.9084 - false_negatives: 124.5909 - false_positives: 142.5909 - loss: 0.2448
```  ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8990 - false_negatives: 143.4783 - false_positives: 164.6956 - loss: 0.2699 + 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9085 - false_negatives: 129.8261 - false_positives: 148.9130 - loss: 0.2445
```  ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.8990 - false_negatives: 148.6667 - false_positives: 172.5417 - loss: 0.2697 + 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9086 - false_negatives: 134.7917 - false_positives: 155.3750 - loss: 0.2442
```  ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 153.9600 - false_positives: 179.9600 - loss: 0.2694 + 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9086 - false_negatives: 139.8000 - false_positives: 161.8000 - loss: 0.2441
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 159.0769 - false_positives: 187.6923 - loss: 0.2693 + 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9086 - false_negatives: 144.9231 - false_positives: 168.3077 - loss: 0.2440
```  ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 164.2593 - false_positives: 195.3704 - loss: 0.2691 + 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9087 - false_negatives: 150.0370 - false_positives: 174.5926 - loss: 0.2439
```  ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 169.4286 - false_positives: 203.3214 - loss: 0.2690 + 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9087 - false_negatives: 154.9286 - false_positives: 181.1786 - loss: 0.2439
```  ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 174.7586 - false_positives: 211.0000 - loss: 0.2688 + 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9088 - false_negatives: 159.8965 - false_positives: 187.4828 - loss: 0.2438
```  ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 179.9667 - false_positives: 218.7333 - loss: 0.2687 + 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9089 - false_negatives: 164.7000 - false_positives: 193.6667 - loss: 0.2437
```  ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 185.0645 - false_positives: 226.5161 - loss: 0.2685 + 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.9090 - false_negatives: 169.4194 - false_positives: 199.8710 - loss: 0.2435
```  ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 190.1875 - false_positives: 234.3438 - loss: 0.2683 + 32/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9091 - false_negatives: 174.0938 - false_positives: 206.0000 - loss: 0.2433
```  ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 195.3030 - false_positives: 241.8788 - loss: 0.2681 + 33/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9093 - false_negatives: 178.7273 - false_positives: 212.0606 - loss: 0.2431
```  ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 200.2941 - false_positives: 249.3529 - loss: 0.2678 + 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9094 - false_negatives: 183.6471 - false_positives: 217.9706 - loss: 0.2430
```  ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8993 - false_negatives: 205.1143 - false_positives: 257.1143 - loss: 0.2676 + 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9094 - false_negatives: 188.4000 - false_positives: 224.1429 - loss: 0.2429
```  ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8993 - false_negatives: 210.2222 - false_positives: 264.4722 - loss: 0.2673 + 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9095 - false_negatives: 193.0833 - false_positives: 230.2222 - loss: 0.2427
```  ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8994 - false_negatives: 215.1081 - false_positives: 272.0811 - loss: 0.2670 + 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9096 - false_negatives: 197.7568 - false_positives: 236.3243 - loss: 0.2426
```  ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8994 - false_negatives: 219.9474 - false_positives: 279.6053 - loss: 0.2668 + 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9097 - false_negatives: 202.4737 - false_positives: 242.4737 - loss: 0.2425
```  ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 224.8205 - false_positives: 287.0256 - loss: 0.2665 + 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9098 - false_negatives: 207.3077 - false_positives: 248.6923 - loss: 0.2424
```  ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 229.7500 - false_positives: 294.5500 - loss: 0.2662 + 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9099 - false_negatives: 212.1500 - false_positives: 254.7250 - loss: 0.2423
```  ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 234.9268 - false_positives: 302.1707 - loss: 0.2661 + 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9099 - false_negatives: 216.9512 - false_positives: 260.8781 - loss: 0.2422
```  ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 239.9524 - false_positives: 310.0000 - loss: 0.2659 + 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9100 - false_negatives: 221.8333 - false_positives: 266.9762 - loss: 0.2421
```  ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 244.9535 - false_positives: 317.7209 - loss: 0.2657 + 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9101 - false_negatives: 226.8372 - false_positives: 273.2093 - loss: 0.2420
```  ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 250.0000 - false_positives: 325.3409 - loss: 0.2655 + 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9101 - false_negatives: 231.8864 - false_positives: 279.3864 - loss: 0.2420
```  ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 254.9778 - false_positives: 333.0444 - loss: 0.2654 + 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9101 - false_negatives: 236.9556 - false_positives: 285.5778 - loss: 0.2419
```  ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 260.1739 - false_positives: 340.6087 - loss: 0.2652 + 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9102 - false_negatives: 242.1087 - false_positives: 291.7609 - loss: 0.2418
```  ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 265.3404 - false_positives: 348.1489 - loss: 0.2650 + 47/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9102 - false_negatives: 247.2553 - false_positives: 298.1277 - loss: 0.2418
```  ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8997 - false_negatives: 270.6875 - false_positives: 355.5417 - loss: 0.2648 + 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9102 - false_negatives: 252.6875 - false_positives: 304.3333 - loss: 0.2418
```  ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8997 - false_negatives: 275.9388 - false_positives: 363.1224 - loss: 0.2647 + 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9102 - false_negatives: 257.9184 - false_positives: 310.8776 - loss: 0.2418
```  ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 281.6400 - false_positives: 370.5800 - loss: 0.2645 + 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9101 - false_negatives: 263.5800 - false_positives: 317.2400 - loss: 0.2419
```  ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8996 - false_negatives: 287.2353 - false_positives: 378.6471 - loss: 0.2645 + 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9101 - false_negatives: 269.1569 - false_positives: 323.8235 - loss: 0.2420
```  ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 292.9038 - false_positives: 386.6538 - loss: 0.2645 + 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9100 - false_negatives: 274.7500 - false_positives: 330.3269 - loss: 0.2420
```  ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8995 - false_negatives: 298.6415 - false_positives: 394.6415 - loss: 0.2645 + 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9100 - false_negatives: 280.2453 - false_positives: 336.8679 - loss: 0.2421
```  ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8994 - false_negatives: 304.4259 - false_positives: 402.5741 - loss: 0.2645 + 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9100 - false_negatives: 285.6667 - false_positives: 343.4259 - loss: 0.2422
```  ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8994 - false_negatives: 310.1454 - false_positives: 410.4182 - loss: 0.2644 + 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9100 - false_negatives: 291.1636 - false_positives: 349.9091 - loss: 0.2423
```  ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8993 - false_negatives: 315.9464 - false_positives: 418.1607 - loss: 0.2644 + 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9099 - false_negatives: 296.6429 - false_positives: 356.4464 - loss: 0.2423
```  ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8993 - false_negatives: 321.6491 - false_positives: 425.8772 - loss: 0.2644 + 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9099 - false_negatives: 302.1404 - false_positives: 363.0526 - loss: 0.2424
```  ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 327.3621 - false_positives: 433.6552 - loss: 0.2644 + 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9099 - false_negatives: 307.5862 - false_positives: 369.7242 - loss: 0.2425
```  ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 333.1187 - false_positives: 441.3898 - loss: 0.2643 + 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.9098 - false_negatives: 313.1356 - false_positives: 376.4068 - loss: 0.2426
```  ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 72ms/step - binary_accuracy: 0.8992 - false_negatives: 338.8667 - false_positives: 449.0333 - loss: 0.2643 + 60/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9098 - false_negatives: 318.6833 - false_positives: 383.0167 - loss: 0.2427
```  ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 344.5246 - false_positives: 456.7541 - loss: 0.2643 + 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9097 - false_negatives: 324.3115 - false_positives: 389.5738 - loss: 0.2428
```  ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8991 - false_negatives: 350.3871 - false_positives: 464.4193 - loss: 0.2643 + 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9097 - false_negatives: 329.8548 - false_positives: 396.1774 - loss: 0.2429
```  ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8990 - false_negatives: 356.1587 - false_positives: 472.2222 - loss: 0.2643 + 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9097 - false_negatives: 335.5555 - false_positives: 402.7460 - loss: 0.2430
```  ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8990 - false_negatives: 361.9375 - false_positives: 479.9219 - loss: 0.2643 + 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9096 - false_negatives: 341.2031 - false_positives: 409.3906 - loss: 0.2431
```  ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8990 - false_negatives: 367.7231 - false_positives: 487.5077 - loss: 0.2642 + 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9096 - false_negatives: 347.0000 - false_positives: 415.8769 - loss: 0.2432
```  ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8990 - false_negatives: 373.5909 - false_positives: 494.9394 - loss: 0.2642 + 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9095 - false_negatives: 352.7576 - false_positives: 422.4697 - loss: 0.2433
```  ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 379.3731 - false_positives: 502.3881 - loss: 0.2642 + 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9095 - false_negatives: 358.5970 - false_positives: 429.0448 - loss: 0.2434
```  ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 385.2353 - false_positives: 509.7941 - loss: 0.2642 + 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9094 - false_negatives: 364.3971 - false_positives: 435.5735 - loss: 0.2436
```  ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 391.0000 - false_positives: 517.2319 - loss: 0.2642 + 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9094 - false_negatives: 370.1304 - false_positives: 442.0724 - loss: 0.2437
```  ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 396.9143 - false_positives: 524.5000 - loss: 0.2642 + 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9094 - false_negatives: 375.9857 - false_positives: 448.5571 - loss: 0.2438
```  ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 402.7465 - false_positives: 531.9155 - loss: 0.2642 + 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9093 - false_negatives: 381.8592 - false_positives: 455.0704 - loss: 0.2439
```  ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8989 - false_negatives: 408.6667 - false_positives: 539.2222 - loss: 0.2642 + 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9093 - false_negatives: 387.7639 - false_positives: 461.5555 - loss: 0.2440
```  ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 414.5479 - false_positives: 546.4932 - loss: 0.2641 + 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9092 - false_negatives: 393.6849 - false_positives: 468.0959 - loss: 0.2441
```  ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 420.4865 - false_positives: 553.6892 - loss: 0.2641 + 74/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9092 - false_negatives: 399.8513 - false_positives: 474.5811 - loss: 0.2442
```  ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 426.4000 - false_positives: 560.9467 - loss: 0.2641 + 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9091 - false_negatives: 405.9333 - false_positives: 481.3333 - loss: 0.2444
```  ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 432.4211 - false_positives: 568.0263 - loss: 0.2641 + 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9091 - false_negatives: 412.1184 - false_positives: 487.9342 - loss: 0.2445
```  ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 438.3766 - false_positives: 575.3896 - loss: 0.2641 + 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9090 - false_negatives: 418.3247 - false_positives: 494.4935 - loss: 0.2446
```  ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8988 - false_negatives: 444.4359 - false_positives: 582.6667 - loss: 0.2642 + 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9089 - false_negatives: 424.6154 - false_positives: 501.0000 - loss: 0.2448
```  ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8987 - false_negatives: 450.4430 - false_positives: 590.0253 - loss: 0.2642 + 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9089 - false_negatives: 430.8861 - false_positives: 507.5949 - loss: 0.2449
```  ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8987 - false_negatives: 456.5250 - false_positives: 597.3375 - loss: 0.2642 + 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9088 - false_negatives: 437.2375 - false_positives: 514.1875 - loss: 0.2450
```  ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8987 - false_negatives: 462.5926 - false_positives: 604.6173 - loss: 0.2642 + 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9087 - false_negatives: 443.6543 - false_positives: 520.7407 - loss: 0.2452
```  ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8987 - false_negatives: 468.6951 - false_positives: 611.8658 - loss: 0.2642 + 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9087 - false_negatives: 450.0366 - false_positives: 527.2439 - loss: 0.2453
```  ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8987 - false_negatives: 474.8434 - false_positives: 619.0361 - loss: 0.2642 + 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9086 - false_negatives: 456.4337 - false_positives: 533.7108 - loss: 0.2454
```  ```
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8986 - false_negatives: 480.9167 - false_positives: 626.2619 - loss: 0.2642 + 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9086 - false_negatives: 462.7500 - false_positives: 540.1786 - loss: 0.2456
```  ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8986 - false_negatives: 487.1294 - false_positives: 633.4588 - loss: 0.2642 + 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9085 - false_negatives: 469.1294 - false_positives: 546.5647 - loss: 0.2457
```  ```
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8986 - false_negatives: 493.3023 - false_positives: 640.7325 - loss: 0.2642 + 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9085 - false_negatives: 475.3954 - false_positives: 553.1279 - loss: 0.2458
```  ```
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8986 - false_negatives: 499.5287 - false_positives: 647.9425 - loss: 0.2641 + 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9084 - false_negatives: 481.8965 - false_positives: 559.5632 - loss: 0.2459
```  ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8986 - false_negatives: 505.7386 - false_positives: 655.0909 - loss: 0.2641 + 88/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9083 - false_negatives: 488.3977 - false_positives: 566.0227 - loss: 0.2460
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8985 - false_negatives: 511.9550 - false_positives: 662.2584 - loss: 0.2641 + 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9083 - false_negatives: 494.8989 - false_positives: 572.4832 - loss: 0.2462
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8985 - false_negatives: 518.2778 - false_positives: 669.3555 - loss: 0.2641 + 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9082 - false_negatives: 501.3667 - false_positives: 578.8778 - loss: 0.2463
```  ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8985 - false_negatives: 524.5494 - false_positives: 676.6264 - loss: 0.2641 + 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9082 - false_negatives: 507.8681 - false_positives: 585.2308 - loss: 0.2464
```  ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8985 - false_negatives: 530.8804 - false_positives: 683.8261 - loss: 0.2642 + 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9081 - false_negatives: 514.3696 - false_positives: 591.6848 - loss: 0.2465
```  ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8984 - false_negatives: 537.2581 - false_positives: 691.0753 - loss: 0.2642 + 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9081 - false_negatives: 520.8172 - false_positives: 598.0753 - loss: 0.2466
```  ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8984 - false_negatives: 543.5851 - false_positives: 698.2447 - loss: 0.2642 + 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9080 - false_negatives: 527.2979 - false_positives: 604.4255 - loss: 0.2467
```  ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8984 - false_negatives: 549.9474 - false_positives: 705.3895 - loss: 0.2642 + 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9080 - false_negatives: 533.7474 - false_positives: 610.7474 - loss: 0.2468
```  ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8984 - false_negatives: 556.3542 - false_positives: 712.4688 - loss: 0.2642 + 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9079 - false_negatives: 540.2292 - false_positives: 617.0104 - loss: 0.2469
```  ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8983 - false_negatives: 562.6701 - false_positives: 719.5258 - loss: 0.2642 + 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9079 - false_negatives: 546.6495 - false_positives: 623.3196 - loss: 0.2470
```  ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8983 - false_negatives: 569.1021 - false_positives: 726.5102 - loss: 0.2642 + 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9078 - false_negatives: 553.1633 - false_positives: 629.5919 - loss: 0.2471
```  ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8983 - false_negatives: 575.4949 - false_positives: 733.5555 - loss: 0.2642 + 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9078 - false_negatives: 559.6161 - false_positives: 635.9091 - loss: 0.2472
```  ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8983 - false_negatives: 581.9900 - false_positives: 740.5800 - loss: 0.2642 + 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9077 - false_negatives: 566.0700 - false_positives: 642.2800 - loss: 0.2473
```  ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8983 - false_negatives: 588.5148 - false_positives: 747.6139 - loss: 0.2642 + 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9077 - false_negatives: 572.5643 - false_positives: 648.6436 - loss: 0.2474
```  ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8982 - false_negatives: 594.9804 - false_positives: 754.6078 - loss: 0.2642 + 102/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9076 - false_negatives: 579.0196 - false_positives: 655.0490 - loss: 0.2475
```  ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8982 - false_negatives: 601.4175 - false_positives: 761.5922 - loss: 0.2642 + 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9076 - false_negatives: 585.5728 - false_positives: 661.3787 - loss: 0.2476
```  ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8982 - false_negatives: 607.9135 - false_positives: 768.6058 - loss: 0.2643 + 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9076 - false_negatives: 592.0865 - false_positives: 667.8077 - loss: 0.2477
```  ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8982 - false_negatives: 614.3428 - false_positives: 775.5809 - loss: 0.2643 + 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9075 - false_negatives: 598.7714 - false_positives: 674.1810 - loss: 0.2479
```  ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8982 - false_negatives: 620.7547 - false_positives: 782.4623 - loss: 0.2643 + 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9075 - false_negatives: 605.3774 - false_positives: 680.6132 - loss: 0.2480
```  ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8982 - false_negatives: 627.1215 - false_positives: 789.3832 - loss: 0.2643 + 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9074 - false_negatives: 612.0000 - false_positives: 687.0000 - loss: 0.2481
```  ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 633.5555 - false_positives: 796.2407 - loss: 0.2643 + 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9074 - false_negatives: 618.6481 - false_positives: 693.3519 - loss: 0.2482
```  ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 639.9449 - false_positives: 803.1284 - loss: 0.2643 + 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9073 - false_negatives: 625.2569 - false_positives: 699.7431 - loss: 0.2483
```  ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 646.3546 - false_positives: 809.9272 - loss: 0.2643 + 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9073 - false_negatives: 631.9182 - false_positives: 706.1273 - loss: 0.2484
```  ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 652.7568 - false_positives: 816.7387 - loss: 0.2643 + 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9072 - false_negatives: 638.5135 - false_positives: 712.5585 - loss: 0.2485
```  ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 659.2232 - false_positives: 823.5179 - loss: 0.2643 + 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9072 - false_negatives: 645.1071 - false_positives: 718.9375 - loss: 0.2486
```  ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 665.6814 - false_positives: 830.3009 - loss: 0.2643 + 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 651.6548 - false_positives: 725.3540 - loss: 0.2487
```  ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 672.2368 - false_positives: 837.0351 - loss: 0.2643 + 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9071 - false_negatives: 658.2368 - false_positives: 731.7193 - loss: 0.2488
```  ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives: 678.7826 - false_positives: 843.9913 - loss: 0.2643 + 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 664.7478 - false_positives: 738.1739 - loss: 0.2488
```  ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 685.4655 - false_positives: 850.8535 - loss: 0.2643 + 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 671.3448 - false_positives: 744.5517 - loss: 0.2489
```  ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 692.1453 - false_positives: 857.8547 - loss: 0.2644 + 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9070 - false_negatives: 677.9146 - false_positives: 750.9316 - loss: 0.2490
```  ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 698.8220 - false_positives: 864.8305 - loss: 0.2644 + 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 684.4492 - false_positives: 757.3220 - loss: 0.2491
```  ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 705.5714 - false_positives: 871.8151 - loss: 0.2644 + 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9069 - false_negatives: 690.9496 - false_positives: 763.7311 - loss: 0.2492
```  ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8980 - false_negatives: 712.3250 - false_positives: 878.7833 - loss: 0.2644 + 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 697.5084 - false_positives: 770.1334 - loss: 0.2493
```  ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8979 - false_negatives: 719.1240 - false_positives: 885.7273 - loss: 0.2645 + 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 704.0248 - false_positives: 776.5537 - loss: 0.2493
```  ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8979 - false_negatives: 725.8934 - false_positives: 892.6885 - loss: 0.2645 + 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9068 - false_negatives: 710.5820 - false_positives: 782.8934 - loss: 0.2494
```  ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8979 - false_negatives: 732.6829 - false_positives: 899.6504 - loss: 0.2645 + 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9067 - false_negatives: 717.0732 - false_positives: 789.3252 - loss: 0.2495
```  ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8979 - false_negatives: 739.4758 - false_positives: 906.5968 - loss: 0.2646 + 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9067 - false_negatives: 723.6855 - false_positives: 795.6774 - loss: 0.2496
```  ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 746.2560 - false_positives: 913.5120 - loss: 0.2646 + 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9066 - false_negatives: 730.2880 - false_positives: 802.0880 - loss: 0.2497
```  ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 753.0000 - false_positives: 920.4921 - loss: 0.2646 + 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9066 - false_negatives: 736.8889 - false_positives: 808.5000 - loss: 0.2498
```  ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 759.7874 - false_positives: 927.4252 - loss: 0.2646 + 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9066 - false_negatives: 743.4960 - false_positives: 814.9134 - loss: 0.2498
```  ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8978 - false_negatives: 766.5391 - false_positives: 934.4141 - loss: 0.2646 + 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9065 - false_negatives: 750.0391 - false_positives: 821.3125 - loss: 0.2499
```  ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 773.3178 - false_positives: 941.4108 - loss: 0.2647 + 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9065 - false_negatives: 756.6512 - false_positives: 827.7054 - loss: 0.2500
```  ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 780.0615 - false_positives: 948.4231 - loss: 0.2647 + 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9064 - false_negatives: 763.2462 - false_positives: 834.1462 - loss: 0.2501
```  ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 786.7863 - false_positives: 955.4351 - loss: 0.2647 + 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9064 - false_negatives: 769.8320 - false_positives: 840.5496 - loss: 0.2502
```  ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 793.5151 - false_positives: 962.3939 - loss: 0.2647 + 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9064 - false_negatives: 776.4773 - false_positives: 846.9697 - loss: 0.2502
```  ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8977 - false_negatives: 800.2556 - false_positives: 969.3158 - loss: 0.2647 + 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9063 - false_negatives: 783.1353 - false_positives: 853.3759 - loss: 0.2503
```  ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 806.9105 - false_positives: 976.3806 - loss: 0.2648 + 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9063 - false_negatives: 789.7761 - false_positives: 859.8134 - loss: 0.2504
```  ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 813.7926 - false_positives: 983.3555 - loss: 0.2648 + 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9063 - false_negatives: 796.4370 - false_positives: 866.2074 - loss: 0.2505
```  ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 820.6397 - false_positives: 990.4338 - loss: 0.2648 + 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9062 - false_negatives: 803.0956 - false_positives: 872.5883 - loss: 0.2506
```  ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8976 - false_negatives: 827.4598 - false_positives: 997.5037 - loss: 0.2649 + 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9062 - false_negatives: 809.7591 - false_positives: 879.0073 - loss: 0.2506
```  ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 834.2464 - false_positives: 1004.5797 - loss: 0.2649 + 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9061 - false_negatives: 816.4348 - false_positives: 885.3840 - loss: 0.2507
``` - + ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 841.1079 - false_positives: 1011.6403 - loss: 0.2649 + 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9061 - false_negatives: 823.0792 - false_positives: 891.7770 - loss: 0.2508
``` - + ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 847.9929 - false_positives: 1018.6714 - loss: 0.2650 + 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9061 - false_negatives: 829.7500 - false_positives: 898.1214 - loss: 0.2508
``` - + ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8975 - false_negatives: 854.8511 - false_positives: 1025.7375 - loss: 0.2650 + 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9060 - false_negatives: 836.4114 - false_positives: 904.5461 - loss: 0.2509
``` - + ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 861.7394 - false_positives: 1032.7606 - loss: 0.2650 + 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9060 - false_negatives: 843.1268 - false_positives: 910.9437 - loss: 0.2510
``` - + ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 868.6573 - false_positives: 1039.8252 - loss: 0.2651 + 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9060 - false_negatives: 849.8461 - false_positives: 917.3357 - loss: 0.2511
``` - + ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 875.5903 - false_positives: 1046.8680 - loss: 0.2651 + 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9059 - false_negatives: 856.5208 - false_positives: 923.7570 - loss: 0.2511
``` - + ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8974 - false_negatives: 882.5517 - false_positives: 1053.8414 - loss: 0.2651 + 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9059 - false_negatives: 863.1862 - false_positives: 930.1448 - loss: 0.2512
``` - + ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 889.5000 - false_positives: 1060.7946 - loss: 0.2652 + 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9059 - false_negatives: 869.8425 - false_positives: 936.5274 - loss: 0.2513
``` - + ```
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 896.4558 - false_positives: 1067.7007 - loss: 0.2652 + 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives: 876.4626 - false_positives: 942.9319 - loss: 0.2513
``` - + ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 903.4257 - false_positives: 1074.6554 - loss: 0.2652 + 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives: 883.1554 - false_positives: 949.2770 - loss: 0.2514
``` - + ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8973 - false_negatives: 910.4295 - false_positives: 1081.5839 - loss: 0.2652 + 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives: 889.8121 - false_positives: 955.7516 - loss: 0.2515
``` - + ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 917.3933 - false_positives: 1088.5333 - loss: 0.2653 + 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9057 - false_negatives: 896.5867 - false_positives: 962.1866 - loss: 0.2516
``` - + ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 924.3643 - false_positives: 1095.4702 - loss: 0.2653 + 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9057 - false_negatives: 903.3245 - false_positives: 968.6357 - loss: 0.2516
``` - + ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 931.3289 - false_positives: 1102.4210 - loss: 0.2653 + 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9057 - false_negatives: 910.0592 - false_positives: 975.0526 - loss: 0.2517
``` - + ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8972 - false_negatives: 938.3856 - false_positives: 1109.3398 - loss: 0.2654 + 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9056 - false_negatives: 916.7843 - false_positives: 981.4510 - loss: 0.2518
``` - + ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8971 - false_negatives: 945.4026 - false_positives: 1116.3312 - loss: 0.2654 + 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9056 - false_negatives: 923.4870 - false_positives: 987.9286 - loss: 0.2518
``` - + ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8971 - false_negatives: 952.4903 - false_positives: 1123.2516 - loss: 0.2654 + 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9056 - false_negatives: 930.2774 - false_positives: 994.3613 - loss: 0.2519
``` - + ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8971 - false_negatives: 959.5320 - false_positives: 1130.3141 - loss: 0.2655 + 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9055 - false_negatives: 937.0320 - false_positives: 1000.8589 - loss: 0.2520
``` -Epoch 11: val_loss did not improve from 0.32398 +Epoch 11: val_loss did not improve from 0.32680  ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.8970 - false_negatives: 973.4747 - false_positives: 1144.1709 - loss: 0.2655 - val_binary_accuracy: 0.8518 - val_false_negatives: 178.0000 - val_false_positives: 563.0000 - val_loss: 0.3375 + 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.9055 - false_negatives: 950.3608 - false_positives: 1013.6456 - loss: 0.2521 - val_binary_accuracy: 0.8602 - val_false_negatives: 402.0000 - val_false_positives: 297.0000 - val_loss: 0.3281
``` -Epoch 12/20 +Epoch 11: early stopping ```
- 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 93ms/step - binary_accuracy: 0.9297 - false_negatives: 4.0000 - false_positives: 14.0000 - loss: 0.2291 - -
-``` - -``` -
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 72ms/step - binary_accuracy: 0.9170 - false_negatives: 10.0000 - false_positives: 23.5000 - loss: 0.2458 +![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_15_1755.png) + -
-``` - -``` -
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9134 - false_negatives: 15.0000 - false_positives: 31.3333 - loss: 0.2459 -
-``` - -``` -
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9131 - false_negatives: 19.5000 - false_positives: 37.7500 - loss: 0.2476 -
-``` - -``` -
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9125 - false_negatives: 24.2000 - false_positives: 44.6000 - loss: 0.2469 + +![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_15_1756.png) + -
-``` - -``` -
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 10s 72ms/step - binary_accuracy: 0.9122 - false_negatives: 28.6667 - false_positives: 51.5000 - loss: 0.2451
``` - -``` -
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 33.7143 - false_positives: 57.8571 - loss: 0.2443 +---------------------------------------------------------------------------------------------------- -
-``` - -``` -
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 39.1250 - false_positives: 63.6250 - loss: 0.2440 +Test set evaluation: {'binary_accuracy': 0.8507999777793884, 'false_negatives': 397.0, 'false_positives': 349.0, 'loss': 0.3372706174850464} +---------------------------------------------------------------------------------------------------- -
-``` - ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 43.5556 - false_positives: 70.2222 - loss: 0.2434 +--- +## Training via Active Learning -
-``` - -``` -
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9121 - false_negatives: 48.3000 - false_positives: 76.4000 - loss: 0.2430 +The general process we follow when performing Active Learning is demonstrated below: -
-``` - -``` -
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 52.5455 - false_positives: 83.5455 - loss: 0.2425 +![Active Learning](https://i.imgur.com/dmNKusp.png) -
-``` - -``` -
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 57.7500 - false_positives: 89.7500 - loss: 0.2421 +The pipeline can be summarized in five parts: -
-``` - -``` -
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 62.1538 - false_positives: 97.3846 - loss: 0.2421 +1. Sample and annotate a small, balanced training dataset +2. Train the model on this small subset +3. Evaluate the model on a balanced testing set +4. If the model satisfies the business criteria, deploy it in a real time setting +5. If it doesn't pass the criteria, sample a few more samples according to the ratio of +false positives and negatives, add them to the training set and repeat from step 2 till +the model passes the tests or till all available data is exhausted. -
-``` - -``` -
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9115 - false_negatives: 67.0714 - false_positives: 104.4286 - loss: 0.2422 +For the code below, we will perform sampling using the following formula:
-
-``` - -``` -
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 71.8000 - false_positives: 111.6000 - loss: 0.2424 +![Ratio Sampling](https://i.imgur.com/LyZEiZL.png) -
-``` - -``` -
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9111 - false_negatives: 76.3750 - false_positives: 118.9375 - loss: 0.2424 +Active Learning techniques use callbacks extensively for progress tracking. We will be +using model checkpointing and early stopping for this example. The `patience` parameter +for Early Stopping can help minimize overfitting and the time required. We have set it +`patience=4` for now but since the model is robust, we can increase the patience level if +desired. -
-``` - -``` -
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 81.0588 - false_positives: 126.0588 - loss: 0.2425 +Note: We are not loading the checkpoint after the first training iteration. In my +experience working on Active Learning techniques, this helps the model probe the +newly formed loss landscape. Even if the model fails to improve in the second iteration, +we will still gain insight about the possible future false positive and negative rates. +This will help us sample a better set in the next iteration where the model will have a +greater chance to improve. -
-``` - -``` -
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 85.5000 - false_positives: 133.3889 - loss: 0.2426 -
-``` - -``` -
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 89.8947 - false_positives: 140.2105 - loss: 0.2425 +```python -
-``` - -``` -
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 94.2500 - false_positives: 147.2000 - loss: 0.2426 +def train_active_learning_models( + train_dataset, + pool_negatives, + pool_positives, + val_dataset, + test_dataset, + num_iterations=3, + sampling_size=5000, +): -
-``` - -``` -
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 98.9524 - false_positives: 153.8571 - loss: 0.2426 + # Creating lists for storing metrics + losses, val_losses, accuracies, val_accuracies = [], [], [], [] -
-``` - -``` -
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 103.6364 - false_positives: 160.4091 - loss: 0.2425 + model = create_model() + # We will monitor the false positives and false negatives predicted by our model + # These will decide the subsequent sampling ratio for every Active Learning loop + model.compile( + loss="binary_crossentropy", + optimizer="rmsprop", + metrics=[ + keras.metrics.BinaryAccuracy(), + keras.metrics.FalseNegatives(), + keras.metrics.FalsePositives(), + ], + ) -
-``` - -``` -
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 108.6957 - false_positives: 166.6956 - loss: 0.2425 + # Defining checkpoints. + # The checkpoint callback is reused throughout the training since it only saves the best overall model. + checkpoint = keras.callbacks.ModelCheckpoint( + "AL_Model.keras", save_best_only=True, verbose=1 + ) + # Here, patience is set to 4. This can be set higher if desired. + early_stopping = keras.callbacks.EarlyStopping(patience=4, verbose=1) -
-``` - + print(f"Starting to train with {len(train_dataset)} samples") + # Initial fit with a small subset of the training set + history = model.fit( + train_dataset.cache().shuffle(20000).batch(256), + epochs=20, + validation_data=val_dataset, + callbacks=[checkpoint, early_stopping], + ) + + # Appending history + losses, val_losses, accuracies, val_accuracies = append_history( + losses, val_losses, accuracies, val_accuracies, history + ) + + for iteration in range(num_iterations): + # Getting predictions from previously trained model + predictions = model.predict(test_dataset) + + # Generating labels from the output probabilities + rounded = ops.where(ops.greater(predictions, 0.5), 1, 0) + + # Evaluating the number of zeros and ones incorrrectly classified + _, _, false_negatives, false_positives = model.evaluate(test_dataset, verbose=0) + + print("-" * 100) + print( + f"Number of zeros incorrectly classified: {false_negatives}, Number of ones incorrectly classified: {false_positives}" + ) + + # This technique of Active Learning demonstrates ratio based sampling where + # Number of ones/zeros to sample = Number of ones/zeros incorrectly classified / Total incorrectly classified + if false_negatives != 0 and false_positives != 0: + total = false_negatives + false_positives + sample_ratio_ones, sample_ratio_zeros = ( + false_positives / total, + false_negatives / total, + ) + # In the case where all samples are correctly predicted, we can sample both classes equally + else: + sample_ratio_ones, sample_ratio_zeros = 0.5, 0.5 + + print( + f"Sample ratio for positives: {sample_ratio_ones}, Sample ratio for negatives:{sample_ratio_zeros}" + ) + + # Sample the required number of ones and zeros + sampled_dataset = pool_negatives.take( + int(sample_ratio_zeros * sampling_size) + ).concatenate(pool_positives.take(int(sample_ratio_ones * sampling_size))) + + # Skip the sampled data points to avoid repetition of sample + pool_negatives = pool_negatives.skip(int(sample_ratio_zeros * sampling_size)) + pool_positives = pool_positives.skip(int(sample_ratio_ones * sampling_size)) + + # Concatenating the train_dataset with the sampled_dataset + train_dataset = train_dataset.concatenate(sampled_dataset).prefetch( + tf.data.AUTOTUNE + ) + + print(f"Starting training with {len(train_dataset)} samples") + print("-" * 100) + + # We recompile the model to reset the optimizer states and retrain the model + model.compile( + loss="binary_crossentropy", + optimizer="rmsprop", + metrics=[ + keras.metrics.BinaryAccuracy(), + keras.metrics.FalseNegatives(), + keras.metrics.FalsePositives(), + ], + ) + history = model.fit( + train_dataset.cache().shuffle(20000).batch(256), + validation_data=val_dataset, + epochs=20, + callbacks=[ + checkpoint, + keras.callbacks.EarlyStopping(patience=4, verbose=1), + ], + ) + + # Appending the history + losses, val_losses, accuracies, val_accuracies = append_history( + losses, val_losses, accuracies, val_accuracies, history + ) + + # Loading the best model from this training loop + model = keras.models.load_model("AL_Model.keras") + + # Plotting the overall history and evaluating the final model + plot_history(losses, val_losses, accuracies, val_accuracies) + print("-" * 100) + print( + "Test set evaluation: ", + model.evaluate(test_dataset, verbose=0, return_dict=True), + ) + print("-" * 100) + + return model + + +active_learning_model = train_active_learning_models( + train_dataset, pool_negatives, pool_positives, val_dataset, test_dataset +) ``` -
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 113.3750 - false_positives: 173.3333 - loss: 0.2424 + + +
Model: "sequential_1"
+
+ + + + +
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
+┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
+│ embedding_1 (Embedding)         │ (None, 150, 128)       │       384,000 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ bidirectional_1 (Bidirectional) │ (None, 150, 64)        │        41,216 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ global_max_pooling1d_1          │ (None, 64)             │             0 │
+│ (GlobalMaxPooling1D)            │                        │               │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dense_2 (Dense)                 │ (None, 20)             │         1,300 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dropout_1 (Dropout)             │ (None, 20)             │             0 │
+├─────────────────────────────────┼────────────────────────┼───────────────┤
+│ dense_3 (Dense)                 │ (None, 1)              │            21 │
+└─────────────────────────────────┴────────────────────────┴───────────────┘
+
+ + + + +
 Total params: 426,537 (1.63 MB)
+
+ + + + +
 Trainable params: 426,537 (1.63 MB)
+
+ + + + +
 Non-trainable params: 0 (0.00 B)
+
+ +
``` - +Starting to train with 15000 samples +Epoch 1/20 + ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 118.2000 - false_positives: 179.7600 - loss: 0.2423 + + 1/59 ━━━━━━━━━━━━━━━━━━━━ 2:36 3s/step - binary_accuracy: 0.4805 - false_negatives_1: 90.0000 - false_positives_1: 43.0000 - loss: 0.6938
```  ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 123.0769 - false_positives: 185.9615 - loss: 0.2421 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.4883 - false_negatives_1: 108.5000 - false_positives_1: 87.0000 - loss: 0.6935
``` - + ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 127.8889 - false_positives: 191.9259 - loss: 0.2419 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.4957 - false_negatives_1: 128.6667 - false_positives_1: 127.0000 - loss: 0.6934
``` - + ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9111 - false_negatives: 132.5000 - false_positives: 198.1786 - loss: 0.2416 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.5007 - false_negatives_1: 153.5000 - false_positives_1: 162.2500 - loss: 0.6932
``` - + ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9112 - false_negatives: 137.1379 - false_positives: 204.4138 - loss: 0.2413 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.5001 - false_negatives_1: 184.8000 - false_positives_1: 196.4000 - loss: 0.6932
``` - + ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 141.7000 - false_positives: 210.6000 - loss: 0.2410 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.4995 - false_negatives_1: 215.1667 - false_positives_1: 231.3333 - loss: 0.6932
``` - + ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 146.2581 - false_positives: 216.7419 - loss: 0.2407 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.4998 - false_negatives_1: 245.0000 - false_positives_1: 265.2857 - loss: 0.6932
``` - + ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9114 - false_negatives: 150.8125 - false_positives: 222.8438 - loss: 0.2404 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5003 - false_negatives_1: 274.3750 - false_positives_1: 299.1250 - loss: 0.6932
``` - + ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9115 - false_negatives: 155.4545 - false_positives: 228.9697 - loss: 0.2401 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.5009 - false_negatives_1: 304.3333 - false_positives_1: 332.1111 - loss: 0.6932
``` - + ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 160.1471 - false_positives: 235.0882 - loss: 0.2398 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.5012 - false_negatives_1: 333.4000 - false_positives_1: 366.4000 - loss: 0.6932
``` - + ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 164.7143 - false_positives: 241.2286 - loss: 0.2395 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5015 - false_negatives_1: 358.9091 - false_positives_1: 404.0909 - loss: 0.6932
``` - + ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 169.3056 - false_positives: 247.2778 - loss: 0.2393 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5014 - false_negatives_1: 383.0833 - false_positives_1: 444.2500 - loss: 0.6932
``` - + ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9118 - false_negatives: 173.9189 - false_positives: 253.2703 - loss: 0.2390 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5015 - false_negatives_1: 406.3846 - false_positives_1: 484.5385 - loss: 0.6932
``` - + ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9118 - false_negatives: 178.4211 - false_positives: 259.5000 - loss: 0.2388 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5014 - false_negatives_1: 428.8571 - false_positives_1: 526.5000 - loss: 0.6932
``` - + ```
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 183.1795 - false_positives: 265.7436 - loss: 0.2387 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5016 - false_negatives_1: 451.0000 - false_positives_1: 567.4667 - loss: 0.6932
``` - + ```
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 187.8750 - false_positives: 272.1750 - loss: 0.2386 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5019 - false_negatives_1: 472.1875 - false_positives_1: 608.8125 - loss: 0.6932
``` - + ```
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 192.8781 - false_positives: 278.5122 - loss: 0.2385 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5023 - false_negatives_1: 493.4118 - false_positives_1: 649.7647 - loss: 0.6932
``` - + ```
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 197.7857 - false_positives: 285.1190 - loss: 0.2385 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5028 - false_negatives_1: 515.1667 - false_positives_1: 689.8333 - loss: 0.6932
``` - + ```
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 202.6977 - false_positives: 291.6279 - loss: 0.2384 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5032 - false_negatives_1: 538.7895 - false_positives_1: 728.2632 - loss: 0.6931
``` - + ```
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 207.5909 - false_positives: 298.0909 - loss: 0.2383 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5036 - false_negatives_1: 563.2500 - false_positives_1: 765.6500 - loss: 0.6931
``` - + ```
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 212.6222 - false_positives: 304.5111 - loss: 0.2383 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5041 - false_negatives_1: 588.5714 - false_positives_1: 801.2381 - loss: 0.6931
``` - + ```
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 217.4565 - false_positives: 311.0869 - loss: 0.2382 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5046 - false_negatives_1: 614.3182 - false_positives_1: 836.5000 - loss: 0.6931
``` - + ```
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9118 - false_negatives: 222.8511 - false_positives: 317.4468 - loss: 0.2382 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5049 - false_negatives_1: 642.2174 - false_positives_1: 870.2609 - loss: 0.6931
``` - + ```
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9118 - false_negatives: 228.0833 - false_positives: 324.1667 - loss: 0.2383 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5052 - false_negatives_1: 672.2917 - false_positives_1: 902.1250 - loss: 0.6931
``` - + ```
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 233.3878 - false_positives: 330.8163 - loss: 0.2384 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5054 - false_negatives_1: 703.9200 - false_positives_1: 932.8000 - loss: 0.6931
``` - + ```
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 238.6600 - false_positives: 337.5200 - loss: 0.2384 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5057 - false_negatives_1: 737.0769 - false_positives_1: 961.8846 - loss: 0.6930
``` - + ```
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 243.9216 - false_positives: 344.2745 - loss: 0.2385 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5060 - false_negatives_1: 769.9630 - false_positives_1: 990.5555 - loss: 0.6930
``` - + ```
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 249.1538 - false_positives: 351.0385 - loss: 0.2386 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5063 - false_negatives_1: 801.8214 - false_positives_1: 1019.8929 - loss: 0.6930
``` - + ```
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9115 - false_negatives: 254.5660 - false_positives: 357.7736 - loss: 0.2387 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5067 - false_negatives_1: 833.1035 - false_positives_1: 1049.3448 - loss: 0.6930
``` - + ```
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9114 - false_negatives: 259.9074 - false_positives: 364.6667 - loss: 0.2388 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5071 - false_negatives_1: 864.3333 - false_positives_1: 1078.3667 - loss: 0.6930
``` - + ```
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9114 - false_negatives: 265.3455 - false_positives: 371.4546 - loss: 0.2388 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5076 - false_negatives_1: 894.3226 - false_positives_1: 1108.3226 - loss: 0.6930
``` - + ```
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 270.6786 - false_positives: 378.2500 - loss: 0.2389 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5080 - false_negatives_1: 922.9688 - false_positives_1: 1139.5000 - loss: 0.6929
``` - + ```
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 276.0526 - false_positives: 384.9825 - loss: 0.2390 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5084 - false_negatives_1: 950.3939 - false_positives_1: 1171.8485 - loss: 0.6929
``` - + ```
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9112 - false_negatives: 281.6724 - false_positives: 391.5862 - loss: 0.2390 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5088 - false_negatives_1: 977.1765 - false_positives_1: 1204.9706 - loss: 0.6929
``` - + ```
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9111 - false_negatives: 287.1864 - false_positives: 398.6102 - loss: 0.2392 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5093 - false_negatives_1: 1002.8857 - false_positives_1: 1238.8857 - loss: 0.6929
``` - + ```
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 292.8667 - false_positives: 405.5000 - loss: 0.2393 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5097 - false_negatives_1: 1027.4722 - false_positives_1: 1273.7500 - loss: 0.6928
``` - + ```
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 298.4590 - false_positives: 412.5082 - loss: 0.2394 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5101 - false_negatives_1: 1051.5946 - false_positives_1: 1308.8108 - loss: 0.6928
``` - + ```
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 304.1129 - false_positives: 419.3871 - loss: 0.2395 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5106 - false_negatives_1: 1075.7894 - false_positives_1: 1343.4210 - loss: 0.6928
``` - + ```
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9108 - false_negatives: 309.6984 - false_positives: 426.4286 - loss: 0.2396 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5110 - false_negatives_1: 1099.4615 - false_positives_1: 1378.4103 - loss: 0.6927
``` - + ```
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9107 - false_negatives: 315.3750 - false_positives: 433.3594 - loss: 0.2397 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5115 - false_negatives_1: 1123.3500 - false_positives_1: 1413.0000 - loss: 0.6927
``` - + ```
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9106 - false_negatives: 321.0000 - false_positives: 440.3385 - loss: 0.2398 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5120 - false_negatives_1: 1147.6097 - false_positives_1: 1447.0731 - loss: 0.6927
``` - + ```
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9106 - false_negatives: 326.5454 - false_positives: 447.2727 - loss: 0.2399 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5124 - false_negatives_1: 1172.5952 - false_positives_1: 1480.2380 - loss: 0.6926
``` - + ```
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9105 - false_negatives: 332.2239 - false_positives: 454.1194 - loss: 0.2400 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5129 - false_negatives_1: 1198.0698 - false_positives_1: 1512.7906 - loss: 0.6926
``` - + ```
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9104 - false_negatives: 337.9412 - false_positives: 460.9706 - loss: 0.2401 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5134 - false_negatives_1: 1224.0227 - false_positives_1: 1544.5227 - loss: 0.6926
``` - + ```
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9104 - false_negatives: 343.7101 - false_positives: 467.8696 - loss: 0.2402 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.5138 - false_negatives_1: 1251.1777 - false_positives_1: 1575.0667 - loss: 0.6925
``` - + ```
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9103 - false_negatives: 349.5143 - false_positives: 474.6857 - loss: 0.2403 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5143 - false_negatives_1: 1279.5000 - false_positives_1: 1604.4783 - loss: 0.6925
``` - + ```
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9102 - false_negatives: 355.3662 - false_positives: 481.5493 - loss: 0.2405 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5147 - false_negatives_1: 1308.7021 - false_positives_1: 1633.0000 - loss: 0.6924
``` - + ```
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9101 - false_negatives: 361.2500 - false_positives: 488.4305 - loss: 0.2406 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5152 - false_negatives_1: 1338.5416 - false_positives_1: 1660.7916 - loss: 0.6924
``` - + ```
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9101 - false_negatives: 367.1096 - false_positives: 495.2603 - loss: 0.2407 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5156 - false_negatives_1: 1369.3673 - false_positives_1: 1687.7755 - loss: 0.6924
``` - + ```
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9100 - false_negatives: 373.0270 - false_positives: 502.1216 - loss: 0.2408 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5160 - false_negatives_1: 1400.7600 - false_positives_1: 1714.1600 - loss: 0.6923
``` - + ```
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9099 - false_negatives: 379.0267 - false_positives: 508.9200 - loss: 0.2409 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5164 - false_negatives_1: 1432.2941 - false_positives_1: 1740.2157 - loss: 0.6923
``` - + ```
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9099 - false_negatives: 384.9211 - false_positives: 515.7500 - loss: 0.2410 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5168 - false_negatives_1: 1464.5000 - false_positives_1: 1765.5193 - loss: 0.6922
``` - + ```
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9098 - false_negatives: 390.9221 - false_positives: 522.5455 - loss: 0.2411 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5172 - false_negatives_1: 1496.5471 - false_positives_1: 1790.6227 - loss: 0.6921
``` - + ```
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9097 - false_negatives: 396.9744 - false_positives: 529.2308 - loss: 0.2412 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5176 - false_negatives_1: 1528.7593 - false_positives_1: 1815.5370 - loss: 0.6921
``` - + ```
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9096 - false_negatives: 403.0380 - false_positives: 535.9874 - loss: 0.2413 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5180 - false_negatives_1: 1560.4000 - false_positives_1: 1840.4364 - loss: 0.6920
``` - + ```
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9096 - false_negatives: 409.2375 - false_positives: 542.7000 - loss: 0.2415 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5185 - false_negatives_1: 1592.0714 - false_positives_1: 1865.2322 - loss: 0.6920
``` - + ```
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9095 - false_negatives: 415.4321 - false_positives: 549.4568 - loss: 0.2416 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5189 - false_negatives_1: 1623.8070 - false_positives_1: 1889.7720 - loss: 0.6919
``` - + ```
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9094 - false_negatives: 421.7317 - false_positives: 556.1342 - loss: 0.2417 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5193 - false_negatives_1: 1655.4656 - false_positives_1: 1914.3448 - loss: 0.6919
``` - + ```
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9093 - false_negatives: 427.9156 - false_positives: 562.9639 - loss: 0.2418 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.5197 - false_negatives_1: 1686.7457 - false_positives_1: 1938.3051 - loss: 0.6918 +
``` - -``` -
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9093 - false_negatives: 434.2738 - false_positives: 569.6548 - loss: 0.2419 +Epoch 1: val_loss improved from inf to 0.67428, saving model to AL_Model.keras -
-``` - + ```
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9092 - false_negatives: 440.5647 - false_positives: 576.3882 - loss: 0.2421 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 8s 89ms/step - binary_accuracy: 0.5202 - false_negatives_1: 1716.9833 - false_positives_1: 1961.4667 - loss: 0.6917 - val_binary_accuracy: 0.6464 - val_false_negatives_1: 279.0000 - val_false_positives_1: 1489.0000 - val_loss: 0.6743 -
-``` - -``` -
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9091 - false_negatives: 446.9186 - false_positives: 583.0582 - loss: 0.2422
``` - -``` -
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9090 - false_negatives: 453.2184 - false_positives: 589.8161 - loss: 0.2423 +Epoch 2/20 -
-``` - ```
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9090 - false_negatives: 459.6477 - false_positives: 596.4773 - loss: 0.2424 + + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 86ms/step - binary_accuracy: 0.6562 - false_negatives_1: 31.0000 - false_positives_1: 57.0000 - loss: 0.6762
```  ```
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9089 - false_negatives: 466.1011 - false_positives: 603.1685 - loss: 0.2425 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.6436 - false_negatives_1: 49.5000 - false_positives_1: 89.0000 - loss: 0.6762
```  ```
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9088 - false_negatives: 472.5778 - false_positives: 609.7889 - loss: 0.2427 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6369 - false_negatives_1: 67.3333 - false_positives_1: 121.3333 - loss: 0.6754
``` - + ```
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9088 - false_negatives: 478.9890 - false_positives: 616.3077 - loss: 0.2428 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6352 - false_negatives_1: 87.0000 - false_positives_1: 149.2500 - loss: 0.6747
``` - + ```
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9087 - false_negatives: 485.4131 - false_positives: 622.8696 - loss: 0.2429 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6341 - false_negatives_1: 104.6000 - false_positives_1: 179.2000 - loss: 0.6741
``` - + ```
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9086 - false_negatives: 491.9032 - false_positives: 629.4731 - loss: 0.2430 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6340 - false_negatives_1: 121.8333 - false_positives_1: 208.5000 - loss: 0.6734
``` - + ```
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9086 - false_negatives: 498.3936 - false_positives: 636.1064 - loss: 0.2431 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6351 - false_negatives_1: 139.0000 - false_positives_1: 235.8571 - loss: 0.6727
``` - + ```
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9085 - false_negatives: 504.8316 - false_positives: 642.7474 - loss: 0.2432 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6358 - false_negatives_1: 156.5000 - false_positives_1: 263.3750 - loss: 0.6721
``` - + ```
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9084 - false_negatives: 511.2812 - false_positives: 649.4271 - loss: 0.2433 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6361 - false_negatives_1: 178.4444 - false_positives_1: 287.3333 - loss: 0.6717
``` - + ```
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9084 - false_negatives: 517.7732 - false_positives: 656.0206 - loss: 0.2434 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6364 - false_negatives_1: 200.0000 - false_positives_1: 311.7000 - loss: 0.6713
``` - + ```
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9083 - false_negatives: 524.1837 - false_positives: 662.7959 - loss: 0.2435 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6367 - false_negatives_1: 220.0000 - false_positives_1: 337.4546 - loss: 0.6708
``` - + ```
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9082 - false_negatives: 530.7374 - false_positives: 669.4747 - loss: 0.2436 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6370 - false_negatives_1: 241.6667 - false_positives_1: 361.3333 - loss: 0.6704
``` - + ```
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9082 - false_negatives: 537.2200 - false_positives: 676.1800 - loss: 0.2437 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6374 - false_negatives_1: 264.0769 - false_positives_1: 384.1538 - loss: 0.6701
``` - + ```
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9081 - false_negatives: 543.7624 - false_positives: 682.8317 - loss: 0.2438 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6379 - false_negatives_1: 286.8571 - false_positives_1: 406.1429 - loss: 0.6697
``` - + ```
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9080 - false_negatives: 550.2549 - false_positives: 689.4804 - loss: 0.2439 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6382 - false_negatives_1: 311.2667 - false_positives_1: 427.1333 - loss: 0.6693
``` - + ```
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9080 - false_negatives: 556.8156 - false_positives: 696.0874 - loss: 0.2440 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6387 - false_negatives_1: 334.3750 - false_positives_1: 448.3750 - loss: 0.6690
``` - + ```
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9079 - false_negatives: 563.4231 - false_positives: 702.7115 - loss: 0.2441 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6393 - false_negatives_1: 356.1765 - false_positives_1: 470.4706 - loss: 0.6686
``` - + ```
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9078 - false_negatives: 570.0000 - false_positives: 709.4286 - loss: 0.2443 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6399 - false_negatives_1: 376.6667 - false_positives_1: 493.6111 - loss: 0.6682
``` - + ```
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9078 - false_negatives: 576.6509 - false_positives: 716.0755 - loss: 0.2444 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6403 - false_negatives_1: 396.7895 - false_positives_1: 517.6316 - loss: 0.6679
``` - + ```
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9077 - false_negatives: 583.2430 - false_positives: 722.7664 - loss: 0.2445 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6407 - false_negatives_1: 417.1500 - false_positives_1: 541.9000 - loss: 0.6676
``` - + ```
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9076 - false_negatives: 589.8426 - false_positives: 729.4352 - loss: 0.2446 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6412 - false_negatives_1: 438.0476 - false_positives_1: 564.7143 - loss: 0.6672
``` - + ```
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9076 - false_negatives: 596.4404 - false_positives: 736.0642 - loss: 0.2447 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6416 - false_negatives_1: 457.7727 - false_positives_1: 588.7727 - loss: 0.6669
``` - + ```
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9075 - false_negatives: 603.1000 - false_positives: 742.7000 - loss: 0.2448 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6420 - false_negatives_1: 478.0435 - false_positives_1: 612.4783 - loss: 0.6665
``` - + ```
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9075 - false_negatives: 609.7297 - false_positives: 749.3874 - loss: 0.2449 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6424 - false_negatives_1: 498.5417 - false_positives_1: 635.9167 - loss: 0.6662
``` - + ```
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9074 - false_negatives: 616.3571 - false_positives: 755.9911 - loss: 0.2450 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6427 - false_negatives_1: 520.0400 - false_positives_1: 658.1600 - loss: 0.6658
``` - + ```
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9073 - false_negatives: 622.9557 - false_positives: 762.5575 - loss: 0.2450 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6431 - false_negatives_1: 540.9615 - false_positives_1: 680.8461 - loss: 0.6655
``` - + ```
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9073 - false_negatives: 629.5351 - false_positives: 769.0877 - loss: 0.2451 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6435 - false_negatives_1: 561.6296 - false_positives_1: 703.6667 - loss: 0.6651
``` - + ```
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9072 - false_negatives: 636.1652 - false_positives: 775.6000 - loss: 0.2452 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6438 - false_negatives_1: 582.5000 - false_positives_1: 726.6071 - loss: 0.6648
``` - + ```
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9072 - false_negatives: 642.8017 - false_positives: 782.1983 - loss: 0.2453 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6441 - false_negatives_1: 603.2759 - false_positives_1: 749.5862 - loss: 0.6644
``` - + ```
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9071 - false_negatives: 649.5726 - false_positives: 788.7180 - loss: 0.2454 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6444 - false_negatives_1: 623.6334 - false_positives_1: 772.8000 - loss: 0.6641
``` - + ```
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9071 - false_negatives: 656.3220 - false_positives: 795.3051 - loss: 0.2455 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6447 - false_negatives_1: 643.8065 - false_positives_1: 796.3549 - loss: 0.6638
``` - + ```
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9070 - false_negatives: 663.1260 - false_positives: 801.8823 - loss: 0.2456 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6450 - false_negatives_1: 664.3125 - false_positives_1: 819.2500 - loss: 0.6635
``` - + ```
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9070 - false_negatives: 669.9167 - false_positives: 808.4250 - loss: 0.2457 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6454 - false_negatives_1: 684.6667 - false_positives_1: 842.0000 - loss: 0.6631
``` - + ```
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9069 - false_negatives: 676.7108 - false_positives: 814.9421 - loss: 0.2458 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6457 - false_negatives_1: 705.2353 - false_positives_1: 864.5000 - loss: 0.6628
``` - + ```
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9068 - false_negatives: 683.4426 - false_positives: 821.5820 - loss: 0.2459 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6460 - false_negatives_1: 725.0286 - false_positives_1: 887.9429 - loss: 0.6625
``` - + ```
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9068 - false_negatives: 690.3090 - false_positives: 828.1382 - loss: 0.2459 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6462 - false_negatives_1: 746.4445 - false_positives_1: 910.3055 - loss: 0.6622
``` - + ```
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9067 - false_negatives: 697.1694 - false_positives: 834.7581 - loss: 0.2460 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6464 - false_negatives_1: 767.0270 - false_positives_1: 933.8378 - loss: 0.6619
``` - + ```
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9067 - false_negatives: 704.0880 - false_positives: 841.3680 - loss: 0.2461 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6466 - false_negatives_1: 788.1053 - false_positives_1: 956.7895 - loss: 0.6616
``` - + ```
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9066 - false_negatives: 711.0079 - false_positives: 847.9048 - loss: 0.2462 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6467 - false_negatives_1: 808.9744 - false_positives_1: 979.8718 - loss: 0.6614
``` - + ```
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9066 - false_negatives: 717.9370 - false_positives: 854.4094 - loss: 0.2463 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6469 - false_negatives_1: 829.3750 - false_positives_1: 1003.1750 - loss: 0.6611
``` - + ```
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9065 - false_negatives: 724.8594 - false_positives: 860.8984 - loss: 0.2464 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6471 - false_negatives_1: 850.0732 - false_positives_1: 1026.1951 - loss: 0.6608
``` - + ```
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9064 - false_negatives: 731.8682 - false_positives: 867.3256 - loss: 0.2465 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6473 - false_negatives_1: 870.7381 - false_positives_1: 1049.0238 - loss: 0.6605
``` - + ```
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9064 - false_negatives: 738.8538 - false_positives: 873.8077 - loss: 0.2466 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6476 - false_negatives_1: 891.2791 - false_positives_1: 1071.5581 - loss: 0.6603
``` - + ```
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9063 - false_negatives: 745.9313 - false_positives: 880.2366 - loss: 0.2467 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6478 - false_negatives_1: 912.3182 - false_positives_1: 1093.5227 - loss: 0.6600
``` - + ```
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9063 - false_negatives: 752.9545 - false_positives: 886.7424 - loss: 0.2468 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.6480 - false_negatives_1: 932.5333 - false_positives_1: 1116.6666 - loss: 0.6597
``` - + ```
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9062 - false_negatives: 760.0301 - false_positives: 893.2481 - loss: 0.2469 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6482 - false_negatives_1: 953.0870 - false_positives_1: 1139.3914 - loss: 0.6594
``` - + ```
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9062 - false_negatives: 767.0895 - false_positives: 899.7612 - loss: 0.2470 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6484 - false_negatives_1: 973.3830 - false_positives_1: 1162.0426 - loss: 0.6592
``` - + ```
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9061 - false_negatives: 774.2074 - false_positives: 906.2296 - loss: 0.2471 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6486 - false_negatives_1: 993.9583 - false_positives_1: 1184.3541 - loss: 0.6589
``` - + ```
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9061 - false_negatives: 781.3309 - false_positives: 912.6985 - loss: 0.2472 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6488 - false_negatives_1: 1014.1633 - false_positives_1: 1207.0613 - loss: 0.6586
``` - + ```
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9060 - false_negatives: 788.4744 - false_positives: 919.1679 - loss: 0.2473 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6490 - false_negatives_1: 1035.4600 - false_positives_1: 1229.0800 - loss: 0.6583
``` - + ```
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9059 - false_negatives: 795.6522 - false_positives: 925.5724 - loss: 0.2474 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6491 - false_negatives_1: 1055.9608 - false_positives_1: 1252.3529 - loss: 0.6581
``` - + ```
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9059 - false_negatives: 802.8129 - false_positives: 932.0504 - loss: 0.2475 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6493 - false_negatives_1: 1076.1154 - false_positives_1: 1275.5769 - loss: 0.6579
``` - + ```
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9058 - false_negatives: 809.9786 - false_positives: 938.5286 - loss: 0.2476 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6494 - false_negatives_1: 1096.1321 - false_positives_1: 1298.6415 - loss: 0.6576
``` - + ```
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9058 - false_negatives: 817.1560 - false_positives: 944.9716 - loss: 0.2476 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6496 - false_negatives_1: 1115.8704 - false_positives_1: 1321.5741 - loss: 0.6573
``` - + ```
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9057 - false_negatives: 824.3028 - false_positives: 951.4296 - loss: 0.2477 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6498 - false_negatives_1: 1136.5636 - false_positives_1: 1343.7455 - loss: 0.6571
``` - + ```
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9057 - false_negatives: 831.5035 - false_positives: 957.8182 - loss: 0.2478 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6500 - false_negatives_1: 1156.6964 - false_positives_1: 1366.4464 - loss: 0.6568
``` - + ```
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9056 - false_negatives: 838.6805 - false_positives: 964.2639 - loss: 0.2479 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6502 - false_negatives_1: 1176.6666 - false_positives_1: 1389.1052 - loss: 0.6566
``` - + ```
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9056 - false_negatives: 845.8621 - false_positives: 970.6758 - loss: 0.2480 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6504 - false_negatives_1: 1196.3966 - false_positives_1: 1411.9656 - loss: 0.6563
``` - + ```
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9055 - false_negatives: 853.0548 - false_positives: 977.1096 - loss: 0.2481 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.6505 - false_negatives_1: 1216.0170 - false_positives_1: 1434.2373 - loss: 0.6561 +
``` - -``` -
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9055 - false_negatives: 860.2381 - false_positives: 983.5374 - loss: 0.2482 +Epoch 2: val_loss improved from 0.67428 to 0.59133, saving model to AL_Model.keras -
-``` - + ```
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9054 - false_negatives: 867.3986 - false_positives: 989.9797 - loss: 0.2482 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.6507 - false_negatives_1: 1234.9833 - false_positives_1: 1455.7667 - loss: 0.6558 - val_binary_accuracy: 0.7032 - val_false_negatives_1: 235.0000 - val_false_positives_1: 1249.0000 - val_loss: 0.5913 +
``` - +Epoch 3/20 + ```
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9054 - false_negatives: 874.5571 - false_positives: 996.4496 - loss: 0.2483 + + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.7266 - false_negatives_1: 15.0000 - false_positives_1: 55.0000 - loss: 0.5886
```  ```
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9053 - false_negatives: 881.7200 - false_positives: 1002.9267 - loss: 0.2484 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.6982 - false_negatives_1: 53.0000 - false_positives_1: 66.5000 - loss: 0.6021
``` - + ```
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9053 - false_negatives: 888.8676 - false_positives: 1009.4040 - loss: 0.2485 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.6908 - false_negatives_1: 66.6667 - false_positives_1: 96.0000 - loss: 0.6071
``` - + ```
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9052 - false_negatives: 896.0395 - false_positives: 1015.8224 - loss: 0.2486 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.6875 - false_negatives_1: 88.5000 - false_positives_1: 116.0000 - loss: 0.6089
```  ```
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9052 - false_negatives: 903.1895 - false_positives: 1022.2679 - loss: 0.2487 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.6858 - false_negatives_1: 105.0000 - false_positives_1: 140.8000 - loss: 0.6092
``` - + ```
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9051 - false_negatives: 910.2987 - false_positives: 1028.6753 - loss: 0.2487 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6868 - false_negatives_1: 123.0000 - false_positives_1: 160.6667 - loss: 0.6077
``` - + ```
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9051 - false_negatives: 917.3806 - false_positives: 1035.0903 - loss: 0.2488 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6880 - false_negatives_1: 140.4286 - false_positives_1: 180.7143 - loss: 0.6066
``` - + ```
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9051 - false_negatives: 924.4615 - false_positives: 1041.4744 - loss: 0.2489 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6888 - false_negatives_1: 161.0000 - false_positives_1: 198.2500 - loss: 0.6057 -
``` -Epoch 12: val_loss did not improve from 0.32398 - - + ```
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 76ms/step - binary_accuracy: 0.9050 - false_negatives: 938.3924 - false_positives: 1054.0380 - loss: 0.2490 - val_binary_accuracy: 0.8622 - val_false_negatives: 329.0000 - val_false_positives: 360.0000 - val_loss: 0.3356 - + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6882 - false_negatives_1: 177.5556 - false_positives_1: 222.7778 - loss: 0.6057
``` -Epoch 13/20 - + ```
- - 1/157 ━━━━━━━━━━━━━━━━━━━━ 14s 91ms/step - binary_accuracy: 0.9375 - false_negatives: 11.0000 - false_positives: 5.0000 - loss: 0.1835 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6881 - false_negatives_1: 193.5000 - false_positives_1: 247.0000 - loss: 0.6055
``` - + ```
- 2/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9365 - false_negatives: 14.0000 - false_positives: 10.5000 - loss: 0.1777 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6890 - false_negatives_1: 209.7273 - false_positives_1: 268.0909 - loss: 0.6048
``` - + ```
- 3/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9325 - false_negatives: 17.6667 - false_positives: 18.0000 - loss: 0.1883 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6903 - false_negatives_1: 225.1667 - false_positives_1: 288.3333 - loss: 0.6038
``` - + ```
- 4/157 ━━━━━━━━━━━━━━━━━━━━ 11s 73ms/step - binary_accuracy: 0.9284 - false_negatives: 24.2500 - false_positives: 24.0000 - loss: 0.1973 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6919 - false_negatives_1: 239.3846 - false_positives_1: 308.5385 - loss: 0.6025
``` - + ```
- 5/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9258 - false_negatives: 29.4000 - false_positives: 30.8000 - loss: 0.2032 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6934 - false_negatives_1: 255.7857 - false_positives_1: 326.7143 - loss: 0.6013
``` - + ```
- 6/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9244 - false_negatives: 34.5000 - false_positives: 36.8333 - loss: 0.2073 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6946 - false_negatives_1: 270.6000 - false_positives_1: 346.7333 - loss: 0.6001
``` - + ```
- 7/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9234 - false_negatives: 39.5714 - false_positives: 42.7143 - loss: 0.2101 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6953 - false_negatives_1: 289.8125 - false_positives_1: 364.4375 - loss: 0.5993
``` - + ```
- 8/157 ━━━━━━━━━━━━━━━━━━━━ 11s 74ms/step - binary_accuracy: 0.9231 - false_negatives: 44.1250 - false_positives: 48.1250 - loss: 0.2116 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6957 - false_negatives_1: 306.9412 - false_positives_1: 385.1176 - loss: 0.5987
``` - + ```
- 9/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9231 - false_negatives: 48.4444 - false_positives: 53.3333 - loss: 0.2123 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6959 - false_negatives_1: 322.6111 - false_positives_1: 407.7778 - loss: 0.5983
``` - + ```
- 10/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9233 - false_negatives: 52.4000 - false_positives: 58.2000 - loss: 0.2126 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6962 - false_negatives_1: 337.8947 - false_positives_1: 430.4211 - loss: 0.5979
``` - + ```
- 11/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9234 - false_negatives: 56.0909 - false_positives: 64.0000 - loss: 0.2131 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6965 - false_negatives_1: 353.5500 - false_positives_1: 452.5500 - loss: 0.5975
``` - + ```
- 12/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9235 - false_negatives: 60.4167 - false_positives: 69.0000 - loss: 0.2137 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6968 - false_negatives_1: 369.9048 - false_positives_1: 473.7619 - loss: 0.5972
``` - + ```
- 13/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9234 - false_negatives: 64.4615 - false_positives: 74.8462 - loss: 0.2142 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6971 - false_negatives_1: 385.8182 - false_positives_1: 495.4091 - loss: 0.5969
``` - + ```
- 14/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9232 - false_negatives: 68.6429 - false_positives: 80.8571 - loss: 0.2149 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6975 - false_negatives_1: 401.4348 - false_positives_1: 516.6522 - loss: 0.5966
``` - + ```
- 15/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9230 - false_negatives: 72.7333 - false_positives: 87.4667 - loss: 0.2157 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.6980 - false_negatives_1: 416.8750 - false_positives_1: 537.8333 - loss: 0.5962
``` - + ```
- 16/157 ━━━━━━━━━━━━━━━━━━━━ 10s 74ms/step - binary_accuracy: 0.9228 - false_negatives: 77.0000 - false_positives: 93.5625 - loss: 0.2163 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6984 - false_negatives_1: 432.3200 - false_positives_1: 558.6000 - loss: 0.5958
``` - + ```
- 17/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9226 - false_negatives: 81.3529 - false_positives: 99.8824 - loss: 0.2168 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6989 - false_negatives_1: 447.7692 - false_positives_1: 578.7308 - loss: 0.5954
``` - + ```
- 18/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9223 - false_negatives: 85.3889 - false_positives: 106.7778 - loss: 0.2173 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6995 - false_negatives_1: 463.3333 - false_positives_1: 598.7037 - loss: 0.5950
``` - + ```
- 19/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9221 - false_negatives: 89.8947 - false_positives: 113.1053 - loss: 0.2177 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7000 - false_negatives_1: 478.7500 - false_positives_1: 618.6071 - loss: 0.5945
``` - + ```
- 20/157 ━━━━━━━━━━━━━━━━━━━━ 10s 73ms/step - binary_accuracy: 0.9219 - false_negatives: 94.2000 - false_positives: 119.4500 - loss: 0.2182 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7005 - false_negatives_1: 494.0345 - false_positives_1: 638.4138 - loss: 0.5941
``` - + ```
- 21/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9218 - false_negatives: 98.4762 - false_positives: 125.7619 - loss: 0.2185 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7010 - false_negatives_1: 509.7333 - false_positives_1: 657.5667 - loss: 0.5936
``` - + ```
- 22/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9216 - false_negatives: 102.5909 - false_positives: 132.5455 - loss: 0.2190 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7015 - false_negatives_1: 524.6774 - false_positives_1: 677.8710 - loss: 0.5932
``` - + ```
- 23/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9214 - false_negatives: 107.2609 - false_positives: 138.9565 - loss: 0.2195 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7019 - false_negatives_1: 540.4062 - false_positives_1: 697.2812 - loss: 0.5928
``` - + ```
- 24/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9213 - false_negatives: 111.7083 - false_positives: 145.2500 - loss: 0.2199 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7023 - false_negatives_1: 555.3636 - false_positives_1: 718.2121 - loss: 0.5924
``` - + ```
- 25/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9211 - false_negatives: 116.0400 - false_positives: 151.7200 - loss: 0.2202 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7026 - false_negatives_1: 570.0588 - false_positives_1: 739.0588 - loss: 0.5921
``` - + ```
- 26/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9209 - false_negatives: 120.2692 - false_positives: 158.6154 - loss: 0.2206 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7031 - false_negatives_1: 584.4857 - false_positives_1: 759.4286 - loss: 0.5916
``` - + ```
- 27/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9208 - false_negatives: 124.5185 - false_positives: 165.1852 - loss: 0.2209 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7035 - false_negatives_1: 598.9722 - false_positives_1: 779.8055 - loss: 0.5912
``` - + ```
- 28/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9207 - false_negatives: 128.6429 - false_positives: 171.9286 - loss: 0.2211 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7039 - false_negatives_1: 614.2973 - false_positives_1: 799.4054 - loss: 0.5908
``` - + ```
- 29/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9205 - false_negatives: 133.0345 - false_positives: 178.5517 - loss: 0.2213 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7042 - false_negatives_1: 629.0526 - false_positives_1: 820.0789 - loss: 0.5904
``` - + ```
- 30/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9204 - false_negatives: 137.2667 - false_positives: 185.1667 - loss: 0.2215 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7045 - false_negatives_1: 644.3589 - false_positives_1: 840.1025 - loss: 0.5900
``` - + ```
- 31/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9203 - false_negatives: 141.4839 - false_positives: 191.6452 - loss: 0.2217 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7049 - false_negatives_1: 659.4250 - false_positives_1: 859.8500 - loss: 0.5896
``` - + ```
- 32/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9202 - false_negatives: 145.5312 - false_positives: 198.2188 - loss: 0.2218 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7053 - false_negatives_1: 674.1464 - false_positives_1: 879.9025 - loss: 0.5892
``` - + ```
- 33/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9202 - false_negatives: 149.5152 - false_positives: 204.6970 - loss: 0.2218 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7056 - false_negatives_1: 689.6667 - false_positives_1: 899.2381 - loss: 0.5888
``` - + ```
- 34/157 ━━━━━━━━━━━━━━━━━━━━ 9s 73ms/step - binary_accuracy: 0.9201 - false_negatives: 153.4706 - false_positives: 211.3529 - loss: 0.2218 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7059 - false_negatives_1: 704.5814 - false_positives_1: 919.5582 - loss: 0.5885
``` - + ```
- 35/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9200 - false_negatives: 157.7143 - false_positives: 217.9714 - loss: 0.2219 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7062 - false_negatives_1: 719.3636 - false_positives_1: 939.8864 - loss: 0.5881
``` - + ```
- 36/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9199 - false_negatives: 161.9722 - false_positives: 224.6111 - loss: 0.2221 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7065 - false_negatives_1: 734.1111 - false_positives_1: 960.0000 - loss: 0.5878
``` - + ```
- 37/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9198 - false_negatives: 166.3513 - false_positives: 231.1892 - loss: 0.2222 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7068 - false_negatives_1: 748.8478 - false_positives_1: 979.9565 - loss: 0.5874
``` - + ```
- 38/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9197 - false_negatives: 170.7105 - false_positives: 237.8947 - loss: 0.2223 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7071 - false_negatives_1: 763.5106 - false_positives_1: 999.8085 - loss: 0.5870
``` - + ``` -
- 39/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9196 - false_negatives: 175.2308 - false_positives: 244.4872 - loss: 0.2224 - -
-``` - -``` -
- 40/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9195 - false_negatives: 179.6500 - false_positives: 251.3500 - loss: 0.2226 - -
-``` - -``` -
- 41/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9194 - false_negatives: 184.2439 - false_positives: 258.2195 - loss: 0.2227 - -
-``` - -``` -
- 42/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9193 - false_negatives: 188.7619 - false_positives: 265.0476 - loss: 0.2228 - -
-``` - -``` -
- 43/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9192 - false_negatives: 193.2791 - false_positives: 271.7209 - loss: 0.2229 - -
-``` - -``` -
- 44/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9191 - false_negatives: 197.9091 - false_positives: 278.2500 - loss: 0.2230 - -
-``` - -``` -
- 45/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9190 - false_negatives: 202.4444 - false_positives: 284.8222 - loss: 0.2231 - -
-``` - -``` -
- 46/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9189 - false_negatives: 207.3044 - false_positives: 291.2174 - loss: 0.2232 - -
-``` - -``` -
- 47/157 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9188 - false_negatives: 212.0000 - false_positives: 297.8511 - loss: 0.2233 - -
-``` - -``` -
- 48/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9187 - false_negatives: 216.7917 - false_positives: 304.3750 - loss: 0.2234 - -
-``` - -``` -
- 49/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9186 - false_negatives: 221.4694 - false_positives: 311.1633 - loss: 0.2235 - -
-``` - -``` -
- 50/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9185 - false_negatives: 226.2200 - false_positives: 317.8800 - loss: 0.2236 - -
-``` - -``` -
- 51/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9184 - false_negatives: 231.0392 - false_positives: 324.5098 - loss: 0.2238 - -
-``` - -``` -
- 52/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9183 - false_negatives: 235.8462 - false_positives: 331.1731 - loss: 0.2239 - -
-``` - -``` -
- 53/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9182 - false_negatives: 240.7547 - false_positives: 337.7547 - loss: 0.2240 - -
-``` - -``` -
- 54/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9181 - false_negatives: 245.6667 - false_positives: 344.4074 - loss: 0.2242 - -
-``` - -``` -
- 55/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9180 - false_negatives: 250.6727 - false_positives: 351.1636 - loss: 0.2243 - -
-``` - -``` -
- 56/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9179 - false_negatives: 255.8214 - false_positives: 357.8393 - loss: 0.2244 - -
-``` - -``` -
- 57/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9178 - false_negatives: 260.9123 - false_positives: 364.6491 - loss: 0.2246 - -
-``` - -``` -
- 58/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9177 - false_negatives: 266.2242 - false_positives: 371.3621 - loss: 0.2247 - -
-``` - -``` -
- 59/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9175 - false_negatives: 271.4237 - false_positives: 378.4576 - loss: 0.2249 - -
-``` - -``` -
- 60/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9174 - false_negatives: 276.7833 - false_positives: 385.5167 - loss: 0.2251 - -
-``` - -``` -
- 61/157 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9173 - false_negatives: 282.1147 - false_positives: 392.5738 - loss: 0.2252 - -
-``` - -``` -
- 62/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9171 - false_negatives: 287.3871 - false_positives: 399.7258 - loss: 0.2254 - -
-``` - -``` -
- 63/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9170 - false_negatives: 292.7143 - false_positives: 406.7619 - loss: 0.2256 - -
-``` - -``` -
- 64/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9169 - false_negatives: 298.0469 - false_positives: 413.7812 - loss: 0.2257 - -
-``` - -``` -
- 65/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9168 - false_negatives: 303.4769 - false_positives: 420.7231 - loss: 0.2259 - -
-``` - -``` -
- 66/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9166 - false_negatives: 308.8788 - false_positives: 427.5757 - loss: 0.2260 - -
-``` - -``` -
- 67/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9165 - false_negatives: 314.3284 - false_positives: 434.4179 - loss: 0.2262 - -
-``` - -``` -
- 68/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9164 - false_negatives: 319.7500 - false_positives: 441.2059 - loss: 0.2263 - -
-``` - -``` -
- 69/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9163 - false_negatives: 325.0869 - false_positives: 447.9855 - loss: 0.2265 - -
-``` - -``` -
- 70/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9162 - false_negatives: 330.5286 - false_positives: 454.7000 - loss: 0.2266 - -
-``` - -``` -
- 71/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9161 - false_negatives: 336.0704 - false_positives: 461.4225 - loss: 0.2267 - -
-``` - -``` -
- 72/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9160 - false_negatives: 341.5555 - false_positives: 468.2500 - loss: 0.2269 - -
-``` - -``` -
- 73/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9159 - false_negatives: 347.1370 - false_positives: 474.9726 - loss: 0.2270 - -
-``` - -``` -
- 74/157 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9158 - false_negatives: 352.7162 - false_positives: 481.7973 - loss: 0.2272 - -
-``` - -``` -
- 75/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9157 - false_negatives: 358.4000 - false_positives: 488.6133 - loss: 0.2273 - -
-``` - -``` -
- 76/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9156 - false_negatives: 364.1974 - false_positives: 495.4342 - loss: 0.2275 - -
-``` - -``` -
- 77/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9155 - false_negatives: 370.0260 - false_positives: 502.1948 - loss: 0.2276 - -
-``` - -``` -
- 78/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9154 - false_negatives: 375.8974 - false_positives: 508.9744 - loss: 0.2278 - -
-``` - -``` -
- 79/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9153 - false_negatives: 381.7342 - false_positives: 515.7342 - loss: 0.2280 - -
-``` - -``` -
- 80/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9152 - false_negatives: 387.6000 - false_positives: 522.4875 - loss: 0.2281 - -
-``` - -``` -
- 81/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9151 - false_negatives: 393.5062 - false_positives: 529.1729 - loss: 0.2283 - -
-``` - -``` -
- 82/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9150 - false_negatives: 399.4024 - false_positives: 535.8049 - loss: 0.2284 - -
-``` - -``` -
- 83/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9149 - false_negatives: 405.3253 - false_positives: 542.3253 - loss: 0.2285 - -
-``` - -``` -
- 84/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9148 - false_negatives: 411.2262 - false_positives: 548.8571 - loss: 0.2287 - -
-``` - -``` -
- 85/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9147 - false_negatives: 417.1059 - false_positives: 555.3530 - loss: 0.2288 - -
-``` - -``` -
- 86/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9146 - false_negatives: 422.9767 - false_positives: 561.8721 - loss: 0.2289 - -
-``` - -``` -
- 87/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9145 - false_negatives: 428.8506 - false_positives: 568.3563 - loss: 0.2290 - -
-``` - -``` -
- 88/157 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9144 - false_negatives: 434.6818 - false_positives: 574.9318 - loss: 0.2292 - -
-``` - -``` -
- 89/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9144 - false_negatives: 440.5618 - false_positives: 581.4045 - loss: 0.2293 - -
-``` - -``` -
- 90/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9143 - false_negatives: 446.4111 - false_positives: 587.9556 - loss: 0.2294 - -
-``` - -``` -
- 91/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9142 - false_negatives: 452.2857 - false_positives: 594.4396 - loss: 0.2295 - -
-``` - -``` -
- 92/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9141 - false_negatives: 458.1522 - false_positives: 600.9783 - loss: 0.2296 - -
-``` - -``` -
- 93/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9141 - false_negatives: 464.0860 - false_positives: 607.4194 - loss: 0.2298 - -
-``` - -``` -
- 94/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9140 - false_negatives: 470.0000 - false_positives: 613.8830 - loss: 0.2299 - -
-``` - -``` -
- 95/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9139 - false_negatives: 476.0526 - false_positives: 620.2947 - loss: 0.2300 - -
-``` - -``` -
- 96/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9138 - false_negatives: 482.0729 - false_positives: 626.7917 - loss: 0.2301 - -
-``` - -``` -
- 97/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9138 - false_negatives: 488.2268 - false_positives: 633.2165 - loss: 0.2303 - -
-``` - -``` -
- 98/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9137 - false_negatives: 494.3061 - false_positives: 639.7857 - loss: 0.2304 - -
-``` - -``` -
- 99/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9136 - false_negatives: 500.5454 - false_positives: 646.2828 - loss: 0.2305 - -
-``` - -``` -
- 100/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9135 - false_negatives: 506.7400 - false_positives: 652.8600 - loss: 0.2307 - -
-``` - -``` -
- 101/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9134 - false_negatives: 512.9703 - false_positives: 659.3366 - loss: 0.2308 - -
-``` - -``` -
- 102/157 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9133 - false_negatives: 519.2353 - false_positives: 665.8726 - loss: 0.2309 - -
-``` - -``` -
- 103/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9133 - false_negatives: 525.5146 - false_positives: 672.4175 - loss: 0.2311 - -
-``` - -``` -
- 104/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9132 - false_negatives: 531.8558 - false_positives: 678.9231 - loss: 0.2312 - -
-``` - -``` -
- 105/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9131 - false_negatives: 538.1524 - false_positives: 685.4952 - loss: 0.2313 - -
-``` - -``` -
- 106/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9130 - false_negatives: 544.5377 - false_positives: 691.9434 - loss: 0.2315 - -
-``` - -``` -
- 107/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9129 - false_negatives: 550.8598 - false_positives: 698.4486 - loss: 0.2316 - -
-``` - -``` -
- 108/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9129 - false_negatives: 557.1852 - false_positives: 704.9352 - loss: 0.2317 - -
-``` - -``` -
- 109/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9128 - false_negatives: 563.4954 - false_positives: 711.4037 - loss: 0.2319 - -
-``` - -``` -
- 110/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9127 - false_negatives: 569.8273 - false_positives: 717.8273 - loss: 0.2320 - -
-``` - -``` -
- 111/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9127 - false_negatives: 576.1442 - false_positives: 724.1802 - loss: 0.2321 - -
-``` - -``` -
- 112/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9126 - false_negatives: 582.3929 - false_positives: 730.6964 - loss: 0.2322 - -
-``` - -``` -
- 113/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9125 - false_negatives: 588.7699 - false_positives: 737.1239 - loss: 0.2323 - -
-``` - -``` -
- 114/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9124 - false_negatives: 595.1491 - false_positives: 743.5614 - loss: 0.2325 - -
-``` - -``` -
- 115/157 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9124 - false_negatives: 601.5391 - false_positives: 749.9652 - loss: 0.2326 - -
-``` - -``` -
- 116/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9123 - false_negatives: 607.9224 - false_positives: 756.3879 - loss: 0.2327 - -
-``` - -``` -
- 117/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9122 - false_negatives: 614.2906 - false_positives: 762.8376 - loss: 0.2328 - -
-``` - -``` -
- 118/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9122 - false_negatives: 620.6780 - false_positives: 769.2627 - loss: 0.2329 - -
-``` - -``` -
- 119/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives: 627.0756 - false_positives: 775.6470 - loss: 0.2331 - -
-``` - -``` -
- 120/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 633.4333 - false_positives: 782.0667 - loss: 0.2332 - -
-``` - -``` -
- 121/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives: 639.8430 - false_positives: 788.4050 - loss: 0.2333 - -
-``` - -``` -
- 122/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 646.2459 - false_positives: 794.8115 - loss: 0.2334 - -
-``` - -``` -
- 123/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9119 - false_negatives: 652.6585 - false_positives: 801.1707 - loss: 0.2335 - -
-``` - -``` -
- 124/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9118 - false_negatives: 659.0242 - false_positives: 807.5323 - loss: 0.2336 - -
-``` - -``` -
- 125/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 665.4000 - false_positives: 813.9280 - loss: 0.2337 - -
-``` - -``` -
- 126/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9117 - false_negatives: 671.7778 - false_positives: 820.3095 - loss: 0.2339 - -
-``` - -``` -
- 127/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 678.1417 - false_positives: 826.7402 - loss: 0.2340 - -
-``` - -``` -
- 128/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9116 - false_negatives: 684.5156 - false_positives: 833.0938 - loss: 0.2341 - -
-``` - -``` -
- 129/157 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9115 - false_negatives: 690.9457 - false_positives: 839.4573 - loss: 0.2342 - -
-``` - -``` -
- 130/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9114 - false_negatives: 697.3307 - false_positives: 845.8846 - loss: 0.2343 - -
-``` - -``` -
- 131/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9114 - false_negatives: 703.7786 - false_positives: 852.2595 - loss: 0.2344 - -
-``` - -``` -
- 132/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 710.2121 - false_positives: 858.6818 - loss: 0.2345 - -
-``` - -``` -
- 133/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9113 - false_negatives: 716.6692 - false_positives: 865.0902 - loss: 0.2346 - -
-``` - -``` -
- 134/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9112 - false_negatives: 723.1194 - false_positives: 871.4702 - loss: 0.2347 - -
-``` - -``` -
- 135/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9112 - false_negatives: 729.5852 - false_positives: 877.8666 - loss: 0.2348 - -
-``` - -``` -
- 136/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9111 - false_negatives: 736.0073 - false_positives: 884.3015 - loss: 0.2349 - -
-``` - -``` -
- 137/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9111 - false_negatives: 742.4891 - false_positives: 890.7080 - loss: 0.2350 - -
-``` - -``` -
- 138/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9110 - false_negatives: 748.9420 - false_positives: 897.1232 - loss: 0.2351 - -
-``` - -``` -
- 139/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 755.3957 - false_positives: 903.5036 - loss: 0.2352 - -
-``` - -``` -
- 140/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9109 - false_negatives: 761.7928 - false_positives: 909.8857 - loss: 0.2353 - -
-``` - -``` -
- 141/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives: 768.2553 - false_positives: 916.2482 - loss: 0.2354 - -
-``` - -``` -
- 142/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives: 774.6409 - false_positives: 922.6972 - loss: 0.2355 - -
-``` - -``` -
- 143/157 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives: 781.1469 - false_positives: 929.0979 - loss: 0.2356 - -
-``` - -``` -
- 144/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives: 787.6042 - false_positives: 935.5417 - loss: 0.2357 - -
-``` - -``` -
- 145/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9106 - false_negatives: 794.0552 - false_positives: 941.9586 - loss: 0.2359 - -
-``` - -``` -
- 146/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9106 - false_negatives: 800.5068 - false_positives: 948.3630 - loss: 0.2359 - -
-``` - -``` -
- 147/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9105 - false_negatives: 806.9660 - false_positives: 954.7551 - loss: 0.2360 - -
-``` - -``` -
- 148/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9105 - false_negatives: 813.4797 - false_positives: 961.1216 - loss: 0.2361 - -
-``` - -``` -
- 149/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9104 - false_negatives: 819.9664 - false_positives: 967.4631 - loss: 0.2362 - -
-``` - -``` -
- 150/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9104 - false_negatives: 826.4467 - false_positives: 973.7933 - loss: 0.2363 - -
-``` - -``` -
- 151/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9103 - false_negatives: 832.9205 - false_positives: 980.1126 - loss: 0.2364 - -
-``` - -``` -
- 152/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9103 - false_negatives: 839.4408 - false_positives: 986.4408 - loss: 0.2365 - -
-``` - -``` -
- 153/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9102 - false_negatives: 845.9346 - false_positives: 992.8170 - loss: 0.2366 - -
-``` - -``` -
- 154/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9102 - false_negatives: 852.4481 - false_positives: 999.1754 - loss: 0.2367 - -
-``` - -``` -
- 155/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9102 - false_negatives: 858.9613 - false_positives: 1005.5161 - loss: 0.2368 - -
-``` - -``` -
- 156/157 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9101 - false_negatives: 865.4167 - false_positives: 1011.8975 - loss: 0.2369 - - -
-``` -Epoch 13: val_loss did not improve from 0.32398 - - -``` -
- 157/157 ━━━━━━━━━━━━━━━━━━━━ 12s 77ms/step - binary_accuracy: 0.9100 - false_negatives: 878.1709 - false_positives: 1024.4177 - loss: 0.2370 - val_binary_accuracy: 0.8612 - val_false_negatives: 254.0000 - val_false_positives: 440.0000 - val_loss: 0.3322 - - -
-``` -Epoch 13: early stopping - -``` -
- -![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_15_2073.png) - - - - - -![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_15_2074.png) - - - -
-``` ----------------------------------------------------------------------------------------------------- - -Test set evaluation: {'binary_accuracy': 0.8587999939918518, 'false_negatives': 297.0, 'false_positives': 409.0, 'loss': 0.32773780822753906} ----------------------------------------------------------------------------------------------------- - -``` -
---- -## Training via Active Learning - -The general process we follow when performing Active Learning is demonstrated below: - -![Active Learning](https://i.imgur.com/dmNKusp.png) - -The pipeline can be summarized in five parts: - -1. Sample and annotate a small, balanced training dataset -2. Train the model on this small subset -3. Evaluate the model on a balanced testing set -4. If the model satisfies the business criteria, deploy it in a real time setting -5. If it doesn't pass the criteria, sample a few more samples according to the ratio of -false positives and negatives, add them to the training set and repeat from step 2 till -the model passes the tests or till all available data is exhausted. - -For the code below, we will perform sampling using the following formula:
- -![Ratio Sampling](https://i.imgur.com/LyZEiZL.png) - -Active Learning techniques use callbacks extensively for progress tracking. We will be -using model checkpointing and early stopping for this example. The `patience` parameter -for Early Stopping can help minimize overfitting and the time required. We have set it -`patience=4` for now but since the model is robust, we can increase the patience level if -desired. - -Note: We are not loading the checkpoint after the first training iteration. In my -experience working on Active Learning techniques, this helps the model probe the -newly formed loss landscape. Even if the model fails to improve in the second iteration, -we will still gain insight about the possible future false positive and negative rates. -This will help us sample a better set in the next iteration where the model will have a -greater chance to improve. - - -```python - -def train_active_learning_models( - train_dataset, - pool_negatives, - pool_positives, - val_dataset, - test_dataset, - num_iterations=3, - sampling_size=5000, -): - - # Creating lists for storing metrics - losses, val_losses, accuracies, val_accuracies = [], [], [], [] - - model = create_model() - # We will monitor the false positives and false negatives predicted by our model - # These will decide the subsequent sampling ratio for every Active Learning loop - model.compile( - loss="binary_crossentropy", - optimizer="rmsprop", - metrics=[ - keras.metrics.BinaryAccuracy(), - keras.metrics.FalseNegatives(), - keras.metrics.FalsePositives(), - ], - ) - - # Defining checkpoints. - # The checkpoint callback is reused throughout the training since it only saves the best overall model. - checkpoint = keras.callbacks.ModelCheckpoint( - "AL_Model.keras", save_best_only=True, verbose=1 - ) - # Here, patience is set to 4. This can be set higher if desired. - early_stopping = keras.callbacks.EarlyStopping(patience=4, verbose=1) - - print(f"Starting to train with {len(train_dataset)} samples") - # Initial fit with a small subset of the training set - history = model.fit( - train_dataset.cache().shuffle(20000).batch(256), - epochs=20, - validation_data=val_dataset, - callbacks=[checkpoint, early_stopping], - ) - - # Appending history - losses, val_losses, accuracies, val_accuracies = append_history( - losses, val_losses, accuracies, val_accuracies, history - ) - - for iteration in range(num_iterations): - # Getting predictions from previously trained model - predictions = model.predict(test_dataset) - - # Generating labels from the output probabilities - rounded = ops.where(ops.greater(predictions, 0.5), 1, 0) - - # Evaluating the number of zeros and ones incorrrectly classified - _, _, false_negatives, false_positives = model.evaluate(test_dataset, verbose=0) - - print("-" * 100) - print( - f"Number of zeros incorrectly classified: {false_negatives}, Number of ones incorrectly classified: {false_positives}" - ) - - # This technique of Active Learning demonstrates ratio based sampling where - # Number of ones/zeros to sample = Number of ones/zeros incorrectly classified / Total incorrectly classified - if false_negatives != 0 and false_positives != 0: - total = false_negatives + false_positives - sample_ratio_ones, sample_ratio_zeros = ( - false_positives / total, - false_negatives / total, - ) - # In the case where all samples are correctly predicted, we can sample both classes equally - else: - sample_ratio_ones, sample_ratio_zeros = 0.5, 0.5 - - print( - f"Sample ratio for positives: {sample_ratio_ones}, Sample ratio for negatives:{sample_ratio_zeros}" - ) - - # Sample the required number of ones and zeros - sampled_dataset = pool_negatives.take( - int(sample_ratio_zeros * sampling_size) - ).concatenate(pool_positives.take(int(sample_ratio_ones * sampling_size))) - - # Skip the sampled data points to avoid repetition of sample - pool_negatives = pool_negatives.skip(int(sample_ratio_zeros * sampling_size)) - pool_positives = pool_positives.skip(int(sample_ratio_ones * sampling_size)) - - # Concatenating the train_dataset with the sampled_dataset - train_dataset = train_dataset.concatenate(sampled_dataset).prefetch( - tf.data.AUTOTUNE - ) - - print(f"Starting training with {len(train_dataset)} samples") - print("-" * 100) - - # We recompile the model to reset the optimizer states and retrain the model - model.compile( - loss="binary_crossentropy", - optimizer="rmsprop", - metrics=[ - keras.metrics.BinaryAccuracy(), - keras.metrics.FalseNegatives(), - keras.metrics.FalsePositives(), - ], - ) - history = model.fit( - train_dataset.cache().shuffle(20000).batch(256), - validation_data=val_dataset, - epochs=20, - callbacks=[ - checkpoint, - keras.callbacks.EarlyStopping(patience=4, verbose=1), - ], - ) - - # Appending the history - losses, val_losses, accuracies, val_accuracies = append_history( - losses, val_losses, accuracies, val_accuracies, history - ) - - # Loading the best model from this training loop - model = keras.models.load_model("AL_Model.keras") - - # Plotting the overall history and evaluating the final model - plot_history(losses, val_losses, accuracies, val_accuracies) - print("-" * 100) - print( - "Test set evaluation: ", - model.evaluate(test_dataset, verbose=0, return_dict=True), - ) - print("-" * 100) - - return model - - -active_learning_model = train_active_learning_models( - train_dataset, pool_negatives, pool_positives, val_dataset, test_dataset -) -``` - - -
Model: "sequential_1"
-
- - - - -
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
-┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
-┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
-│ embedding_1 (Embedding)         │ (None, 150, 128)       │       384,000 │
-├─────────────────────────────────┼────────────────────────┼───────────────┤
-│ bidirectional_1 (Bidirectional) │ (None, 150, 64)        │        41,216 │
-├─────────────────────────────────┼────────────────────────┼───────────────┤
-│ global_max_pooling1d_1          │ (None, 64)             │             0 │
-│ (GlobalMaxPooling1D)            │                        │               │
-├─────────────────────────────────┼────────────────────────┼───────────────┤
-│ dense_2 (Dense)                 │ (None, 20)             │         1,300 │
-├─────────────────────────────────┼────────────────────────┼───────────────┤
-│ dropout_1 (Dropout)             │ (None, 20)             │             0 │
-├─────────────────────────────────┼────────────────────────┼───────────────┤
-│ dense_3 (Dense)                 │ (None, 1)              │            21 │
-└─────────────────────────────────┴────────────────────────┴───────────────┘
-
+ + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7074 - false_negatives_1: 778.5208 - false_positives_1: 1019.0417 - loss: 0.5866 +
+``` + +``` +
+ 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7077 - false_negatives_1: 793.0204 - false_positives_1: 1039.3877 - loss: 0.5863 +
+``` + +``` +
+ 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7080 - false_negatives_1: 807.9600 - false_positives_1: 1059.2800 - loss: 0.5860 +
+``` + +``` +
+ 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7082 - false_negatives_1: 822.6667 - false_positives_1: 1079.2354 - loss: 0.5856 -
 Total params: 426,537 (1.63 MB)
-
+
+``` + +``` +
+ 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7085 - false_negatives_1: 837.2308 - false_positives_1: 1099.0000 - loss: 0.5853 +
+``` + +``` +
+ 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7088 - false_negatives_1: 851.9623 - false_positives_1: 1118.3773 - loss: 0.5849 +
+``` + +``` +
+ 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7091 - false_negatives_1: 866.7407 - false_positives_1: 1137.5927 - loss: 0.5846 +
+``` + +``` +
+ 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7094 - false_negatives_1: 881.2364 - false_positives_1: 1156.9454 - loss: 0.5842 -
 Trainable params: 426,537 (1.63 MB)
-
+
+``` + +``` +
+ 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7097 - false_negatives_1: 896.4107 - false_positives_1: 1175.6608 - loss: 0.5838 +
+``` + +``` +
+ 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7099 - false_negatives_1: 911.1228 - false_positives_1: 1195.5088 - loss: 0.5835 +
+``` + +``` +
+ 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7101 - false_negatives_1: 925.5345 - false_positives_1: 1215.8103 - loss: 0.5832 +
+``` + +``` +
+ 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7103 - false_negatives_1: 939.5255 - false_positives_1: 1235.8983 - loss: 0.5829 -
 Non-trainable params: 0 (0.00 B)
-
+ +
+``` +Epoch 3: val_loss improved from 0.59133 to 0.51602, saving model to AL_Model.keras + +``` +
+ 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.7106 - false_negatives_1: 953.0500 - false_positives_1: 1255.3167 - loss: 0.5827 - val_binary_accuracy: 0.7686 - val_false_negatives_1: 812.0000 - val_false_positives_1: 345.0000 - val_loss: 0.5160
``` -Starting to train with 15000 samples -Epoch 1/20 +Epoch 4/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 2:27 3s/step - binary_accuracy: 0.5078 - false_negatives_1: 91.0000 - false_positives_1: 35.0000 - loss: 0.6934 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 85ms/step - binary_accuracy: 0.7227 - false_negatives_1: 50.0000 - false_positives_1: 21.0000 - loss: 0.5611
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.5107 - false_negatives_1: 145.0000 - false_positives_1: 42.5000 - loss: 0.6930 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.7266 - false_negatives_1: 58.5000 - false_positives_1: 46.0000 - loss: 0.5532
``` - + ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.5106 - false_negatives_1: 202.3333 - false_positives_1: 48.0000 - loss: 0.6931 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.7335 - false_negatives_1: 68.6667 - false_positives_1: 65.6667 - loss: 0.5442
``` - + ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5131 - false_negatives_1: 255.0000 - false_positives_1: 55.5000 - loss: 0.6928 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7384 - false_negatives_1: 82.0000 - false_positives_1: 82.0000 - loss: 0.5374
``` - + ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5144 - false_negatives_1: 310.6000 - false_positives_1: 60.8000 - loss: 0.6926 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7410 - false_negatives_1: 94.4000 - false_positives_1: 100.4000 - loss: 0.5330
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5135 - false_negatives_1: 368.8333 - false_positives_1: 66.3333 - loss: 0.6926 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7426 - false_negatives_1: 111.5000 - false_positives_1: 114.6667 - loss: 0.5304
``` - + ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5135 - false_negatives_1: 421.1429 - false_positives_1: 76.4286 - loss: 0.6926 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7439 - false_negatives_1: 126.0000 - false_positives_1: 131.4286 - loss: 0.5290
``` - + ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5129 - false_negatives_1: 473.0000 - false_positives_1: 88.1250 - loss: 0.6926 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7445 - false_negatives_1: 140.6250 - false_positives_1: 149.0000 - loss: 0.5283
``` - + ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5126 - false_negatives_1: 520.4445 - false_positives_1: 103.6667 - loss: 0.6926 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7457 - false_negatives_1: 153.5556 - false_positives_1: 166.4444 - loss: 0.5270
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5127 - false_negatives_1: 567.7000 - false_positives_1: 118.6000 - loss: 0.6925 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7461 - false_negatives_1: 170.9000 - false_positives_1: 181.2000 - loss: 0.5266
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5129 - false_negatives_1: 614.7273 - false_positives_1: 133.2727 - loss: 0.6925 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7458 - false_negatives_1: 185.1818 - false_positives_1: 200.8182 - loss: 0.5274
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5132 - false_negatives_1: 662.7500 - false_positives_1: 146.8333 - loss: 0.6925 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7457 - false_negatives_1: 198.2500 - false_positives_1: 220.9167 - loss: 0.5278
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5134 - false_negatives_1: 711.1539 - false_positives_1: 160.0000 - loss: 0.6924 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7459 - false_negatives_1: 210.8462 - false_positives_1: 240.6923 - loss: 0.5280
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.5137 - false_negatives_1: 760.0714 - false_positives_1: 172.2857 - loss: 0.6924 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7463 - false_negatives_1: 223.5714 - false_positives_1: 259.2143 - loss: 0.5280
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.5141 - false_negatives_1: 809.9333 - false_positives_1: 183.4000 - loss: 0.6923 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7466 - false_negatives_1: 235.4667 - false_positives_1: 279.0000 - loss: 0.5280
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.5145 - false_negatives_1: 860.3125 - false_positives_1: 193.5000 - loss: 0.6923 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7469 - false_negatives_1: 247.8750 - false_positives_1: 297.8125 - loss: 0.5278
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.5148 - false_negatives_1: 911.5883 - false_positives_1: 203.1765 - loss: 0.6922 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7475 - false_negatives_1: 260.1765 - false_positives_1: 315.9412 - loss: 0.5273
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5152 - false_negatives_1: 962.3333 - false_positives_1: 212.9444 - loss: 0.6922 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7480 - false_negatives_1: 273.0000 - false_positives_1: 333.2222 - loss: 0.5267
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5155 - false_negatives_1: 1013.4737 - false_positives_1: 222.6316 - loss: 0.6921 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7484 - false_negatives_1: 286.2632 - false_positives_1: 350.4211 - loss: 0.5263
``` - + ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5159 - false_negatives_1: 1062.8000 - false_positives_1: 233.6500 - loss: 0.6921 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7489 - false_negatives_1: 298.7500 - false_positives_1: 368.4000 - loss: 0.5258
``` - + ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.5164 - false_negatives_1: 1109.0476 - false_positives_1: 246.9048 - loss: 0.6920 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7490 - false_negatives_1: 313.7143 - false_positives_1: 384.9524 - loss: 0.5257
``` - + ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5168 - false_negatives_1: 1151.9091 - false_positives_1: 263.8182 - loss: 0.6920 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7489 - false_negatives_1: 327.3636 - false_positives_1: 404.5000 - loss: 0.5260
``` - + ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5173 - false_negatives_1: 1192.5217 - false_positives_1: 282.1739 - loss: 0.6919 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7487 - false_negatives_1: 339.9565 - false_positives_1: 425.4348 - loss: 0.5264
``` - + ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5179 - false_negatives_1: 1230.6666 - false_positives_1: 302.9583 - loss: 0.6919 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7486 - false_negatives_1: 352.1250 - false_positives_1: 446.4583 - loss: 0.5267
``` - + ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5183 - false_negatives_1: 1267.0400 - false_positives_1: 325.6800 - loss: 0.6918 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7486 - false_negatives_1: 364.3600 - false_positives_1: 466.8000 - loss: 0.5270
``` - + ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5189 - false_negatives_1: 1302.4231 - false_positives_1: 348.8462 - loss: 0.6918 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7486 - false_negatives_1: 376.1923 - false_positives_1: 486.9615 - loss: 0.5271
``` - + ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5194 - false_negatives_1: 1337.1111 - false_positives_1: 372.2592 - loss: 0.6917 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7487 - false_negatives_1: 388.2592 - false_positives_1: 506.6296 - loss: 0.5272
``` - + ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5199 - false_negatives_1: 1372.5358 - false_positives_1: 395.6429 - loss: 0.6917 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7489 - false_negatives_1: 399.7857 - false_positives_1: 526.4286 - loss: 0.5272
``` - + ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5203 - false_negatives_1: 1406.9656 - false_positives_1: 419.7242 - loss: 0.6916 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7490 - false_negatives_1: 411.5862 - false_positives_1: 545.7586 - loss: 0.5272
``` - + ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5208 - false_negatives_1: 1442.2000 - false_positives_1: 442.6000 - loss: 0.6916 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7492 - false_negatives_1: 423.7000 - false_positives_1: 565.0000 - loss: 0.5272
``` - + ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.5213 - false_negatives_1: 1477.8387 - false_positives_1: 465.0000 - loss: 0.6915 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7494 - false_negatives_1: 435.8387 - false_positives_1: 583.7097 - loss: 0.5271
``` - + ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5218 - false_negatives_1: 1512.4688 - false_positives_1: 487.9688 - loss: 0.6915 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7496 - false_negatives_1: 448.3125 - false_positives_1: 601.9062 - loss: 0.5270
``` - + ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5223 - false_negatives_1: 1546.6364 - false_positives_1: 511.2727 - loss: 0.6914 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7497 - false_negatives_1: 460.7879 - false_positives_1: 620.6970 - loss: 0.5270
``` - + ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5229 - false_negatives_1: 1580.4412 - false_positives_1: 534.5294 - loss: 0.6914 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7498 - false_negatives_1: 473.4706 - false_positives_1: 639.0588 - loss: 0.5269
``` - + ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5234 - false_negatives_1: 1613.3715 - false_positives_1: 558.3428 - loss: 0.6913 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7500 - false_negatives_1: 486.1143 - false_positives_1: 657.3143 - loss: 0.5268
``` - + ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5240 - false_negatives_1: 1646.2778 - false_positives_1: 582.2500 - loss: 0.6912 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7501 - false_negatives_1: 498.9445 - false_positives_1: 675.3889 - loss: 0.5267
``` - + ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5245 - false_negatives_1: 1678.5946 - false_positives_1: 606.6216 - loss: 0.6912 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7503 - false_negatives_1: 511.4865 - false_positives_1: 693.5135 - loss: 0.5266
``` - + ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5250 - false_negatives_1: 1709.6052 - false_positives_1: 631.7368 - loss: 0.6911 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7505 - false_negatives_1: 524.2105 - false_positives_1: 711.1316 - loss: 0.5263
``` - + ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5256 - false_negatives_1: 1739.8718 - false_positives_1: 657.2820 - loss: 0.6911 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7507 - false_negatives_1: 536.5385 - false_positives_1: 729.0000 - loss: 0.5261
``` - + ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5261 - false_negatives_1: 1769.7500 - false_positives_1: 683.6500 - loss: 0.6910 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7509 - false_negatives_1: 549.3500 - false_positives_1: 746.3250 - loss: 0.5259
``` - + ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5266 - false_negatives_1: 1799.4878 - false_positives_1: 710.0244 - loss: 0.6909 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7511 - false_negatives_1: 561.7317 - false_positives_1: 764.2195 - loss: 0.5257
``` - + ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5272 - false_negatives_1: 1829.0000 - false_positives_1: 736.2143 - loss: 0.6909 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7512 - false_negatives_1: 574.2619 - false_positives_1: 781.8333 - loss: 0.5255
``` - + ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5277 - false_negatives_1: 1857.5349 - false_positives_1: 763.2558 - loss: 0.6908 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7515 - false_negatives_1: 586.4651 - false_positives_1: 799.4186 - loss: 0.5252
``` - + ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5282 - false_negatives_1: 1885.7273 - false_positives_1: 790.3636 - loss: 0.6908 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7517 - false_negatives_1: 598.7045 - false_positives_1: 816.7500 - loss: 0.5250
``` - + ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.5288 - false_negatives_1: 1913.6222 - false_positives_1: 817.4000 - loss: 0.6907 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7519 - false_negatives_1: 610.9111 - false_positives_1: 833.8666 - loss: 0.5247
``` - + ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5293 - false_negatives_1: 1941.9783 - false_positives_1: 844.3478 - loss: 0.6906 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7522 - false_negatives_1: 623.3261 - false_positives_1: 850.6087 - loss: 0.5244
``` - + ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5298 - false_negatives_1: 1969.7446 - false_positives_1: 871.3617 - loss: 0.6905 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7524 - false_negatives_1: 635.6383 - false_positives_1: 867.5106 - loss: 0.5241
``` - + ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5304 - false_negatives_1: 1996.7709 - false_positives_1: 898.7708 - loss: 0.6905 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7527 - false_negatives_1: 648.4375 - false_positives_1: 883.8750 - loss: 0.5238
``` - + ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5309 - false_negatives_1: 2023.6938 - false_positives_1: 926.1021 - loss: 0.6904 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7529 - false_negatives_1: 660.7347 - false_positives_1: 901.0816 - loss: 0.5235
``` - + ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5315 - false_negatives_1: 2050.2000 - false_positives_1: 953.5200 - loss: 0.6903 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7530 - false_negatives_1: 674.2000 - false_positives_1: 917.6600 - loss: 0.5233
``` - + ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5320 - false_negatives_1: 2076.5293 - false_positives_1: 980.9412 - loss: 0.6902 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7532 - false_negatives_1: 687.1961 - false_positives_1: 934.8039 - loss: 0.5231
``` - + ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5326 - false_negatives_1: 2102.9038 - false_positives_1: 1008.0769 - loss: 0.6902 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7533 - false_negatives_1: 700.0385 - false_positives_1: 951.9231 - loss: 0.5230
``` - + ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5332 - false_negatives_1: 2129.1699 - false_positives_1: 1035.0754 - loss: 0.6901 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7535 - false_negatives_1: 712.6604 - false_positives_1: 969.2075 - loss: 0.5228
``` - + ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5337 - false_negatives_1: 2154.8704 - false_positives_1: 1062.6111 - loss: 0.6900 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7536 - false_negatives_1: 725.2407 - false_positives_1: 986.2963 - loss: 0.5226
``` - + ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5343 - false_negatives_1: 2180.3274 - false_positives_1: 1090.4728 - loss: 0.6899 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7538 - false_negatives_1: 737.8182 - false_positives_1: 1003.2182 - loss: 0.5224
``` - + ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5348 - false_negatives_1: 2205.4644 - false_positives_1: 1118.3572 - loss: 0.6898 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7540 - false_negatives_1: 750.3036 - false_positives_1: 1020.0893 - loss: 0.5221
``` - + ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5354 - false_negatives_1: 2230.4561 - false_positives_1: 1146.1404 - loss: 0.6897 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7542 - false_negatives_1: 762.7193 - false_positives_1: 1036.9122 - loss: 0.5219
``` - + ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5359 - false_negatives_1: 2255.7415 - false_positives_1: 1173.5690 - loss: 0.6896 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7543 - false_negatives_1: 775.1724 - false_positives_1: 1053.6379 - loss: 0.5217
``` - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.5364 - false_negatives_1: 2280.5933 - false_positives_1: 1200.6271 - loss: 0.6896 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7545 - false_negatives_1: 787.4237 - false_positives_1: 1070.0339 - loss: 0.5214
``` -Epoch 1: val_loss improved from inf to 0.66886, saving model to AL_Model.keras +Epoch 4: val_loss improved from 0.51602 to 0.43948, saving model to AL_Model.keras - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 8s 90ms/step - binary_accuracy: 0.5369 - false_negatives_1: 2304.6167 - false_positives_1: 1226.7833 - loss: 0.6895 - val_binary_accuracy: 0.5976 - val_false_negatives_1: 169.0000 - val_false_positives_1: 1843.0000 - val_loss: 0.6689 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.7547 - false_negatives_1: 799.2667 - false_positives_1: 1085.8833 - loss: 0.5212 - val_binary_accuracy: 0.8028 - val_false_negatives_1: 342.0000 - val_false_positives_1: 644.0000 - val_loss: 0.4395
``` -Epoch 2/20 +Epoch 5/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 86ms/step - binary_accuracy: 0.5820 - false_negatives_1: 13.0000 - false_positives_1: 94.0000 - loss: 0.6720 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8164 - false_negatives_1: 12.0000 - false_positives_1: 35.0000 - loss: 0.4524
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.5918 - false_negatives_1: 30.0000 - false_positives_1: 125.5000 - loss: 0.6699 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.7998 - false_negatives_1: 37.5000 - false_positives_1: 41.5000 - loss: 0.4679
``` - + ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.6020 - false_negatives_1: 45.6667 - false_positives_1: 154.6667 - loss: 0.6681 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.7836 - false_negatives_1: 47.6667 - false_positives_1: 68.6667 - loss: 0.4876
``` - + ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6114 - false_negatives_1: 61.7500 - false_positives_1: 180.7500 - loss: 0.6667 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7791 - false_negatives_1: 60.2500 - false_positives_1: 87.0000 - loss: 0.4911
``` - + ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6163 - false_negatives_1: 76.0000 - false_positives_1: 211.2000 - loss: 0.6659 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7782 - false_negatives_1: 70.6000 - false_positives_1: 105.0000 - loss: 0.4904
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6206 - false_negatives_1: 92.3333 - false_positives_1: 238.6667 - loss: 0.6653 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7782 - false_negatives_1: 81.5000 - false_positives_1: 121.5000 - loss: 0.4889
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6246 - false_negatives_1: 108.4286 - false_positives_1: 265.1429 - loss: 0.6646 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7792 - false_negatives_1: 92.1429 - false_positives_1: 136.8571 - loss: 0.4867
``` - + ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6278 - false_negatives_1: 123.8750 - false_positives_1: 292.6250 - loss: 0.6639 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7809 - false_negatives_1: 102.7500 - false_positives_1: 150.7500 - loss: 0.4836
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6306 - false_negatives_1: 142.5556 - false_positives_1: 316.4445 - loss: 0.6634 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7826 - false_negatives_1: 112.8889 - false_positives_1: 164.6667 - loss: 0.4807
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6330 - false_negatives_1: 161.6000 - false_positives_1: 340.0000 - loss: 0.6629 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7841 - false_negatives_1: 123.2000 - false_positives_1: 178.3000 - loss: 0.4785
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6348 - false_negatives_1: 179.0000 - false_positives_1: 365.7273 - loss: 0.6624 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7853 - false_negatives_1: 134.9091 - false_positives_1: 191.0000 - loss: 0.4767
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6365 - false_negatives_1: 196.7500 - false_positives_1: 391.0000 - loss: 0.6619 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7861 - false_negatives_1: 145.0000 - false_positives_1: 206.2500 - loss: 0.4755
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6379 - false_negatives_1: 214.3846 - false_positives_1: 416.6154 - loss: 0.6615 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7867 - false_negatives_1: 156.4615 - false_positives_1: 220.7692 - loss: 0.4746
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6392 - false_negatives_1: 232.2143 - false_positives_1: 441.6429 - loss: 0.6611 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7870 - false_negatives_1: 167.5000 - false_positives_1: 236.2143 - loss: 0.4738
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6404 - false_negatives_1: 249.0667 - false_positives_1: 467.4667 - loss: 0.6606 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7875 - false_negatives_1: 178.3333 - false_positives_1: 250.8667 - loss: 0.4728
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.6417 - false_negatives_1: 267.4375 - false_positives_1: 491.3750 - loss: 0.6602 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7880 - false_negatives_1: 189.3125 - false_positives_1: 265.6250 - loss: 0.4721
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.6427 - false_negatives_1: 284.2941 - false_positives_1: 517.2941 - loss: 0.6598 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7885 - false_negatives_1: 200.4706 - false_positives_1: 279.9412 - loss: 0.4713
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6435 - false_negatives_1: 301.2778 - false_positives_1: 543.1667 - loss: 0.6594 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7890 - false_negatives_1: 211.3333 - false_positives_1: 294.2778 - loss: 0.4705
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6444 - false_negatives_1: 318.6316 - false_positives_1: 568.4211 - loss: 0.6590 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7894 - false_negatives_1: 223.0526 - false_positives_1: 307.9474 - loss: 0.4697
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6454 - false_negatives_1: 336.1000 - false_positives_1: 592.8000 - loss: 0.6586 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7896 - false_negatives_1: 233.8000 - false_positives_1: 323.5000 - loss: 0.4692
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6460 - false_negatives_1: 352.5714 - false_positives_1: 619.1429 - loss: 0.6582 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7896 - false_negatives_1: 247.0952 - false_positives_1: 337.6190 - loss: 0.4691
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6464 - false_negatives_1: 372.7273 - false_positives_1: 643.4545 - loss: 0.6580 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7894 - false_negatives_1: 259.2727 - false_positives_1: 353.9091 - loss: 0.4693
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.6468 - false_negatives_1: 391.5652 - false_positives_1: 668.4783 - loss: 0.6576 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 270.7391 - false_positives_1: 370.3478 - loss: 0.4694
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6472 - false_negatives_1: 409.6667 - false_positives_1: 694.2917 - loss: 0.6573 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 282.2917 - false_positives_1: 386.3750 - loss: 0.4695
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6475 - false_negatives_1: 427.9200 - false_positives_1: 719.9600 - loss: 0.6570 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 293.8400 - false_positives_1: 402.0000 - loss: 0.4696
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6479 - false_negatives_1: 446.8846 - false_positives_1: 744.6539 - loss: 0.6567 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 305.0385 - false_positives_1: 418.0385 - loss: 0.4696
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6483 - false_negatives_1: 466.6667 - false_positives_1: 768.3704 - loss: 0.6564 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 316.5926 - false_positives_1: 433.5926 - loss: 0.4696
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6486 - false_negatives_1: 486.0000 - false_positives_1: 792.2857 - loss: 0.6560 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7892 - false_negatives_1: 327.9643 - false_positives_1: 449.0714 - loss: 0.4696
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6490 - false_negatives_1: 505.5172 - false_positives_1: 815.7586 - loss: 0.6557 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7893 - false_negatives_1: 339.0345 - false_positives_1: 464.4828 - loss: 0.4695
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6494 - false_negatives_1: 524.8333 - false_positives_1: 839.6667 - loss: 0.6553 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7895 - false_negatives_1: 349.8667 - false_positives_1: 479.8333 - loss: 0.4694
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6497 - false_negatives_1: 545.6774 - false_positives_1: 862.3226 - loss: 0.6550 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7896 - false_negatives_1: 361.1290 - false_positives_1: 494.5807 - loss: 0.4693
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.6499 - false_negatives_1: 565.4688 - false_positives_1: 886.1875 - loss: 0.6546 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7897 - false_negatives_1: 371.9688 - false_positives_1: 509.8750 - loss: 0.4691
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6501 - false_negatives_1: 584.5757 - false_positives_1: 911.3939 - loss: 0.6543 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7898 - false_negatives_1: 383.6667 - false_positives_1: 524.6061 - loss: 0.4690
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6502 - false_negatives_1: 603.5000 - false_positives_1: 936.6177 - loss: 0.6540 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7899 - false_negatives_1: 394.8235 - false_positives_1: 539.9412 - loss: 0.4689
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6504 - false_negatives_1: 622.2571 - false_positives_1: 962.1143 - loss: 0.6537 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7900 - false_negatives_1: 406.1429 - false_positives_1: 554.8857 - loss: 0.4687
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6506 - false_negatives_1: 640.8055 - false_positives_1: 987.3333 - loss: 0.6533 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7901 - false_negatives_1: 417.3333 - false_positives_1: 569.6667 - loss: 0.4686
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6508 - false_negatives_1: 659.1622 - false_positives_1: 1012.3784 - loss: 0.6530 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7902 - false_negatives_1: 428.6216 - false_positives_1: 584.4324 - loss: 0.4685
``` - + ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6510 - false_negatives_1: 678.3947 - false_positives_1: 1036.5526 - loss: 0.6527 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7903 - false_negatives_1: 439.9474 - false_positives_1: 599.3421 - loss: 0.4684
``` - + ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6512 - false_negatives_1: 696.7692 - false_positives_1: 1061.3334 - loss: 0.6523 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7904 - false_negatives_1: 451.0000 - false_positives_1: 614.0769 - loss: 0.4682
``` - + ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6515 - false_negatives_1: 715.4750 - false_positives_1: 1085.4250 - loss: 0.6520 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7905 - false_negatives_1: 462.1750 - false_positives_1: 628.5000 - loss: 0.4681
``` - + ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6517 - false_negatives_1: 733.6585 - false_positives_1: 1109.9512 - loss: 0.6516 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7907 - false_negatives_1: 473.0976 - false_positives_1: 643.2927 - loss: 0.4679
``` - + ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6519 - false_negatives_1: 752.0238 - false_positives_1: 1134.2380 - loss: 0.6513 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7908 - false_negatives_1: 484.4762 - false_positives_1: 657.5238 - loss: 0.4677
``` - + ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6522 - false_negatives_1: 769.9535 - false_positives_1: 1159.0233 - loss: 0.6509 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7909 - false_negatives_1: 495.3721 - false_positives_1: 673.0000 - loss: 0.4676
``` - + ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6524 - false_negatives_1: 788.4091 - false_positives_1: 1183.1136 - loss: 0.6506 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7909 - false_negatives_1: 507.2046 - false_positives_1: 687.9318 - loss: 0.4675
``` - + ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.6526 - false_negatives_1: 806.2889 - false_positives_1: 1208.1777 - loss: 0.6503 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7909 - false_negatives_1: 518.7556 - false_positives_1: 702.8444 - loss: 0.4674
``` - + ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6528 - false_negatives_1: 824.6304 - false_positives_1: 1232.5217 - loss: 0.6500 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7910 - false_negatives_1: 530.1739 - false_positives_1: 717.7826 - loss: 0.4673
``` - + ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6530 - false_negatives_1: 842.8298 - false_positives_1: 1256.9788 - loss: 0.6497 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7910 - false_negatives_1: 541.5958 - false_positives_1: 732.4894 - loss: 0.4671
``` - + ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6532 - false_negatives_1: 861.1667 - false_positives_1: 1281.1041 - loss: 0.6494 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7911 - false_negatives_1: 552.8333 - false_positives_1: 747.3750 - loss: 0.4670
``` - + ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6535 - false_negatives_1: 879.1837 - false_positives_1: 1305.3062 - loss: 0.6490 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7912 - false_negatives_1: 564.3878 - false_positives_1: 761.8979 - loss: 0.4669
``` - + ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6537 - false_negatives_1: 897.7400 - false_positives_1: 1328.8600 - loss: 0.6487 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7912 - false_negatives_1: 575.6000 - false_positives_1: 776.7600 - loss: 0.4668
``` - + ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6539 - false_negatives_1: 915.6667 - false_positives_1: 1353.3334 - loss: 0.6484 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7913 - false_negatives_1: 587.0000 - false_positives_1: 791.3333 - loss: 0.4667
``` - + ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6541 - false_negatives_1: 933.8461 - false_positives_1: 1377.3077 - loss: 0.6481 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7914 - false_negatives_1: 598.0961 - false_positives_1: 806.0961 - loss: 0.4666
``` - + ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6543 - false_negatives_1: 951.7358 - false_positives_1: 1401.5094 - loss: 0.6478 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7915 - false_negatives_1: 609.4340 - false_positives_1: 820.6038 - loss: 0.4664
``` - + ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6545 - false_negatives_1: 970.3148 - false_positives_1: 1425.0000 - loss: 0.6475 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7915 - false_negatives_1: 620.7222 - false_positives_1: 835.2037 - loss: 0.4663
``` - + ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6547 - false_negatives_1: 988.4363 - false_positives_1: 1449.0909 - loss: 0.6472 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7916 - false_negatives_1: 632.0182 - false_positives_1: 849.8182 - loss: 0.4662
``` - + ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6549 - false_negatives_1: 1006.2679 - false_positives_1: 1473.2142 - loss: 0.6468 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7917 - false_negatives_1: 643.2500 - false_positives_1: 864.4107 - loss: 0.4661
``` - + ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6551 - false_negatives_1: 1024.2456 - false_positives_1: 1497.1052 - loss: 0.6465 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7918 - false_negatives_1: 654.5088 - false_positives_1: 878.9298 - loss: 0.4659
``` - + ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6553 - false_negatives_1: 1042.0344 - false_positives_1: 1521.0518 - loss: 0.6462 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7918 - false_negatives_1: 665.7414 - false_positives_1: 893.3448 - loss: 0.4658
``` - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.6555 - false_negatives_1: 1059.6610 - false_positives_1: 1544.6610 - loss: 0.6459 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7919 - false_negatives_1: 676.7458 - false_positives_1: 907.4915 - loss: 0.4657
``` -Epoch 2: val_loss improved from 0.66886 to 0.57736, saving model to AL_Model.keras +Epoch 5: val_loss improved from 0.43948 to 0.41679, saving model to AL_Model.keras - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 86ms/step - binary_accuracy: 0.6557 - false_negatives_1: 1076.7000 - false_positives_1: 1567.4833 - loss: 0.6456 - val_binary_accuracy: 0.6952 - val_false_negatives_1: 200.0000 - val_false_positives_1: 1324.0000 - val_loss: 0.5774 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.7920 - false_negatives_1: 687.3834 - false_positives_1: 921.1667 - loss: 0.4655 - val_binary_accuracy: 0.8158 - val_false_negatives_1: 598.0000 - val_false_positives_1: 323.0000 - val_loss: 0.4168
``` -Epoch 3/20 +Epoch 6/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 88ms/step - binary_accuracy: 0.7109 - false_negatives_1: 15.0000 - false_positives_1: 59.0000 - loss: 0.5792 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 88ms/step - binary_accuracy: 0.8242 - false_negatives_1: 35.0000 - false_positives_1: 10.0000 - loss: 0.4112
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.7266 - false_negatives_1: 38.0000 - false_positives_1: 65.0000 - loss: 0.5712 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7920 - false_negatives_1: 36.5000 - false_positives_1: 47.5000 - loss: 0.4591
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.7192 - false_negatives_1: 47.6667 - false_positives_1: 96.6667 - loss: 0.5763 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7745 - false_negatives_1: 62.3333 - false_positives_1: 60.3333 - loss: 0.4832
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.7154 - false_negatives_1: 68.5000 - false_positives_1: 115.5000 - loss: 0.5764 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7635 - false_negatives_1: 75.2500 - false_positives_1: 85.7500 - loss: 0.4998
``` - + ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.7122 - false_negatives_1: 82.4000 - false_positives_1: 141.8000 - loss: 0.5769 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7589 - false_negatives_1: 90.2000 - false_positives_1: 105.0000 - loss: 0.5053
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7107 - false_negatives_1: 94.8333 - false_positives_1: 168.0000 - loss: 0.5774 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7598 - false_negatives_1: 102.6667 - false_positives_1: 120.3333 - loss: 0.5042
``` - + ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7104 - false_negatives_1: 110.2857 - false_positives_1: 189.5714 - loss: 0.5773 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7619 - false_negatives_1: 114.4286 - false_positives_1: 134.5714 - loss: 0.5020
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7098 - false_negatives_1: 123.6250 - false_positives_1: 214.1250 - loss: 0.5775 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7644 - false_negatives_1: 124.7500 - false_positives_1: 148.8750 - loss: 0.4986
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7094 - false_negatives_1: 138.3333 - false_positives_1: 237.0000 - loss: 0.5776 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7668 - false_negatives_1: 135.1111 - false_positives_1: 163.0000 - loss: 0.4955
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7098 - false_negatives_1: 154.8000 - false_positives_1: 256.5000 - loss: 0.5771 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7690 - false_negatives_1: 145.9000 - false_positives_1: 176.3000 - loss: 0.4923
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7099 - false_negatives_1: 169.0909 - false_positives_1: 278.7273 - loss: 0.5768 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7714 - false_negatives_1: 156.0909 - false_positives_1: 189.1818 - loss: 0.4890
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7100 - false_negatives_1: 182.9167 - false_positives_1: 301.5000 - loss: 0.5765 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7736 - false_negatives_1: 166.0833 - false_positives_1: 202.1667 - loss: 0.4859
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7103 - false_negatives_1: 197.4615 - false_positives_1: 323.0000 - loss: 0.5764 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7759 - false_negatives_1: 175.8462 - false_positives_1: 214.6154 - loss: 0.4827
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7104 - false_negatives_1: 211.6429 - false_positives_1: 345.5714 - loss: 0.5763 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7778 - false_negatives_1: 185.2857 - false_positives_1: 227.6429 - loss: 0.4797
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7107 - false_negatives_1: 226.7333 - false_positives_1: 366.2667 - loss: 0.5760 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7795 - false_negatives_1: 195.5333 - false_positives_1: 240.2667 - loss: 0.4771
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7106 - false_negatives_1: 240.3125 - false_positives_1: 390.0625 - loss: 0.5761 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7809 - false_negatives_1: 204.8750 - false_positives_1: 254.3750 - loss: 0.4750
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.7104 - false_negatives_1: 256.4706 - false_positives_1: 411.6471 - loss: 0.5763 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7819 - false_negatives_1: 217.1176 - false_positives_1: 267.0588 - loss: 0.4736
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7102 - false_negatives_1: 271.2778 - false_positives_1: 434.8333 - loss: 0.5765 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7827 - false_negatives_1: 228.0000 - false_positives_1: 281.1667 - loss: 0.4725
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7101 - false_negatives_1: 285.2105 - false_positives_1: 458.6842 - loss: 0.5767 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7836 - false_negatives_1: 238.5789 - false_positives_1: 295.3684 - loss: 0.4714
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7101 - false_negatives_1: 298.7500 - false_positives_1: 482.1000 - loss: 0.5768 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7843 - false_negatives_1: 249.4000 - false_positives_1: 309.3500 - loss: 0.4705
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7102 - false_negatives_1: 312.2857 - false_positives_1: 505.1429 - loss: 0.5768 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7851 - false_negatives_1: 260.0952 - false_positives_1: 322.9524 - loss: 0.4694
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7103 - false_negatives_1: 325.6818 - false_positives_1: 527.7727 - loss: 0.5768 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7859 - false_negatives_1: 270.6364 - false_positives_1: 336.6818 - loss: 0.4684
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7105 - false_negatives_1: 338.8261 - false_positives_1: 550.4348 - loss: 0.5767 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7866 - false_negatives_1: 280.8696 - false_positives_1: 350.3478 - loss: 0.4674
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7108 - false_negatives_1: 352.5000 - false_positives_1: 572.0000 - loss: 0.5765 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7874 - false_negatives_1: 291.4167 - false_positives_1: 363.6667 - loss: 0.4664
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7111 - false_negatives_1: 366.1200 - false_positives_1: 593.7200 - loss: 0.5763 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7881 - false_negatives_1: 301.6000 - false_positives_1: 376.8800 - loss: 0.4654
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7114 - false_negatives_1: 379.9615 - false_positives_1: 615.0385 - loss: 0.5760 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7888 - false_negatives_1: 312.1923 - false_positives_1: 389.7308 - loss: 0.4644
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7117 - false_negatives_1: 393.7778 - false_positives_1: 636.3333 - loss: 0.5757 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7895 - false_negatives_1: 322.1852 - false_positives_1: 403.2592 - loss: 0.4635
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7120 - false_negatives_1: 408.0000 - false_positives_1: 656.9643 - loss: 0.5754 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7901 - false_negatives_1: 333.2857 - false_positives_1: 416.0357 - loss: 0.4627
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7123 - false_negatives_1: 421.7586 - false_positives_1: 677.5172 - loss: 0.5751 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7905 - false_negatives_1: 343.7586 - false_positives_1: 429.9310 - loss: 0.4620
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7126 - false_negatives_1: 436.4667 - false_positives_1: 697.4667 - loss: 0.5747 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7910 - false_negatives_1: 354.4333 - false_positives_1: 443.8333 - loss: 0.4614
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7128 - false_negatives_1: 450.3226 - false_positives_1: 719.1290 - loss: 0.5746 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.7914 - false_negatives_1: 364.8710 - false_positives_1: 457.5484 - loss: 0.4607
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7130 - false_negatives_1: 463.7500 - false_positives_1: 741.1875 - loss: 0.5744 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7918 - false_negatives_1: 375.2188 - false_positives_1: 471.3125 - loss: 0.4601
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7132 - false_negatives_1: 477.0909 - false_positives_1: 763.4243 - loss: 0.5742 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7923 - false_negatives_1: 385.6667 - false_positives_1: 484.7879 - loss: 0.4595
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7134 - false_negatives_1: 490.4706 - false_positives_1: 785.2941 - loss: 0.5740 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7927 - false_negatives_1: 395.8529 - false_positives_1: 498.4118 - loss: 0.4589
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7136 - false_negatives_1: 503.8857 - false_positives_1: 806.8571 - loss: 0.5737 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7932 - false_negatives_1: 406.3143 - false_positives_1: 511.5714 - loss: 0.4583
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7138 - false_negatives_1: 517.1667 - false_positives_1: 828.1389 - loss: 0.5734 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7935 - false_negatives_1: 416.4722 - false_positives_1: 525.2500 - loss: 0.4577
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7141 - false_negatives_1: 530.4324 - false_positives_1: 849.1081 - loss: 0.5731 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7939 - false_negatives_1: 426.8919 - false_positives_1: 538.4865 - loss: 0.4571
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7144 - false_negatives_1: 543.6579 - false_positives_1: 869.7895 - loss: 0.5728 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7943 - false_negatives_1: 437.4737 - false_positives_1: 551.3947 - loss: 0.4566
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7147 - false_negatives_1: 556.7949 - false_positives_1: 890.6154 - loss: 0.5724 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7947 - false_negatives_1: 447.7180 - false_positives_1: 565.0769 - loss: 0.4560
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7150 - false_negatives_1: 570.8000 - false_positives_1: 910.7250 - loss: 0.5721 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7949 - false_negatives_1: 459.2000 - false_positives_1: 578.1750 - loss: 0.4557
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7151 - false_negatives_1: 584.1951 - false_positives_1: 932.5610 - loss: 0.5720 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7952 - false_negatives_1: 470.2195 - false_positives_1: 592.0732 - loss: 0.4554
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7152 - false_negatives_1: 597.1905 - false_positives_1: 955.3810 - loss: 0.5719 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7954 - false_negatives_1: 481.2143 - false_positives_1: 605.7143 - loss: 0.4551
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7154 - false_negatives_1: 609.9070 - false_positives_1: 977.9535 - loss: 0.5717 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7956 - false_negatives_1: 492.1163 - false_positives_1: 619.3023 - loss: 0.4548
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7155 - false_negatives_1: 622.4773 - false_positives_1: 1000.3864 - loss: 0.5716 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7959 - false_negatives_1: 502.9773 - false_positives_1: 632.5909 - loss: 0.4545
``` - + ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7157 - false_negatives_1: 634.8444 - false_positives_1: 1022.4445 - loss: 0.5713 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.7961 - false_negatives_1: 513.8889 - false_positives_1: 645.9333 - loss: 0.4541
``` - + ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7159 - false_negatives_1: 647.3696 - false_positives_1: 1044.0652 - loss: 0.5711 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7964 - false_negatives_1: 524.5435 - false_positives_1: 659.3261 - loss: 0.4538
``` - + ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7162 - false_negatives_1: 659.8511 - false_positives_1: 1065.5957 - loss: 0.5708 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7966 - false_negatives_1: 535.1702 - false_positives_1: 672.7234 - loss: 0.4535
``` - + ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7164 - false_negatives_1: 672.3125 - false_positives_1: 1087.0416 - loss: 0.5706 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7969 - false_negatives_1: 545.8542 - false_positives_1: 685.9583 - loss: 0.4532
``` - + ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7166 - false_negatives_1: 684.8367 - false_positives_1: 1108.4694 - loss: 0.5704 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7971 - false_negatives_1: 556.5510 - false_positives_1: 699.1429 - loss: 0.4529
``` - + ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7168 - false_negatives_1: 697.3000 - false_positives_1: 1129.7600 - loss: 0.5701 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7974 - false_negatives_1: 567.0000 - false_positives_1: 712.2400 - loss: 0.4525
``` - + ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7171 - false_negatives_1: 709.9020 - false_positives_1: 1150.8823 - loss: 0.5698 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7976 - false_negatives_1: 577.5686 - false_positives_1: 725.0588 - loss: 0.4522
``` - + ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7173 - false_negatives_1: 722.4231 - false_positives_1: 1172.0193 - loss: 0.5696 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7979 - false_negatives_1: 587.8461 - false_positives_1: 738.0192 - loss: 0.4519
``` - + ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7175 - false_negatives_1: 735.6604 - false_positives_1: 1192.4529 - loss: 0.5693 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7981 - false_negatives_1: 598.5283 - false_positives_1: 750.5849 - loss: 0.4515
``` - + ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7177 - false_negatives_1: 748.4259 - false_positives_1: 1214.0000 - loss: 0.5691 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7984 - false_negatives_1: 608.8519 - false_positives_1: 763.8704 - loss: 0.4513
``` - + ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7178 - false_negatives_1: 761.3091 - false_positives_1: 1235.5272 - loss: 0.5689 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7986 - false_negatives_1: 619.5091 - false_positives_1: 776.8727 - loss: 0.4510
``` - + ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7180 - false_negatives_1: 774.3214 - false_positives_1: 1256.7322 - loss: 0.5687 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7988 - false_negatives_1: 630.0357 - false_positives_1: 789.8393 - loss: 0.4507
``` - + ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7182 - false_negatives_1: 787.2281 - false_positives_1: 1277.7368 - loss: 0.5685 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7990 - false_negatives_1: 640.5088 - false_positives_1: 802.7193 - loss: 0.4504
``` - + ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.7184 - false_negatives_1: 800.1552 - false_positives_1: 1298.5000 - loss: 0.5683 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7992 - false_negatives_1: 651.0000 - false_positives_1: 815.5000 - loss: 0.4501
``` - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7186 - false_negatives_1: 812.8813 - false_positives_1: 1318.9661 - loss: 0.5680 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.7994 - false_negatives_1: 661.3560 - false_positives_1: 828.0847 - loss: 0.4498
``` -Epoch 3: val_loss improved from 0.57736 to 0.47568, saving model to AL_Model.keras +Epoch 6: val_loss improved from 0.41679 to 0.39680, saving model to AL_Model.keras - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.7187 - false_negatives_1: 825.1833 - false_positives_1: 1338.7500 - loss: 0.5678 - val_binary_accuracy: 0.7852 - val_false_negatives_1: 423.0000 - val_false_positives_1: 651.0000 - val_loss: 0.4757 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.7997 - false_negatives_1: 671.3666 - false_positives_1: 840.2500 - loss: 0.4495 - val_binary_accuracy: 0.8260 - val_false_negatives_1: 382.0000 - val_false_positives_1: 488.0000 - val_loss: 0.3968
``` -Epoch 4/20 +Epoch 7/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 87ms/step - binary_accuracy: 0.8438 - false_negatives_1: 16.0000 - false_positives_1: 24.0000 - loss: 0.4527 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8281 - false_negatives_1: 14.0000 - false_positives_1: 30.0000 - loss: 0.4037
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8252 - false_negatives_1: 26.5000 - false_positives_1: 43.0000 - loss: 0.4617 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.8301 - false_negatives_1: 26.5000 - false_positives_1: 38.5000 - loss: 0.4047
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8136 - false_negatives_1: 47.0000 - false_positives_1: 53.0000 - loss: 0.4768 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8338 - false_negatives_1: 34.0000 - false_positives_1: 50.0000 - loss: 0.3987
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.7996 - false_negatives_1: 57.5000 - false_positives_1: 79.5000 - loss: 0.4926 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8358 - false_negatives_1: 44.0000 - false_positives_1: 59.5000 - loss: 0.3945
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7922 - false_negatives_1: 66.4000 - false_positives_1: 104.0000 - loss: 0.5018 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8374 - false_negatives_1: 52.4000 - false_positives_1: 70.4000 - loss: 0.3902
``` - + ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7872 - false_negatives_1: 78.6667 - false_positives_1: 124.1667 - loss: 0.5072 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8382 - false_negatives_1: 62.8333 - false_positives_1: 79.8333 - loss: 0.3874
``` - + ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7838 - false_negatives_1: 90.5714 - false_positives_1: 143.8571 - loss: 0.5103 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8377 - false_negatives_1: 70.8571 - false_positives_1: 93.8571 - loss: 0.3875
``` - + ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7820 - false_negatives_1: 101.0000 - false_positives_1: 163.2500 - loss: 0.5114 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 71ms/step - binary_accuracy: 0.8352 - false_negatives_1: 86.1250 - false_positives_1: 104.5000 - loss: 0.3913
``` - + ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7814 - false_negatives_1: 111.3333 - false_positives_1: 180.6667 - loss: 0.5111 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8333 - false_negatives_1: 98.1111 - false_positives_1: 118.0000 - loss: 0.3944
``` - + ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7814 - false_negatives_1: 121.3000 - false_positives_1: 197.5000 - loss: 0.5103 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8320 - false_negatives_1: 109.2000 - false_positives_1: 131.2000 - loss: 0.3964
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7817 - false_negatives_1: 131.7273 - false_positives_1: 213.2727 - loss: 0.5094 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8315 - false_negatives_1: 120.0000 - false_positives_1: 143.1818 - loss: 0.3976
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7813 - false_negatives_1: 141.5833 - false_positives_1: 231.5833 - loss: 0.5090 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 130.4167 - false_positives_1: 155.3333 - loss: 0.3987
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7804 - false_negatives_1: 156.3077 - false_positives_1: 247.2308 - loss: 0.5096 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8309 - false_negatives_1: 139.9231 - false_positives_1: 167.5385 - loss: 0.3992
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7791 - false_negatives_1: 169.1429 - false_positives_1: 266.4286 - loss: 0.5106 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8308 - false_negatives_1: 149.4286 - false_positives_1: 179.5000 - loss: 0.3997
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7779 - false_negatives_1: 181.0667 - false_positives_1: 286.8667 - loss: 0.5114 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8309 - false_negatives_1: 158.8000 - false_positives_1: 191.4000 - loss: 0.4000
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7769 - false_negatives_1: 193.0000 - false_positives_1: 306.5625 - loss: 0.5121 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 167.9375 - false_positives_1: 202.9375 - loss: 0.4001
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.7760 - false_negatives_1: 205.2353 - false_positives_1: 325.7647 - loss: 0.5128 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 177.2941 - false_positives_1: 214.6471 - loss: 0.4002
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7754 - false_negatives_1: 216.7222 - false_positives_1: 345.2222 - loss: 0.5132 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8313 - false_negatives_1: 186.5000 - false_positives_1: 226.3333 - loss: 0.4000
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7748 - false_negatives_1: 228.9474 - false_positives_1: 363.5789 - loss: 0.5136 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8313 - false_negatives_1: 196.0526 - false_positives_1: 237.9474 - loss: 0.4001
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7742 - false_negatives_1: 240.8500 - false_positives_1: 382.6000 - loss: 0.5139 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8315 - false_negatives_1: 205.3000 - false_positives_1: 249.4500 - loss: 0.4000
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7737 - false_negatives_1: 253.5238 - false_positives_1: 401.1905 - loss: 0.5143 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8315 - false_negatives_1: 215.1429 - false_positives_1: 260.6667 - loss: 0.3999
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7732 - false_negatives_1: 266.0909 - false_positives_1: 419.4546 - loss: 0.5145 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8316 - false_negatives_1: 224.1364 - false_positives_1: 273.0454 - loss: 0.3999
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7728 - false_negatives_1: 278.3478 - false_positives_1: 437.4783 - loss: 0.5146 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8314 - false_negatives_1: 235.0435 - false_positives_1: 284.4348 - loss: 0.4002
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7726 - false_negatives_1: 291.0417 - false_positives_1: 454.5417 - loss: 0.5145 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8312 - false_negatives_1: 245.2500 - false_positives_1: 297.0417 - loss: 0.4007
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7724 - false_negatives_1: 303.1200 - false_positives_1: 471.9600 - loss: 0.5144 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 255.4800 - false_positives_1: 309.7600 - loss: 0.4011
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7723 - false_negatives_1: 315.8846 - false_positives_1: 488.2692 - loss: 0.5142 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8308 - false_negatives_1: 265.7308 - false_positives_1: 322.0769 - loss: 0.4014
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7723 - false_negatives_1: 327.9630 - false_positives_1: 504.9259 - loss: 0.5139 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8307 - false_negatives_1: 275.6296 - false_positives_1: 334.5555 - loss: 0.4017
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7722 - false_negatives_1: 340.9643 - false_positives_1: 520.9286 - loss: 0.5137 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8306 - false_negatives_1: 285.5714 - false_positives_1: 346.6786 - loss: 0.4018
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7720 - false_negatives_1: 353.3793 - false_positives_1: 538.7586 - loss: 0.5136 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8305 - false_negatives_1: 295.5172 - false_positives_1: 359.0345 - loss: 0.4020
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7718 - false_negatives_1: 366.7333 - false_positives_1: 555.7333 - loss: 0.5135 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8305 - false_negatives_1: 305.3333 - false_positives_1: 371.3333 - loss: 0.4022
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.7716 - false_negatives_1: 379.5484 - false_positives_1: 573.4194 - loss: 0.5134 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8305 - false_negatives_1: 315.0968 - false_positives_1: 383.2258 - loss: 0.4023
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7713 - false_negatives_1: 393.0000 - false_positives_1: 590.7188 - loss: 0.5134 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8305 - false_negatives_1: 324.8125 - false_positives_1: 394.7812 - loss: 0.4022
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7711 - false_negatives_1: 405.9394 - false_positives_1: 608.3636 - loss: 0.5133 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8305 - false_negatives_1: 334.4849 - false_positives_1: 406.3940 - loss: 0.4022
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7709 - false_negatives_1: 419.4118 - false_positives_1: 625.5000 - loss: 0.5132 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8306 - false_negatives_1: 344.1765 - false_positives_1: 417.7647 - loss: 0.4021
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7707 - false_negatives_1: 432.2571 - false_positives_1: 643.4572 - loss: 0.5131 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8307 - false_negatives_1: 353.7143 - false_positives_1: 429.2857 - loss: 0.4021
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7705 - false_negatives_1: 445.0555 - false_positives_1: 661.3611 - loss: 0.5130 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8307 - false_negatives_1: 363.3333 - false_positives_1: 440.8889 - loss: 0.4020
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7703 - false_negatives_1: 457.9730 - false_positives_1: 678.9189 - loss: 0.5129 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8308 - false_negatives_1: 372.8919 - false_positives_1: 452.3784 - loss: 0.4019
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7701 - false_negatives_1: 470.4474 - false_positives_1: 696.7105 - loss: 0.5128 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8308 - false_negatives_1: 382.4474 - false_positives_1: 463.7368 - loss: 0.4017
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7700 - false_negatives_1: 483.0256 - false_positives_1: 714.0256 - loss: 0.5127 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8309 - false_negatives_1: 391.7436 - false_positives_1: 475.0000 - loss: 0.4016
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7700 - false_negatives_1: 495.3000 - false_positives_1: 731.1750 - loss: 0.5124 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 401.0250 - false_positives_1: 485.9500 - loss: 0.4014
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7700 - false_negatives_1: 507.2439 - false_positives_1: 748.3415 - loss: 0.5122 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8312 - false_negatives_1: 409.9756 - false_positives_1: 497.6585 - loss: 0.4013
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7699 - false_negatives_1: 520.2143 - false_positives_1: 764.8333 - loss: 0.5120 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 420.5952 - false_positives_1: 508.8095 - loss: 0.4014
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7698 - false_negatives_1: 532.5814 - false_positives_1: 782.7442 - loss: 0.5119 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 430.7675 - false_positives_1: 520.5582 - loss: 0.4015
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7697 - false_negatives_1: 544.7727 - false_positives_1: 800.8409 - loss: 0.5119 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 440.7954 - false_positives_1: 532.3864 - loss: 0.4016
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.7696 - false_negatives_1: 556.9556 - false_positives_1: 818.9778 - loss: 0.5118 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 450.8667 - false_positives_1: 544.1778 - loss: 0.4017
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7695 - false_negatives_1: 569.0217 - false_positives_1: 837.0652 - loss: 0.5117 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 461.0000 - false_positives_1: 555.9348 - loss: 0.4017
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7694 - false_negatives_1: 580.9787 - false_positives_1: 855.0638 - loss: 0.5116 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 470.8723 - false_positives_1: 567.9575 - loss: 0.4018
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7694 - false_negatives_1: 593.1042 - false_positives_1: 872.8958 - loss: 0.5114 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 480.8542 - false_positives_1: 579.6875 - loss: 0.4018
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 605.0816 - false_positives_1: 890.7347 - loss: 0.5113 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 490.9184 - false_positives_1: 591.3878 - loss: 0.4019
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 617.0400 - false_positives_1: 908.2800 - loss: 0.5112 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 500.7200 - false_positives_1: 603.3600 - loss: 0.4019
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 628.8431 - false_positives_1: 925.7843 - loss: 0.5110 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 510.7451 - false_positives_1: 615.0392 - loss: 0.4019
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 640.5961 - false_positives_1: 943.0000 - loss: 0.5108 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 520.6154 - false_positives_1: 626.8654 - loss: 0.4019
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 652.6226 - false_positives_1: 959.8868 - loss: 0.5106 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 530.5095 - false_positives_1: 638.6793 - loss: 0.4019
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 664.3519 - false_positives_1: 977.0555 - loss: 0.5104 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 540.3148 - false_positives_1: 650.3519 - loss: 0.4019
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 676.8364 - false_positives_1: 993.8182 - loss: 0.5103 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 550.1454 - false_positives_1: 661.8727 - loss: 0.4019
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 688.9107 - false_positives_1: 1011.1250 - loss: 0.5101 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 559.9464 - false_positives_1: 673.3214 - loss: 0.4018
``` - + ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 700.8596 - false_positives_1: 1028.3508 - loss: 0.5100 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 569.7193 - false_positives_1: 684.6316 - loss: 0.4018
``` - + ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 712.8448 - false_positives_1: 1045.4656 - loss: 0.5098 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 579.5690 - false_positives_1: 695.8448 - loss: 0.4017
``` - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.7693 - false_negatives_1: 724.5932 - false_positives_1: 1062.3390 - loss: 0.5097 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8311 - false_negatives_1: 589.1187 - false_positives_1: 707.0170 - loss: 0.4017
``` -Epoch 4: val_loss improved from 0.47568 to 0.45039, saving model to AL_Model.keras +Epoch 7: val_loss did not improve from 0.39680 - + ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.7694 - false_negatives_1: 735.9500 - false_positives_1: 1078.6500 - loss: 0.5096 - val_binary_accuracy: 0.8002 - val_false_negatives_1: 599.0000 - val_false_positives_1: 400.0000 - val_loss: 0.4504 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8312 - false_negatives_1: 598.3500 - false_positives_1: 717.8167 - loss: 0.4016 - val_binary_accuracy: 0.7706 - val_false_negatives_1: 1004.0000 - val_false_positives_1: 143.0000 - val_loss: 0.4884
``` -Epoch 5/20 +Epoch 8/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 88ms/step - binary_accuracy: 0.8242 - false_negatives_1: 26.0000 - false_positives_1: 19.0000 - loss: 0.4325 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8047 - false_negatives_1: 46.0000 - false_positives_1: 4.0000 - loss: 0.4254
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8213 - false_negatives_1: 33.5000 - false_positives_1: 35.5000 - loss: 0.4354 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.7959 - false_negatives_1: 51.0000 - false_positives_1: 28.5000 - loss: 0.4374
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8166 - false_negatives_1: 45.6667 - false_positives_1: 49.6667 - loss: 0.4380 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.7928 - false_negatives_1: 68.0000 - false_positives_1: 39.6667 - loss: 0.4406
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8141 - false_negatives_1: 59.0000 - false_positives_1: 62.0000 - loss: 0.4391 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7940 - false_negatives_1: 79.2500 - false_positives_1: 53.2500 - loss: 0.4401
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8130 - false_negatives_1: 69.2000 - false_positives_1: 76.6000 - loss: 0.4381 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.7971 - false_negatives_1: 88.8000 - false_positives_1: 66.0000 - loss: 0.4355
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8129 - false_negatives_1: 81.1667 - false_positives_1: 88.3333 - loss: 0.4373 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8009 - false_negatives_1: 97.6667 - false_positives_1: 77.5000 - loss: 0.4306
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8123 - false_negatives_1: 90.4286 - false_positives_1: 103.8571 - loss: 0.4372 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8040 - false_negatives_1: 106.0000 - false_positives_1: 89.4286 - loss: 0.4261
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8105 - false_negatives_1: 104.3750 - false_positives_1: 117.3750 - loss: 0.4389 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8070 - false_negatives_1: 114.0000 - false_positives_1: 101.0000 - loss: 0.4221
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8084 - false_negatives_1: 115.6667 - false_positives_1: 134.8889 - loss: 0.4410 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8099 - false_negatives_1: 122.4444 - false_positives_1: 111.4444 - loss: 0.4184
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8072 - false_negatives_1: 127.4000 - false_positives_1: 150.2000 - loss: 0.4422 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8129 - false_negatives_1: 130.4000 - false_positives_1: 121.2000 - loss: 0.4148
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8061 - false_negatives_1: 138.6364 - false_positives_1: 166.1818 - loss: 0.4435 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8155 - false_negatives_1: 138.4545 - false_positives_1: 130.7273 - loss: 0.4108
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8055 - false_negatives_1: 149.3333 - false_positives_1: 181.5000 - loss: 0.4441 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8178 - false_negatives_1: 145.5000 - false_positives_1: 141.5000 - loss: 0.4076
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8053 - false_negatives_1: 159.3846 - false_positives_1: 196.5385 - loss: 0.4441 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8194 - false_negatives_1: 155.2308 - false_positives_1: 151.0000 - loss: 0.4056
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8051 - false_negatives_1: 170.0714 - false_positives_1: 210.8571 - loss: 0.4443 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8202 - false_negatives_1: 163.7857 - false_positives_1: 163.7857 - loss: 0.4048
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8049 - false_negatives_1: 180.0667 - false_positives_1: 226.2667 - loss: 0.4444 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8208 - false_negatives_1: 174.3333 - false_positives_1: 175.4000 - loss: 0.4046
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8046 - false_negatives_1: 191.4375 - false_positives_1: 240.5000 - loss: 0.4446 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8213 - false_negatives_1: 184.0000 - false_positives_1: 187.7500 - loss: 0.4042
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8043 - false_negatives_1: 201.8235 - false_positives_1: 256.0000 - loss: 0.4450 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8217 - false_negatives_1: 194.0000 - false_positives_1: 199.6471 - loss: 0.4039
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8042 - false_negatives_1: 212.5556 - false_positives_1: 270.6667 - loss: 0.4453 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8223 - false_negatives_1: 203.4444 - false_positives_1: 211.2222 - loss: 0.4034
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8041 - false_negatives_1: 222.8421 - false_positives_1: 285.5263 - loss: 0.4457 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8230 - false_negatives_1: 212.8947 - false_positives_1: 222.2632 - loss: 0.4028
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8040 - false_negatives_1: 233.7000 - false_positives_1: 299.7000 - loss: 0.4459 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8236 - false_negatives_1: 221.8000 - false_positives_1: 233.9000 - loss: 0.4023
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8041 - false_negatives_1: 243.7619 - false_positives_1: 314.0476 - loss: 0.4459 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8242 - false_negatives_1: 230.8095 - false_positives_1: 245.0952 - loss: 0.4017
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8041 - false_negatives_1: 255.1818 - false_positives_1: 327.3182 - loss: 0.4461 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8248 - false_negatives_1: 239.4545 - false_positives_1: 256.1364 - loss: 0.4011
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8040 - false_negatives_1: 265.6087 - false_positives_1: 342.4783 - loss: 0.4465 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8255 - false_negatives_1: 247.9565 - false_positives_1: 266.8261 - loss: 0.4003
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8039 - false_negatives_1: 276.0833 - false_positives_1: 357.4167 - loss: 0.4468 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8263 - false_negatives_1: 256.2500 - false_positives_1: 277.2083 - loss: 0.3995
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 287.2000 - false_positives_1: 371.8800 - loss: 0.4471 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8270 - false_negatives_1: 264.7200 - false_positives_1: 287.3600 - loss: 0.3987
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 298.0000 - false_positives_1: 386.0769 - loss: 0.4473 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8276 - false_negatives_1: 272.8077 - false_positives_1: 298.1538 - loss: 0.3981
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 308.7778 - false_positives_1: 400.2222 - loss: 0.4474 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8281 - false_negatives_1: 281.5555 - false_positives_1: 308.5555 - loss: 0.3974
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 319.5714 - false_positives_1: 414.2500 - loss: 0.4474 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8287 - false_negatives_1: 289.8214 - false_positives_1: 319.0000 - loss: 0.3968
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 330.3103 - false_positives_1: 428.0690 - loss: 0.4474 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8292 - false_negatives_1: 298.8276 - false_positives_1: 329.1724 - loss: 0.3963
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8039 - false_negatives_1: 341.3333 - false_positives_1: 441.4667 - loss: 0.4474 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8297 - false_negatives_1: 307.5667 - false_positives_1: 339.8000 - loss: 0.3958
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8040 - false_negatives_1: 352.0323 - false_positives_1: 455.1613 - loss: 0.4474 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8301 - false_negatives_1: 316.2903 - false_positives_1: 350.2258 - loss: 0.3953
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8040 - false_negatives_1: 363.7188 - false_positives_1: 468.3125 - loss: 0.4474 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8306 - false_negatives_1: 324.8125 - false_positives_1: 360.5938 - loss: 0.3947
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8039 - false_negatives_1: 374.7273 - false_positives_1: 483.1515 - loss: 0.4476 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8310 - false_negatives_1: 333.2424 - false_positives_1: 370.9394 - loss: 0.3942
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8038 - false_negatives_1: 385.8824 - false_positives_1: 497.8235 - loss: 0.4479 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8315 - false_negatives_1: 341.7353 - false_positives_1: 381.1471 - loss: 0.3936
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8037 - false_negatives_1: 396.9714 - false_positives_1: 512.4572 - loss: 0.4481 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8319 - false_negatives_1: 350.2000 - false_positives_1: 391.3143 - loss: 0.3931
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8036 - false_negatives_1: 408.3889 - false_positives_1: 526.6389 - loss: 0.4482 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8323 - false_negatives_1: 358.6389 - false_positives_1: 401.7222 - loss: 0.3926
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8036 - false_negatives_1: 419.6216 - false_positives_1: 540.8649 - loss: 0.4484 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8327 - false_negatives_1: 367.1892 - false_positives_1: 411.9730 - loss: 0.3921
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8035 - false_negatives_1: 430.7368 - false_positives_1: 555.0000 - loss: 0.4484 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8330 - false_negatives_1: 375.6842 - false_positives_1: 422.2368 - loss: 0.3916
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8035 - false_negatives_1: 441.5385 - false_positives_1: 569.3589 - loss: 0.4485 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8334 - false_negatives_1: 384.1282 - false_positives_1: 432.2820 - loss: 0.3911
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8035 - false_negatives_1: 453.3000 - false_positives_1: 583.1250 - loss: 0.4486 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8338 - false_negatives_1: 392.5250 - false_positives_1: 442.4250 - loss: 0.3906
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8033 - false_negatives_1: 464.5366 - false_positives_1: 598.4146 - loss: 0.4488 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8341 - false_negatives_1: 400.9024 - false_positives_1: 452.4146 - loss: 0.3901
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8032 - false_negatives_1: 475.7381 - false_positives_1: 613.6429 - loss: 0.4491 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8344 - false_negatives_1: 409.0714 - false_positives_1: 463.2381 - loss: 0.3898
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8031 - false_negatives_1: 487.0000 - false_positives_1: 628.7442 - loss: 0.4493 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8346 - false_negatives_1: 419.0698 - false_positives_1: 473.5581 - loss: 0.3897
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8030 - false_negatives_1: 498.2273 - false_positives_1: 643.8864 - loss: 0.4495 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8347 - false_negatives_1: 428.6591 - false_positives_1: 484.7273 - loss: 0.3898
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8029 - false_negatives_1: 509.5333 - false_positives_1: 658.9333 - loss: 0.4496 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8348 - false_negatives_1: 438.1778 - false_positives_1: 495.9556 - loss: 0.3898
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8028 - false_negatives_1: 520.8696 - false_positives_1: 673.9565 - loss: 0.4498 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8349 - false_negatives_1: 447.5217 - false_positives_1: 507.3696 - loss: 0.3899
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8027 - false_negatives_1: 532.1702 - false_positives_1: 688.8298 - loss: 0.4499 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8350 - false_negatives_1: 456.9575 - false_positives_1: 518.6383 - loss: 0.3899
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8026 - false_negatives_1: 543.5000 - false_positives_1: 703.6458 - loss: 0.4501 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8351 - false_negatives_1: 466.2500 - false_positives_1: 530.0417 - loss: 0.3899
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8025 - false_negatives_1: 554.6938 - false_positives_1: 718.5306 - loss: 0.4502 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8352 - false_negatives_1: 475.7347 - false_positives_1: 541.1633 - loss: 0.3899
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8024 - false_negatives_1: 566.0400 - false_positives_1: 733.0800 - loss: 0.4503 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8353 - false_negatives_1: 485.0800 - false_positives_1: 552.3800 - loss: 0.3900
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8024 - false_negatives_1: 577.1765 - false_positives_1: 747.8431 - loss: 0.4504 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8354 - false_negatives_1: 494.3922 - false_positives_1: 563.4706 - loss: 0.3900
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8023 - false_negatives_1: 588.7885 - false_positives_1: 762.2692 - loss: 0.4504 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8355 - false_negatives_1: 503.6923 - false_positives_1: 574.4808 - loss: 0.3900
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8022 - false_negatives_1: 600.0377 - false_positives_1: 777.3585 - loss: 0.4506 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8357 - false_negatives_1: 512.8868 - false_positives_1: 585.5283 - loss: 0.3900
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8021 - false_negatives_1: 611.3148 - false_positives_1: 792.2778 - loss: 0.4507 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8358 - false_negatives_1: 522.0555 - false_positives_1: 596.4259 - loss: 0.3899
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8020 - false_negatives_1: 622.4182 - false_positives_1: 807.5637 - loss: 0.4508 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8359 - false_negatives_1: 530.9636 - false_positives_1: 607.2182 - loss: 0.3899
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8020 - false_negatives_1: 633.8571 - false_positives_1: 822.4464 - loss: 0.4509 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8361 - false_negatives_1: 539.9821 - false_positives_1: 617.9286 - loss: 0.3898
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8019 - false_negatives_1: 645.0702 - false_positives_1: 837.4737 - loss: 0.4511 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8362 - false_negatives_1: 548.9123 - false_positives_1: 628.5965 - loss: 0.3897
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8018 - false_negatives_1: 656.2931 - false_positives_1: 852.3965 - loss: 0.4512 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8363 - false_negatives_1: 557.8793 - false_positives_1: 639.2931 - loss: 0.3896
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8018 - false_negatives_1: 667.3220 - false_positives_1: 867.1017 - loss: 0.4513 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8365 - false_negatives_1: 566.7288 - false_positives_1: 649.9322 - loss: 0.3896
``` -Epoch 5: val_loss improved from 0.45039 to 0.40482, saving model to AL_Model.keras +Epoch 8: val_loss did not improve from 0.39680  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8017 - false_negatives_1: 677.9833 - false_positives_1: 881.3167 - loss: 0.4514 - val_binary_accuracy: 0.8236 - val_false_negatives_1: 379.0000 - val_false_positives_1: 503.0000 - val_loss: 0.4048 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8366 - false_negatives_1: 575.2833 - false_positives_1: 660.2167 - loss: 0.3895 - val_binary_accuracy: 0.8216 - val_false_negatives_1: 623.0000 - val_false_positives_1: 269.0000 - val_loss: 0.4043
``` -Epoch 6/20 +Epoch 9/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 86ms/step - binary_accuracy: 0.8164 - false_negatives_1: 17.0000 - false_positives_1: 30.0000 - loss: 0.4093 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8516 - false_negatives_1: 33.0000 - false_positives_1: 5.0000 - loss: 0.3544
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8223 - false_negatives_1: 30.5000 - false_positives_1: 37.0000 - loss: 0.4114 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8467 - false_negatives_1: 33.5000 - false_positives_1: 26.0000 - loss: 0.3685
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8216 - false_negatives_1: 38.0000 - false_positives_1: 53.0000 - loss: 0.4151 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8392 - false_negatives_1: 50.0000 - false_positives_1: 34.6667 - loss: 0.3813
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8210 - false_negatives_1: 50.0000 - false_positives_1: 64.5000 - loss: 0.4183 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8357 - false_negatives_1: 59.7500 - false_positives_1: 48.5000 - loss: 0.3864
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8187 - false_negatives_1: 58.6000 - false_positives_1: 81.8000 - loss: 0.4216 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8345 - false_negatives_1: 70.0000 - false_positives_1: 60.2000 - loss: 0.3876
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8160 - false_negatives_1: 72.5000 - false_positives_1: 95.0000 - loss: 0.4254 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8352 - false_negatives_1: 79.1667 - false_positives_1: 70.6667 - loss: 0.3864
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8136 - false_negatives_1: 83.1429 - false_positives_1: 111.8571 - loss: 0.4282 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8362 - false_negatives_1: 87.0000 - false_positives_1: 81.8571 - loss: 0.3849
``` - + ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8122 - false_negatives_1: 93.8750 - false_positives_1: 127.3750 - loss: 0.4301 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8376 - false_negatives_1: 95.0000 - false_positives_1: 91.7500 - loss: 0.3832
``` - + ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8112 - false_negatives_1: 104.7778 - false_positives_1: 142.2222 - loss: 0.4316 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8389 - false_negatives_1: 101.8889 - false_positives_1: 102.6667 - loss: 0.3820
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8105 - false_negatives_1: 115.3000 - false_positives_1: 157.3000 - loss: 0.4325 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8397 - false_negatives_1: 110.8000 - false_positives_1: 112.5000 - loss: 0.3811
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8101 - false_negatives_1: 125.3636 - false_positives_1: 171.9091 - loss: 0.4328 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8407 - false_negatives_1: 118.7273 - false_positives_1: 122.5455 - loss: 0.3801
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8096 - false_negatives_1: 136.5833 - false_positives_1: 186.1667 - loss: 0.4335 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8418 - false_negatives_1: 126.1667 - false_positives_1: 132.3333 - loss: 0.3785
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8092 - false_negatives_1: 146.5385 - false_positives_1: 201.3077 - loss: 0.4341 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8430 - false_negatives_1: 133.3846 - false_positives_1: 141.7692 - loss: 0.3766
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8092 - false_negatives_1: 157.2143 - false_positives_1: 214.7143 - loss: 0.4341 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8441 - false_negatives_1: 141.0000 - false_positives_1: 150.7143 - loss: 0.3749
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8093 - false_negatives_1: 167.0000 - false_positives_1: 228.6000 - loss: 0.4339 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8449 - false_negatives_1: 148.0000 - false_positives_1: 160.9333 - loss: 0.3736
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8093 - false_negatives_1: 178.3750 - false_positives_1: 241.3750 - loss: 0.4336 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8455 - false_negatives_1: 156.8750 - false_positives_1: 170.0000 - loss: 0.3727
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8093 - false_negatives_1: 188.7059 - false_positives_1: 255.2353 - loss: 0.4334 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8458 - false_negatives_1: 164.7647 - false_positives_1: 181.2941 - loss: 0.3724
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8094 - false_negatives_1: 199.5556 - false_positives_1: 268.0555 - loss: 0.4331 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8461 - false_negatives_1: 173.1667 - false_positives_1: 191.8333 - loss: 0.3721
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8095 - false_negatives_1: 209.8947 - false_positives_1: 281.4211 - loss: 0.4328 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8465 - false_negatives_1: 181.2105 - false_positives_1: 201.9474 - loss: 0.3717
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8096 - false_negatives_1: 220.3500 - false_positives_1: 294.7500 - loss: 0.4325 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8470 - false_negatives_1: 188.9500 - false_positives_1: 212.0500 - loss: 0.3712
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8097 - false_negatives_1: 230.7143 - false_positives_1: 308.0000 - loss: 0.4322 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8473 - false_negatives_1: 197.6190 - false_positives_1: 221.6667 - loss: 0.3708
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8099 - false_negatives_1: 240.7273 - false_positives_1: 321.0000 - loss: 0.4318 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8477 - false_negatives_1: 206.0000 - false_positives_1: 231.1818 - loss: 0.3703
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8102 - false_negatives_1: 250.9130 - false_positives_1: 333.3478 - loss: 0.4314 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8481 - false_negatives_1: 214.2174 - false_positives_1: 240.5652 - loss: 0.3699
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 260.3750 - false_positives_1: 346.9583 - loss: 0.4311 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8485 - false_negatives_1: 222.3333 - false_positives_1: 250.0417 - loss: 0.3695
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 272.0000 - false_positives_1: 359.4800 - loss: 0.4310 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8489 - false_negatives_1: 230.2400 - false_positives_1: 259.3200 - loss: 0.3690
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 282.8462 - false_positives_1: 372.9231 - loss: 0.4310 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8493 - false_negatives_1: 238.0769 - false_positives_1: 268.7308 - loss: 0.3684
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 293.6667 - false_positives_1: 386.2963 - loss: 0.4309 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8496 - false_negatives_1: 246.0741 - false_positives_1: 278.2592 - loss: 0.3679
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 304.3929 - false_positives_1: 399.7500 - loss: 0.4309 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8499 - false_negatives_1: 254.1786 - false_positives_1: 287.9643 - loss: 0.3675
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8104 - false_negatives_1: 315.3103 - false_positives_1: 413.2414 - loss: 0.4309 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8502 - false_negatives_1: 262.0690 - false_positives_1: 297.5517 - loss: 0.3671
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8104 - false_negatives_1: 325.8333 - false_positives_1: 426.8333 - loss: 0.4308 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8505 - false_negatives_1: 270.0667 - false_positives_1: 306.8667 - loss: 0.3667
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8105 - false_negatives_1: 336.3871 - false_positives_1: 440.0000 - loss: 0.4307 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8508 - false_negatives_1: 277.7419 - false_positives_1: 316.6452 - loss: 0.3663
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8105 - false_negatives_1: 347.0312 - false_positives_1: 453.1250 - loss: 0.4306 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8510 - false_negatives_1: 286.5312 - false_positives_1: 325.9062 - loss: 0.3661
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8106 - false_negatives_1: 357.5151 - false_positives_1: 466.3333 - loss: 0.4304 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8511 - false_negatives_1: 294.9091 - false_positives_1: 336.0909 - loss: 0.3659
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8107 - false_negatives_1: 367.8824 - false_positives_1: 479.0882 - loss: 0.4303 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8512 - false_negatives_1: 303.4412 - false_positives_1: 346.0588 - loss: 0.3657
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8109 - false_negatives_1: 377.8571 - false_positives_1: 492.2571 - loss: 0.4301 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8514 - false_negatives_1: 311.7714 - false_positives_1: 355.9143 - loss: 0.3655
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8110 - false_negatives_1: 388.4167 - false_positives_1: 504.8333 - loss: 0.4299 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8515 - false_negatives_1: 320.1389 - false_positives_1: 365.9722 - loss: 0.3653
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8111 - false_negatives_1: 398.6487 - false_positives_1: 517.9459 - loss: 0.4298 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8516 - false_negatives_1: 328.7838 - false_positives_1: 375.8108 - loss: 0.3651
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8112 - false_negatives_1: 409.0526 - false_positives_1: 530.7105 - loss: 0.4296 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8517 - false_negatives_1: 337.2632 - false_positives_1: 385.8158 - loss: 0.3650
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8113 - false_negatives_1: 419.1026 - false_positives_1: 543.5128 - loss: 0.4295 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8518 - false_negatives_1: 345.9487 - false_positives_1: 395.6923 - loss: 0.3649
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8115 - false_negatives_1: 429.1250 - false_positives_1: 555.9250 - loss: 0.4292 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8519 - false_negatives_1: 354.5750 - false_positives_1: 405.4500 - loss: 0.3647
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8117 - false_negatives_1: 439.0488 - false_positives_1: 568.1707 - loss: 0.4289 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8520 - false_negatives_1: 363.1951 - false_positives_1: 415.1951 - loss: 0.3646
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8119 - false_negatives_1: 448.9524 - false_positives_1: 580.2381 - loss: 0.4286 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8521 - false_negatives_1: 371.7619 - false_positives_1: 424.9762 - loss: 0.3644
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8121 - false_negatives_1: 458.6279 - false_positives_1: 592.5582 - loss: 0.4284 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8522 - false_negatives_1: 380.3023 - false_positives_1: 434.7675 - loss: 0.3643
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8123 - false_negatives_1: 468.4546 - false_positives_1: 604.6364 - loss: 0.4281 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8522 - false_negatives_1: 388.9091 - false_positives_1: 444.3864 - loss: 0.3641
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8125 - false_negatives_1: 478.0222 - false_positives_1: 616.8889 - loss: 0.4278 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8523 - false_negatives_1: 397.4667 - false_positives_1: 454.2000 - loss: 0.3640
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8127 - false_negatives_1: 488.0435 - false_positives_1: 628.8261 - loss: 0.4276 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8524 - false_negatives_1: 406.4783 - false_positives_1: 463.7609 - loss: 0.3639
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8128 - false_negatives_1: 497.6383 - false_positives_1: 641.8723 - loss: 0.4274 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8525 - false_negatives_1: 415.1702 - false_positives_1: 473.5107 - loss: 0.3638
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8129 - false_negatives_1: 507.9792 - false_positives_1: 654.5000 - loss: 0.4273 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8525 - false_negatives_1: 424.0208 - false_positives_1: 483.1875 - loss: 0.3638
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8130 - false_negatives_1: 518.0816 - false_positives_1: 667.2857 - loss: 0.4272 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8526 - false_negatives_1: 432.7347 - false_positives_1: 492.7551 - loss: 0.3637
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8131 - false_negatives_1: 528.2000 - false_positives_1: 679.9400 - loss: 0.4271 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8527 - false_negatives_1: 441.2600 - false_positives_1: 502.3200 - loss: 0.3635
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8133 - false_negatives_1: 538.0588 - false_positives_1: 692.5098 - loss: 0.4270 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8528 - false_negatives_1: 449.9412 - false_positives_1: 511.9019 - loss: 0.3634
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8134 - false_negatives_1: 547.9231 - false_positives_1: 704.9615 - loss: 0.4268 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8528 - false_negatives_1: 458.3654 - false_positives_1: 521.8269 - loss: 0.3633
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8136 - false_negatives_1: 557.6604 - false_positives_1: 717.3396 - loss: 0.4267 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8529 - false_negatives_1: 467.2453 - false_positives_1: 531.4528 - loss: 0.3633
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8137 - false_negatives_1: 567.5926 - false_positives_1: 729.5370 - loss: 0.4265 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8529 - false_negatives_1: 475.8704 - false_positives_1: 541.6111 - loss: 0.3633
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8138 - false_negatives_1: 577.3636 - false_positives_1: 741.8364 - loss: 0.4264 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8529 - false_negatives_1: 484.6545 - false_positives_1: 551.5455 - loss: 0.3632
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8140 - false_negatives_1: 587.3036 - false_positives_1: 753.8929 - loss: 0.4263 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8530 - false_negatives_1: 493.2500 - false_positives_1: 561.6607 - loss: 0.3632
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8141 - false_negatives_1: 597.0702 - false_positives_1: 766.3684 - loss: 0.4261 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8530 - false_negatives_1: 501.9474 - false_positives_1: 571.5965 - loss: 0.3632
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8142 - false_negatives_1: 607.0690 - false_positives_1: 778.6207 - loss: 0.4260 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8530 - false_negatives_1: 510.4828 - false_positives_1: 581.7069 - loss: 0.3632
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8144 - false_negatives_1: 616.8475 - false_positives_1: 790.7797 - loss: 0.4259 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8531 - false_negatives_1: 519.0170 - false_positives_1: 591.6440 - loss: 0.3631
``` -Epoch 6: val_loss improved from 0.40482 to 0.40126, saving model to AL_Model.keras +Epoch 9: val_loss improved from 0.39680 to 0.37727, saving model to AL_Model.keras  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8145 - false_negatives_1: 626.3000 - false_positives_1: 802.5333 - loss: 0.4257 - val_binary_accuracy: 0.8230 - val_false_negatives_1: 603.0000 - val_false_positives_1: 282.0000 - val_loss: 0.4013 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8531 - false_negatives_1: 527.2667 - false_positives_1: 601.2500 - loss: 0.3631 - val_binary_accuracy: 0.8348 - val_false_negatives_1: 296.0000 - val_false_positives_1: 530.0000 - val_loss: 0.3773
``` -Epoch 7/20 +Epoch 10/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 86ms/step - binary_accuracy: 0.8555 - false_negatives_1: 27.0000 - false_positives_1: 10.0000 - loss: 0.3358 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 86ms/step - binary_accuracy: 0.9141 - false_negatives_1: 8.0000 - false_positives_1: 14.0000 - loss: 0.2965
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8506 - false_negatives_1: 30.5000 - false_positives_1: 27.5000 - loss: 0.3434 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.9121 - false_negatives_1: 12.5000 - false_positives_1: 21.5000 - loss: 0.3008
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8457 - false_negatives_1: 44.3333 - false_positives_1: 36.3333 - loss: 0.3534 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9076 - false_negatives_1: 18.6667 - false_positives_1: 30.0000 - loss: 0.3022
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8430 - false_negatives_1: 52.7500 - false_positives_1: 50.0000 - loss: 0.3605 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9067 - false_negatives_1: 24.2500 - false_positives_1: 36.7500 - loss: 0.3006
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8433 - false_negatives_1: 61.6000 - false_positives_1: 60.4000 - loss: 0.3629 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9051 - false_negatives_1: 29.6000 - false_positives_1: 45.2000 - loss: 0.3013
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8430 - false_negatives_1: 69.1667 - false_positives_1: 73.1667 - loss: 0.3652 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9019 - false_negatives_1: 38.3333 - false_positives_1: 53.1667 - loss: 0.3036
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8424 - false_negatives_1: 78.4286 - false_positives_1: 84.8571 - loss: 0.3668 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8982 - false_negatives_1: 45.1429 - false_positives_1: 65.0000 - loss: 0.3074
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8419 - false_negatives_1: 87.1250 - false_positives_1: 97.0000 - loss: 0.3686 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8943 - false_negatives_1: 55.8750 - false_positives_1: 74.5000 - loss: 0.3122
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8417 - false_negatives_1: 96.7778 - false_positives_1: 107.7778 - loss: 0.3696 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8911 - false_negatives_1: 65.5556 - false_positives_1: 84.8889 - loss: 0.3164
``` - + ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8416 - false_negatives_1: 105.7000 - false_positives_1: 119.3000 - loss: 0.3704 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8888 - false_negatives_1: 74.7000 - false_positives_1: 94.4000 - loss: 0.3194
``` - + ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8415 - false_negatives_1: 115.2727 - false_positives_1: 130.0000 - loss: 0.3708 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8870 - false_negatives_1: 82.7273 - false_positives_1: 104.6364 - loss: 0.3218
``` - + ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8415 - false_negatives_1: 123.6667 - false_positives_1: 141.7500 - loss: 0.3711 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8853 - false_negatives_1: 91.2500 - false_positives_1: 114.5000 - loss: 0.3238
``` - + ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8413 - false_negatives_1: 133.1538 - false_positives_1: 153.0769 - loss: 0.3717 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_1: 98.7692 - false_positives_1: 124.2308 - loss: 0.3251
``` - + ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8415 - false_negatives_1: 142.0000 - false_positives_1: 163.8571 - loss: 0.3718 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8834 - false_negatives_1: 106.3571 - false_positives_1: 133.2857 - loss: 0.3260
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8414 - false_negatives_1: 152.0667 - false_positives_1: 174.1333 - loss: 0.3721 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8828 - false_negatives_1: 113.2667 - false_positives_1: 142.6000 - loss: 0.3266
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8410 - false_negatives_1: 160.9375 - false_positives_1: 187.1875 - loss: 0.3732 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8822 - false_negatives_1: 120.4375 - false_positives_1: 151.8125 - loss: 0.3271
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8402 - false_negatives_1: 172.8235 - false_positives_1: 198.8824 - loss: 0.3747 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8816 - false_negatives_1: 127.8235 - false_positives_1: 161.2941 - loss: 0.3275
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8396 - false_negatives_1: 183.6111 - false_positives_1: 211.3889 - loss: 0.3761 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8811 - false_negatives_1: 134.7778 - false_positives_1: 171.0000 - loss: 0.3279
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8391 - false_negatives_1: 194.0000 - false_positives_1: 223.4211 - loss: 0.3771 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8807 - false_negatives_1: 141.7895 - false_positives_1: 180.2105 - loss: 0.3281
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8388 - false_negatives_1: 204.2500 - false_positives_1: 235.3500 - loss: 0.3780 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8803 - false_negatives_1: 148.5500 - false_positives_1: 189.7500 - loss: 0.3283
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8385 - false_negatives_1: 214.6190 - false_positives_1: 246.9048 - loss: 0.3788 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8799 - false_negatives_1: 156.3810 - false_positives_1: 198.6667 - loss: 0.3286
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8381 - false_negatives_1: 224.6818 - false_positives_1: 259.0909 - loss: 0.3795 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8793 - false_negatives_1: 163.5000 - false_positives_1: 209.4545 - loss: 0.3292
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8379 - false_negatives_1: 235.2174 - false_positives_1: 270.6522 - loss: 0.3801 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8785 - false_negatives_1: 173.0000 - false_positives_1: 219.4348 - loss: 0.3300
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8376 - false_negatives_1: 245.3333 - false_positives_1: 282.2917 - loss: 0.3807 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8778 - false_negatives_1: 182.0000 - false_positives_1: 229.5833 - loss: 0.3307
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8375 - false_negatives_1: 255.3200 - false_positives_1: 293.7200 - loss: 0.3811 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8771 - false_negatives_1: 190.8800 - false_positives_1: 239.7200 - loss: 0.3313
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8374 - false_negatives_1: 265.1538 - false_positives_1: 305.0000 - loss: 0.3815 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8765 - false_negatives_1: 199.7308 - false_positives_1: 249.6538 - loss: 0.3319
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8373 - false_negatives_1: 274.8889 - false_positives_1: 316.1852 - loss: 0.3818 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8760 - false_negatives_1: 208.3333 - false_positives_1: 259.7778 - loss: 0.3323
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8372 - false_negatives_1: 284.5357 - false_positives_1: 327.7500 - loss: 0.3821 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8755 - false_negatives_1: 216.8571 - false_positives_1: 269.7500 - loss: 0.3327
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8372 - false_negatives_1: 294.2414 - false_positives_1: 339.1379 - loss: 0.3823 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8750 - false_negatives_1: 225.2414 - false_positives_1: 279.8965 - loss: 0.3331
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8372 - false_negatives_1: 303.5000 - false_positives_1: 350.5667 - loss: 0.3825 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8746 - false_negatives_1: 233.9000 - false_positives_1: 289.7667 - loss: 0.3334
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8371 - false_negatives_1: 313.4193 - false_positives_1: 361.5807 - loss: 0.3827 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8742 - false_negatives_1: 242.3871 - false_positives_1: 299.7742 - loss: 0.3338
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8370 - false_negatives_1: 322.8750 - false_positives_1: 373.8125 - loss: 0.3830 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8738 - false_negatives_1: 251.1562 - false_positives_1: 309.6562 - loss: 0.3342
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8368 - false_negatives_1: 332.8788 - false_positives_1: 385.6970 - loss: 0.3833 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8734 - false_negatives_1: 259.6060 - false_positives_1: 319.9697 - loss: 0.3345
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8367 - false_negatives_1: 342.7353 - false_positives_1: 397.5882 - loss: 0.3836 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8730 - false_negatives_1: 268.2353 - false_positives_1: 329.7941 - loss: 0.3349
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8366 - false_negatives_1: 352.5428 - false_positives_1: 409.4286 - loss: 0.3839 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8727 - false_negatives_1: 276.6000 - false_positives_1: 339.9714 - loss: 0.3352
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8365 - false_negatives_1: 362.0278 - false_positives_1: 421.4167 - loss: 0.3841 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8723 - false_negatives_1: 285.3055 - false_positives_1: 349.8055 - loss: 0.3356
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8364 - false_negatives_1: 371.3784 - false_positives_1: 433.7027 - loss: 0.3843 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8720 - false_negatives_1: 293.5946 - false_positives_1: 359.8649 - loss: 0.3359
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8363 - false_negatives_1: 381.2368 - false_positives_1: 445.6053 - loss: 0.3846 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8717 - false_negatives_1: 302.2632 - false_positives_1: 369.6316 - loss: 0.3363
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8361 - false_negatives_1: 390.6923 - false_positives_1: 458.5128 - loss: 0.3849 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8715 - false_negatives_1: 310.6154 - false_positives_1: 379.4359 - loss: 0.3365
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8359 - false_negatives_1: 400.9500 - false_positives_1: 470.9000 - loss: 0.3852 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 318.9250 - false_positives_1: 389.0000 - loss: 0.3368
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8358 - false_negatives_1: 410.8293 - false_positives_1: 483.7561 - loss: 0.3856 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8711 - false_negatives_1: 327.1219 - false_positives_1: 398.5122 - loss: 0.3369
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8356 - false_negatives_1: 420.6190 - false_positives_1: 496.4762 - loss: 0.3859 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8709 - false_negatives_1: 335.0000 - false_positives_1: 408.0952 - loss: 0.3371
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8354 - false_negatives_1: 430.3954 - false_positives_1: 509.0233 - loss: 0.3861 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8707 - false_negatives_1: 343.3721 - false_positives_1: 417.3256 - loss: 0.3372
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8353 - false_negatives_1: 440.1591 - false_positives_1: 521.5000 - loss: 0.3863 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8706 - false_negatives_1: 351.4546 - false_positives_1: 426.8182 - loss: 0.3373
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8352 - false_negatives_1: 449.8667 - false_positives_1: 534.0444 - loss: 0.3865 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8704 - false_negatives_1: 359.8000 - false_positives_1: 436.1111 - loss: 0.3374
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8351 - false_negatives_1: 459.5217 - false_positives_1: 546.4783 - loss: 0.3867 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8703 - false_negatives_1: 368.0217 - false_positives_1: 445.7391 - loss: 0.3376
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8350 - false_negatives_1: 469.2766 - false_positives_1: 558.7021 - loss: 0.3869 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8701 - false_negatives_1: 376.3617 - false_positives_1: 455.1277 - loss: 0.3377
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8349 - false_negatives_1: 478.8125 - false_positives_1: 571.4167 - loss: 0.3871 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8700 - false_negatives_1: 384.6042 - false_positives_1: 464.7083 - loss: 0.3378
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8347 - false_negatives_1: 489.0000 - false_positives_1: 583.7143 - loss: 0.3874 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8698 - false_negatives_1: 392.9184 - false_positives_1: 474.2653 - loss: 0.3379
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8346 - false_negatives_1: 498.8400 - false_positives_1: 596.8600 - loss: 0.3877 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8697 - false_negatives_1: 401.3600 - false_positives_1: 483.7200 - loss: 0.3380
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8344 - false_negatives_1: 509.3333 - false_positives_1: 609.6667 - loss: 0.3880 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8695 - false_negatives_1: 409.6471 - false_positives_1: 493.3333 - loss: 0.3381
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8342 - false_negatives_1: 519.4423 - false_positives_1: 622.6731 - loss: 0.3883 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8694 - false_negatives_1: 418.1538 - false_positives_1: 502.6923 - loss: 0.3382
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8341 - false_negatives_1: 529.6604 - false_positives_1: 635.4528 - loss: 0.3886 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8692 - false_negatives_1: 426.4340 - false_positives_1: 512.4905 - loss: 0.3383
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8339 - false_negatives_1: 539.6667 - false_positives_1: 648.1852 - loss: 0.3889 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8691 - false_negatives_1: 434.8333 - false_positives_1: 522.0555 - loss: 0.3384
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8338 - false_negatives_1: 549.6545 - false_positives_1: 660.8182 - loss: 0.3891 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8690 - false_negatives_1: 443.1273 - false_positives_1: 531.5455 - loss: 0.3385
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8337 - false_negatives_1: 559.4821 - false_positives_1: 673.2500 - loss: 0.3893 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8689 - false_negatives_1: 451.4464 - false_positives_1: 540.9821 - loss: 0.3386
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8336 - false_negatives_1: 569.1754 - false_positives_1: 685.5965 - loss: 0.3895 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8688 - false_negatives_1: 459.7018 - false_positives_1: 550.4386 - loss: 0.3386
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8336 - false_negatives_1: 578.8276 - false_positives_1: 697.7759 - loss: 0.3897 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8687 - false_negatives_1: 467.8276 - false_positives_1: 559.8276 - loss: 0.3386
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8335 - false_negatives_1: 588.2712 - false_positives_1: 709.7627 - loss: 0.3899 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8686 - false_negatives_1: 475.7966 - false_positives_1: 569.0508 - loss: 0.3387
``` -Epoch 7: val_loss improved from 0.40126 to 0.37307, saving model to AL_Model.keras +Epoch 10: val_loss improved from 0.37727 to 0.37354, saving model to AL_Model.keras  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 85ms/step - binary_accuracy: 0.8335 - false_negatives_1: 597.4000 - false_positives_1: 721.3500 - loss: 0.3900 - val_binary_accuracy: 0.8408 - val_false_negatives_1: 389.0000 - val_false_positives_1: 407.0000 - val_loss: 0.3731 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8685 - false_negatives_1: 483.5000 - false_positives_1: 577.9667 - loss: 0.3387 - val_binary_accuracy: 0.8400 - val_false_negatives_1: 327.0000 - val_false_positives_1: 473.0000 - val_loss: 0.3735
``` -Epoch 8/20 +Epoch 11/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 87ms/step - binary_accuracy: 0.8711 - false_negatives_1: 13.0000 - false_positives_1: 20.0000 - loss: 0.3246 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 85ms/step - binary_accuracy: 0.8906 - false_negatives_1: 8.0000 - false_positives_1: 20.0000 - loss: 0.2813
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8682 - false_negatives_1: 23.0000 - false_positives_1: 28.0000 - loss: 0.3232 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8818 - false_negatives_1: 23.0000 - false_positives_1: 23.5000 - loss: 0.3083
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8683 - false_negatives_1: 29.6667 - false_positives_1: 38.0000 - loss: 0.3227 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 29.0000 - false_positives_1: 40.3333 - loss: 0.3302
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8673 - false_negatives_1: 40.0000 - false_positives_1: 45.5000 - loss: 0.3257 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8642 - false_negatives_1: 41.5000 - false_positives_1: 50.7500 - loss: 0.3430
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8676 - false_negatives_1: 47.4000 - false_positives_1: 54.6000 - loss: 0.3267 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8615 - false_negatives_1: 51.2000 - false_positives_1: 60.8000 - loss: 0.3477
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8674 - false_negatives_1: 56.3333 - false_positives_1: 62.8333 - loss: 0.3290 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8607 - false_negatives_1: 60.6667 - false_positives_1: 69.3333 - loss: 0.3492
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8657 - false_negatives_1: 63.2857 - false_positives_1: 75.8571 - loss: 0.3328 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8608 - false_negatives_1: 68.1429 - false_positives_1: 78.8571 - loss: 0.3489
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8630 - false_negatives_1: 75.1250 - false_positives_1: 86.5000 - loss: 0.3377 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8610 - false_negatives_1: 76.0000 - false_positives_1: 87.7500 - loss: 0.3484
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8603 - false_negatives_1: 84.8889 - false_positives_1: 100.1111 - loss: 0.3425 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8616 - false_negatives_1: 82.8889 - false_positives_1: 96.8889 - loss: 0.3474
``` - + ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8586 - false_negatives_1: 94.4000 - false_positives_1: 112.2000 - loss: 0.3457 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8621 - false_negatives_1: 91.4000 - false_positives_1: 104.6000 - loss: 0.3469
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8575 - false_negatives_1: 103.3636 - false_positives_1: 123.6364 - loss: 0.3479 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8624 - false_negatives_1: 98.7273 - false_positives_1: 113.8182 - loss: 0.3465
``` - + ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 111.7500 - false_positives_1: 134.0000 - loss: 0.3492 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8631 - false_negatives_1: 106.0000 - false_positives_1: 122.0000 - loss: 0.3455
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 120.2308 - false_positives_1: 143.7692 - loss: 0.3500 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8639 - false_negatives_1: 112.6923 - false_positives_1: 130.0000 - loss: 0.3444
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 128.2857 - false_positives_1: 153.2143 - loss: 0.3504 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8648 - false_negatives_1: 119.5714 - false_positives_1: 137.6429 - loss: 0.3432
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 136.6000 - false_positives_1: 162.4667 - loss: 0.3506 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8655 - false_negatives_1: 126.1333 - false_positives_1: 145.6667 - loss: 0.3422
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 144.7500 - false_positives_1: 172.1250 - loss: 0.3508 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8661 - false_negatives_1: 133.5625 - false_positives_1: 153.1875 - loss: 0.3414
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8572 - false_negatives_1: 152.8235 - false_positives_1: 181.5882 - loss: 0.3510 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8667 - false_negatives_1: 140.2941 - false_positives_1: 161.4118 - loss: 0.3405
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8573 - false_negatives_1: 160.6667 - false_positives_1: 191.2222 - loss: 0.3511 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8671 - false_negatives_1: 147.7778 - false_positives_1: 169.3889 - loss: 0.3398
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8575 - false_negatives_1: 168.5789 - false_positives_1: 200.3684 - loss: 0.3509 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8674 - false_negatives_1: 155.2632 - false_positives_1: 177.7895 - loss: 0.3393
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8577 - false_negatives_1: 175.9500 - false_positives_1: 210.3500 - loss: 0.3509 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8678 - false_negatives_1: 162.6000 - false_positives_1: 185.8000 - loss: 0.3386
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8575 - false_negatives_1: 185.7143 - false_positives_1: 219.4762 - loss: 0.3514 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8682 - false_negatives_1: 169.7143 - false_positives_1: 193.9048 - loss: 0.3378
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 194.6818 - false_positives_1: 231.2273 - loss: 0.3524 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8685 - false_negatives_1: 177.1364 - false_positives_1: 201.6364 - loss: 0.3371
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8565 - false_negatives_1: 204.0000 - false_positives_1: 242.9565 - loss: 0.3534 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8688 - false_negatives_1: 184.1739 - false_positives_1: 210.0435 - loss: 0.3365
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8561 - false_negatives_1: 213.0000 - false_positives_1: 254.6667 - loss: 0.3542 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8690 - false_negatives_1: 192.0833 - false_positives_1: 218.0000 - loss: 0.3360
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8557 - false_negatives_1: 222.0000 - false_positives_1: 266.2400 - loss: 0.3549 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8692 - false_negatives_1: 199.4400 - false_positives_1: 226.8000 - loss: 0.3356
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8554 - false_negatives_1: 230.8462 - false_positives_1: 277.8846 - loss: 0.3556 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8692 - false_negatives_1: 207.8846 - false_positives_1: 235.2308 - loss: 0.3353
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8551 - false_negatives_1: 239.8889 - false_positives_1: 289.1482 - loss: 0.3562 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8692 - false_negatives_1: 215.8148 - false_positives_1: 244.2593 - loss: 0.3352
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8548 - false_negatives_1: 248.8929 - false_positives_1: 300.2857 - loss: 0.3568 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8692 - false_negatives_1: 223.8571 - false_positives_1: 253.3214 - loss: 0.3351
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8545 - false_negatives_1: 258.0000 - false_positives_1: 311.2414 - loss: 0.3573 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8693 - false_negatives_1: 231.5862 - false_positives_1: 262.1379 - loss: 0.3350
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8543 - false_negatives_1: 266.9667 - false_positives_1: 322.2000 - loss: 0.3577 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8694 - false_negatives_1: 239.2667 - false_positives_1: 270.8333 - loss: 0.3349
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8542 - false_negatives_1: 275.5484 - false_positives_1: 333.0000 - loss: 0.3581 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8694 - false_negatives_1: 246.6129 - false_positives_1: 279.8387 - loss: 0.3347
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8541 - false_negatives_1: 284.6250 - false_positives_1: 343.3125 - loss: 0.3584 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8696 - false_negatives_1: 254.0625 - false_positives_1: 288.4688 - loss: 0.3345
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8539 - false_negatives_1: 293.3333 - false_positives_1: 354.4849 - loss: 0.3588 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8697 - false_negatives_1: 261.4546 - false_positives_1: 296.9697 - loss: 0.3343
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8537 - false_negatives_1: 302.5294 - false_positives_1: 365.3235 - loss: 0.3593 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8698 - false_negatives_1: 268.6176 - false_positives_1: 305.5000 - loss: 0.3340
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8535 - false_negatives_1: 311.4286 - false_positives_1: 376.2857 - loss: 0.3596 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8700 - false_negatives_1: 275.6571 - false_positives_1: 314.0571 - loss: 0.3337
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8534 - false_negatives_1: 320.1945 - false_positives_1: 387.0833 - loss: 0.3599 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8701 - false_negatives_1: 282.6667 - false_positives_1: 322.5000 - loss: 0.3334
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8532 - false_negatives_1: 329.0000 - false_positives_1: 398.1081 - loss: 0.3603 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8703 - false_negatives_1: 289.8108 - false_positives_1: 330.8378 - loss: 0.3332
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8531 - false_negatives_1: 338.0789 - false_positives_1: 408.9211 - loss: 0.3606 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8704 - false_negatives_1: 297.0000 - false_positives_1: 339.1579 - loss: 0.3329
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8529 - false_negatives_1: 346.8462 - false_positives_1: 420.3333 - loss: 0.3609 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8705 - false_negatives_1: 304.1026 - false_positives_1: 347.6410 - loss: 0.3327
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8528 - false_negatives_1: 356.0750 - false_positives_1: 431.3000 - loss: 0.3613 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8707 - false_negatives_1: 311.2750 - false_positives_1: 355.9500 - loss: 0.3324
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8526 - false_negatives_1: 365.0244 - false_positives_1: 442.5610 - loss: 0.3616 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8708 - false_negatives_1: 318.3171 - false_positives_1: 364.1951 - loss: 0.3322
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8524 - false_negatives_1: 374.0714 - false_positives_1: 453.7857 - loss: 0.3619 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives_1: 325.3333 - false_positives_1: 372.6429 - loss: 0.3319
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8523 - false_negatives_1: 382.9535 - false_positives_1: 465.1395 - loss: 0.3622 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8711 - false_negatives_1: 332.3954 - false_positives_1: 381.0930 - loss: 0.3317
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8521 - false_negatives_1: 391.8864 - false_positives_1: 476.1818 - loss: 0.3625 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8712 - false_negatives_1: 339.6136 - false_positives_1: 389.5454 - loss: 0.3315
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8520 - false_negatives_1: 400.5555 - false_positives_1: 487.6889 - loss: 0.3628 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 346.6222 - false_positives_1: 398.3111 - loss: 0.3313
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8518 - false_negatives_1: 410.1522 - false_positives_1: 498.8696 - loss: 0.3631 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 354.3913 - false_positives_1: 406.7391 - loss: 0.3311
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8516 - false_negatives_1: 419.4043 - false_positives_1: 510.5107 - loss: 0.3635 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 361.8511 - false_positives_1: 415.8936 - loss: 0.3311
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8515 - false_negatives_1: 428.5417 - false_positives_1: 521.9583 - loss: 0.3638 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8713 - false_negatives_1: 369.4375 - false_positives_1: 424.8333 - loss: 0.3310
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8513 - false_negatives_1: 437.6327 - false_positives_1: 533.3878 - loss: 0.3641 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8714 - false_negatives_1: 377.0816 - false_positives_1: 433.6735 - loss: 0.3309
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8512 - false_negatives_1: 446.8200 - false_positives_1: 544.6400 - loss: 0.3644 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8714 - false_negatives_1: 384.5600 - false_positives_1: 442.5400 - loss: 0.3309
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8511 - false_negatives_1: 455.8431 - false_positives_1: 555.8039 - loss: 0.3646 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8714 - false_negatives_1: 392.0981 - false_positives_1: 451.4314 - loss: 0.3308
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8509 - false_negatives_1: 464.8846 - false_positives_1: 566.8846 - loss: 0.3649 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8714 - false_negatives_1: 399.6731 - false_positives_1: 460.2308 - loss: 0.3307
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8509 - false_negatives_1: 473.7924 - false_positives_1: 577.9245 - loss: 0.3651 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8715 - false_negatives_1: 407.0000 - false_positives_1: 469.1509 - loss: 0.3306
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8508 - false_negatives_1: 482.8704 - false_positives_1: 588.7593 - loss: 0.3653 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8715 - false_negatives_1: 414.5370 - false_positives_1: 477.8148 - loss: 0.3306
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8507 - false_negatives_1: 491.7636 - false_positives_1: 600.0546 - loss: 0.3655 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8715 - false_negatives_1: 421.8909 - false_positives_1: 486.6545 - loss: 0.3305
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8505 - false_negatives_1: 501.1429 - false_positives_1: 611.0179 - loss: 0.3657 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8716 - false_negatives_1: 429.5000 - false_positives_1: 495.4286 - loss: 0.3304
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8504 - false_negatives_1: 510.3333 - false_positives_1: 622.3509 - loss: 0.3660 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8716 - false_negatives_1: 437.0877 - false_positives_1: 504.3684 - loss: 0.3304
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8503 - false_negatives_1: 519.5862 - false_positives_1: 633.5862 - loss: 0.3662 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8716 - false_negatives_1: 444.6379 - false_positives_1: 513.2759 - loss: 0.3304
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8502 - false_negatives_1: 528.6780 - false_positives_1: 644.6102 - loss: 0.3664 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8716 - false_negatives_1: 452.1356 - false_positives_1: 522.1187 - loss: 0.3303
``` -Epoch 8: val_loss did not improve from 0.37307 +Epoch 11: val_loss improved from 0.37354 to 0.37074, saving model to AL_Model.keras  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8501 - false_negatives_1: 537.4667 - false_positives_1: 655.2667 - loss: 0.3666 - val_binary_accuracy: 0.8316 - val_false_negatives_1: 250.0000 - val_false_positives_1: 592.0000 - val_loss: 0.3795 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8716 - false_negatives_1: 459.3833 - false_positives_1: 530.6667 - loss: 0.3303 - val_binary_accuracy: 0.8390 - val_false_negatives_1: 362.0000 - val_false_positives_1: 443.0000 - val_loss: 0.3707
``` -Epoch 9/20 +Epoch 12/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 90ms/step - binary_accuracy: 0.8789 - false_negatives_1: 7.0000 - false_positives_1: 24.0000 - loss: 0.3292 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 86ms/step - binary_accuracy: 0.9102 - false_negatives_1: 9.0000 - false_positives_1: 14.0000 - loss: 0.2477
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8730 - false_negatives_1: 16.5000 - false_positives_1: 33.0000 - loss: 0.3367 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.9150 - false_negatives_1: 13.5000 - false_positives_1: 18.5000 - loss: 0.2470
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8707 - false_negatives_1: 26.0000 - false_positives_1: 41.3333 - loss: 0.3380 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9160 - false_negatives_1: 18.3333 - false_positives_1: 24.0000 - loss: 0.2465
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8708 - false_negatives_1: 33.5000 - false_positives_1: 50.0000 - loss: 0.3358 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9111 - false_negatives_1: 26.7500 - false_positives_1: 31.5000 - loss: 0.2538
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8694 - false_negatives_1: 43.8000 - false_positives_1: 57.8000 - loss: 0.3359 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9091 - false_negatives_1: 33.4000 - false_positives_1: 38.6000 - loss: 0.2579
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8675 - false_negatives_1: 51.5000 - false_positives_1: 69.5000 - loss: 0.3376 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9075 - false_negatives_1: 41.1667 - false_positives_1: 44.5000 - loss: 0.2619
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8658 - false_negatives_1: 62.0000 - false_positives_1: 78.7143 - loss: 0.3397 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9057 - false_negatives_1: 47.2857 - false_positives_1: 53.1429 - loss: 0.2662
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8651 - false_negatives_1: 71.0000 - false_positives_1: 87.8750 - loss: 0.3406 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9035 - false_negatives_1: 56.2500 - false_positives_1: 60.1250 - loss: 0.2705
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8647 - false_negatives_1: 79.3333 - false_positives_1: 97.4444 - loss: 0.3409 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9010 - false_negatives_1: 63.6667 - false_positives_1: 70.2222 - loss: 0.2747
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8645 - false_negatives_1: 88.0000 - false_positives_1: 106.3000 - loss: 0.3413 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8987 - false_negatives_1: 73.1000 - false_positives_1: 78.7000 - loss: 0.2786
``` - + ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8643 - false_negatives_1: 95.6364 - false_positives_1: 116.0909 - loss: 0.3416 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8968 - false_negatives_1: 81.2727 - false_positives_1: 87.9091 - loss: 0.2815
``` - + ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8640 - false_negatives_1: 105.0000 - false_positives_1: 124.8333 - loss: 0.3421 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8955 - false_negatives_1: 89.0000 - false_positives_1: 96.5000 - loss: 0.2837
``` - + ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8635 - false_negatives_1: 113.6154 - false_positives_1: 135.0000 - loss: 0.3429 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8944 - false_negatives_1: 96.0000 - false_positives_1: 105.7692 - loss: 0.2857
``` - + ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8630 - false_negatives_1: 123.0000 - false_positives_1: 144.5714 - loss: 0.3436 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8934 - false_negatives_1: 103.2143 - false_positives_1: 114.8571 - loss: 0.2872
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8625 - false_negatives_1: 131.4000 - false_positives_1: 155.2000 - loss: 0.3443 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8924 - false_negatives_1: 110.8000 - false_positives_1: 123.7333 - loss: 0.2887
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8623 - false_negatives_1: 139.8750 - false_positives_1: 165.1250 - loss: 0.3447 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8916 - false_negatives_1: 118.1875 - false_positives_1: 132.6875 - loss: 0.2901
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8621 - false_negatives_1: 148.1176 - false_positives_1: 175.1176 - loss: 0.3449 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8909 - false_negatives_1: 125.6471 - false_positives_1: 141.0000 - loss: 0.2914
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8620 - false_negatives_1: 155.9444 - false_positives_1: 184.8889 - loss: 0.3449 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8904 - false_negatives_1: 132.7778 - false_positives_1: 149.5556 - loss: 0.2924
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8619 - false_negatives_1: 164.0526 - false_positives_1: 194.5263 - loss: 0.3448 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8899 - false_negatives_1: 140.2632 - false_positives_1: 157.6316 - loss: 0.2934
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8619 - false_negatives_1: 171.7000 - false_positives_1: 204.2500 - loss: 0.3446 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8893 - false_negatives_1: 147.2500 - false_positives_1: 167.0000 - loss: 0.2946
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8620 - false_negatives_1: 179.6190 - false_positives_1: 213.5714 - loss: 0.3444 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8885 - false_negatives_1: 156.3810 - false_positives_1: 175.5714 - loss: 0.2961
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8619 - false_negatives_1: 186.9545 - false_positives_1: 224.0455 - loss: 0.3443 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8877 - false_negatives_1: 165.0909 - false_positives_1: 184.5000 - loss: 0.2975
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8616 - false_negatives_1: 196.7391 - false_positives_1: 233.6522 - loss: 0.3449 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8871 - false_negatives_1: 173.5217 - false_positives_1: 193.1304 - loss: 0.2986
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8611 - false_negatives_1: 205.7917 - false_positives_1: 245.1250 - loss: 0.3456 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8867 - false_negatives_1: 181.5833 - false_positives_1: 201.5833 - loss: 0.2996
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8606 - false_negatives_1: 214.8400 - false_positives_1: 256.5600 - loss: 0.3463 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8863 - false_negatives_1: 189.4400 - false_positives_1: 209.8000 - loss: 0.3004
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8602 - false_negatives_1: 223.5769 - false_positives_1: 268.2308 - loss: 0.3470 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 197.0000 - false_positives_1: 218.1154 - loss: 0.3010
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8598 - false_negatives_1: 232.2963 - false_positives_1: 279.7037 - loss: 0.3476 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8857 - false_negatives_1: 204.5926 - false_positives_1: 226.1111 - loss: 0.3016
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8595 - false_negatives_1: 241.1071 - false_positives_1: 290.9286 - loss: 0.3481 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8855 - false_negatives_1: 212.0357 - false_positives_1: 233.9286 - loss: 0.3021
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8592 - false_negatives_1: 249.7931 - false_positives_1: 302.1379 - loss: 0.3485 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 219.2759 - false_positives_1: 241.6552 - loss: 0.3024
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8589 - false_negatives_1: 258.4000 - false_positives_1: 313.2000 - loss: 0.3489 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 226.4667 - false_positives_1: 249.3000 - loss: 0.3027
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8586 - false_negatives_1: 267.0645 - false_positives_1: 324.3548 - loss: 0.3493 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 233.4839 - false_positives_1: 257.1290 - loss: 0.3030
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8584 - false_negatives_1: 276.0312 - false_positives_1: 335.1875 - loss: 0.3497 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8851 - false_negatives_1: 240.8438 - false_positives_1: 264.8125 - loss: 0.3033
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8582 - false_negatives_1: 284.6364 - false_positives_1: 346.0909 - loss: 0.3500 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8850 - false_negatives_1: 247.9091 - false_positives_1: 272.6667 - loss: 0.3035
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8580 - false_negatives_1: 293.0588 - false_positives_1: 356.9118 - loss: 0.3503 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8849 - false_negatives_1: 254.8824 - false_positives_1: 280.2941 - loss: 0.3037
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8579 - false_negatives_1: 301.4000 - false_positives_1: 367.6000 - loss: 0.3505 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8849 - false_negatives_1: 261.6286 - false_positives_1: 288.1429 - loss: 0.3038
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8577 - false_negatives_1: 309.7500 - false_positives_1: 378.1667 - loss: 0.3507 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8848 - false_negatives_1: 268.8055 - false_positives_1: 295.8055 - loss: 0.3039
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8576 - false_negatives_1: 317.8378 - false_positives_1: 389.0270 - loss: 0.3508 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8847 - false_negatives_1: 275.7297 - false_positives_1: 303.8919 - loss: 0.3041
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8575 - false_negatives_1: 326.3947 - false_positives_1: 399.4737 - loss: 0.3510 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8846 - false_negatives_1: 283.2368 - false_positives_1: 311.7368 - loss: 0.3043
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8574 - false_negatives_1: 334.5641 - false_positives_1: 410.2564 - loss: 0.3512 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8845 - false_negatives_1: 290.5128 - false_positives_1: 319.7180 - loss: 0.3046
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8573 - false_negatives_1: 342.9750 - false_positives_1: 420.6000 - loss: 0.3513 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8844 - false_negatives_1: 297.8500 - false_positives_1: 327.6750 - loss: 0.3048
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8572 - false_negatives_1: 351.2439 - false_positives_1: 431.0244 - loss: 0.3515 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8843 - false_negatives_1: 304.9512 - false_positives_1: 335.9268 - loss: 0.3050
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8572 - false_negatives_1: 359.4762 - false_positives_1: 441.3095 - loss: 0.3516 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8842 - false_negatives_1: 312.4048 - false_positives_1: 343.9762 - loss: 0.3052
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 367.7907 - false_positives_1: 451.6279 - loss: 0.3517 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 319.6977 - false_positives_1: 352.1395 - loss: 0.3054
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 376.1364 - false_positives_1: 461.7727 - loss: 0.3518 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8840 - false_negatives_1: 326.9773 - false_positives_1: 360.1818 - loss: 0.3055
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 384.3556 - false_positives_1: 471.8667 - loss: 0.3518 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8839 - false_negatives_1: 334.3333 - false_positives_1: 368.1555 - loss: 0.3057
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 392.4131 - false_positives_1: 481.8478 - loss: 0.3518 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8839 - false_negatives_1: 341.4565 - false_positives_1: 376.1956 - loss: 0.3058
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 400.3192 - false_positives_1: 491.8511 - loss: 0.3518 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8838 - false_negatives_1: 348.4043 - false_positives_1: 384.0851 - loss: 0.3058
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 408.1042 - false_positives_1: 501.8750 - loss: 0.3518 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8838 - false_negatives_1: 355.3333 - false_positives_1: 392.0417 - loss: 0.3059
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 415.7959 - false_positives_1: 511.8776 - loss: 0.3517 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8838 - false_negatives_1: 362.4898 - false_positives_1: 399.9184 - loss: 0.3060
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 423.9000 - false_positives_1: 521.6800 - loss: 0.3517 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8837 - false_negatives_1: 369.5000 - false_positives_1: 408.0600 - loss: 0.3060
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8571 - false_negatives_1: 431.6863 - false_positives_1: 531.9804 - loss: 0.3517 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8837 - false_negatives_1: 376.5882 - false_positives_1: 416.0588 - loss: 0.3061
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 440.3654 - false_positives_1: 541.9808 - loss: 0.3518 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 383.5385 - false_positives_1: 424.0577 - loss: 0.3061
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8570 - false_negatives_1: 448.8679 - false_positives_1: 552.4340 - loss: 0.3519 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 390.6038 - false_positives_1: 431.9622 - loss: 0.3061
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8569 - false_negatives_1: 457.7222 - false_positives_1: 562.8704 - loss: 0.3520 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 397.4815 - false_positives_1: 440.2963 - loss: 0.3062
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8568 - false_negatives_1: 466.4546 - false_positives_1: 573.3818 - loss: 0.3522 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8835 - false_negatives_1: 404.8000 - false_positives_1: 448.3818 - loss: 0.3063
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8567 - false_negatives_1: 474.9643 - false_positives_1: 583.8750 - loss: 0.3523 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8834 - false_negatives_1: 411.9286 - false_positives_1: 456.7143 - loss: 0.3064
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8567 - false_negatives_1: 483.5263 - false_positives_1: 594.2982 - loss: 0.3525 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8834 - false_negatives_1: 419.0175 - false_positives_1: 464.9298 - loss: 0.3064
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8566 - false_negatives_1: 492.1207 - false_positives_1: 604.7069 - loss: 0.3526 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8834 - false_negatives_1: 426.0690 - false_positives_1: 473.1379 - loss: 0.3065
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8566 - false_negatives_1: 500.5593 - false_positives_1: 614.9153 - loss: 0.3527 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8833 - false_negatives_1: 433.0678 - false_positives_1: 481.1864 - loss: 0.3065
``` -Epoch 9: val_loss improved from 0.37307 to 0.36301, saving model to AL_Model.keras +Epoch 12: val_loss did not improve from 0.37074  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8565 - false_negatives_1: 508.7167 - false_positives_1: 624.7833 - loss: 0.3528 - val_binary_accuracy: 0.8416 - val_false_negatives_1: 344.0000 - val_false_positives_1: 448.0000 - val_loss: 0.3630 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8833 - false_negatives_1: 439.8333 - false_positives_1: 488.9667 - loss: 0.3066 - val_binary_accuracy: 0.8236 - val_false_negatives_1: 208.0000 - val_false_positives_1: 674.0000 - val_loss: 0.4046
``` -Epoch 10/20 +Epoch 13/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 88ms/step - binary_accuracy: 0.9062 - false_negatives_1: 12.0000 - false_positives_1: 12.0000 - loss: 0.2607 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8750 - false_negatives_1: 1.0000 - false_positives_1: 31.0000 - loss: 0.3301
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9023 - false_negatives_1: 18.0000 - false_positives_1: 20.0000 - loss: 0.2677 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8701 - false_negatives_1: 17.5000 - false_positives_1: 33.0000 - loss: 0.3315
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.8984 - false_negatives_1: 23.6667 - false_positives_1: 29.6667 - loss: 0.2827 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8687 - false_negatives_1: 25.3333 - false_positives_1: 42.6667 - loss: 0.3310
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8955 - false_negatives_1: 33.0000 - false_positives_1: 36.0000 - loss: 0.2898 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8703 - false_negatives_1: 33.7500 - false_positives_1: 49.2500 - loss: 0.3300
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8927 - false_negatives_1: 39.2000 - false_positives_1: 46.4000 - loss: 0.2938 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8726 - false_negatives_1: 39.6000 - false_positives_1: 57.0000 - loss: 0.3265
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8899 - false_negatives_1: 48.3333 - false_positives_1: 54.6667 - loss: 0.2972 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8755 - false_negatives_1: 44.6667 - false_positives_1: 64.0000 - loss: 0.3223
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8876 - false_negatives_1: 55.7143 - false_positives_1: 65.0000 - loss: 0.2998 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8775 - false_negatives_1: 50.1429 - false_positives_1: 71.2857 - loss: 0.3188
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8860 - false_negatives_1: 63.1250 - false_positives_1: 74.3750 - loss: 0.3014 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8795 - false_negatives_1: 55.5000 - false_positives_1: 78.1250 - loss: 0.3155
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8851 - false_negatives_1: 71.0000 - false_positives_1: 82.6667 - loss: 0.3025 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8812 - false_negatives_1: 60.7778 - false_positives_1: 84.8889 - loss: 0.3127
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8842 - false_negatives_1: 78.4000 - false_positives_1: 91.5000 - loss: 0.3033 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8826 - false_negatives_1: 66.7000 - false_positives_1: 91.1000 - loss: 0.3099
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8831 - false_negatives_1: 87.9091 - false_positives_1: 99.4545 - loss: 0.3048 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8841 - false_negatives_1: 71.9091 - false_positives_1: 97.4545 - loss: 0.3073
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8814 - false_negatives_1: 95.9167 - false_positives_1: 110.8333 - loss: 0.3070 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8854 - false_negatives_1: 77.5000 - false_positives_1: 103.5833 - loss: 0.3054
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8795 - false_negatives_1: 106.7692 - false_positives_1: 120.6923 - loss: 0.3096 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8862 - false_negatives_1: 82.6154 - false_positives_1: 111.1538 - loss: 0.3039
``` - + ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8781 - false_negatives_1: 116.5714 - false_positives_1: 130.5714 - loss: 0.3119 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8868 - false_negatives_1: 88.5714 - false_positives_1: 118.3571 - loss: 0.3026
``` - + ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8770 - false_negatives_1: 125.8667 - false_positives_1: 140.4000 - loss: 0.3137 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8872 - false_negatives_1: 94.1333 - false_positives_1: 126.3333 - loss: 0.3017
``` - + ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8760 - false_negatives_1: 134.5000 - false_positives_1: 150.4375 - loss: 0.3152 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 100.4375 - false_positives_1: 133.6250 - loss: 0.3011
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8751 - false_negatives_1: 143.1765 - false_positives_1: 160.6471 - loss: 0.3166 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 106.2353 - false_positives_1: 142.0588 - loss: 0.3007
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8743 - false_negatives_1: 151.9444 - false_positives_1: 170.6667 - loss: 0.3179 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8878 - false_negatives_1: 113.0000 - false_positives_1: 149.8889 - loss: 0.3005
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8737 - false_negatives_1: 160.2105 - false_positives_1: 180.5263 - loss: 0.3190 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 119.4737 - false_positives_1: 158.8421 - loss: 0.3008
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8732 - false_negatives_1: 168.6000 - false_positives_1: 190.1500 - loss: 0.3200 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 126.4500 - false_positives_1: 167.3000 - loss: 0.3010
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8727 - false_negatives_1: 176.8095 - false_positives_1: 200.0476 - loss: 0.3209 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 133.3333 - false_positives_1: 175.4762 - loss: 0.3011
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8723 - false_negatives_1: 185.0000 - false_positives_1: 209.3636 - loss: 0.3216 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 140.0000 - false_positives_1: 183.8182 - loss: 0.3011
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8721 - false_negatives_1: 192.9130 - false_positives_1: 218.5652 - loss: 0.3221 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 146.7826 - false_positives_1: 191.7391 - loss: 0.3009
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8718 - false_negatives_1: 200.6250 - false_positives_1: 227.7500 - loss: 0.3226 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 153.4167 - false_positives_1: 199.7083 - loss: 0.3008
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8717 - false_negatives_1: 208.6800 - false_positives_1: 236.4400 - loss: 0.3230 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 160.2400 - false_positives_1: 207.4800 - loss: 0.3007
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8715 - false_negatives_1: 216.3846 - false_positives_1: 245.8846 - loss: 0.3234 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 166.6923 - false_positives_1: 215.5000 - loss: 0.3005
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8712 - false_negatives_1: 225.5556 - false_positives_1: 254.6667 - loss: 0.3240 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 173.7037 - false_positives_1: 223.1852 - loss: 0.3004
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8708 - false_negatives_1: 234.1786 - false_positives_1: 264.5357 - loss: 0.3247 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 180.3929 - false_positives_1: 231.1786 - loss: 0.3003
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8704 - false_negatives_1: 243.2414 - false_positives_1: 274.3103 - loss: 0.3254 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8875 - false_negatives_1: 187.1724 - false_positives_1: 238.8965 - loss: 0.3003
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8700 - false_negatives_1: 252.1333 - false_positives_1: 284.1000 - loss: 0.3261 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 193.8333 - false_positives_1: 246.6333 - loss: 0.3002
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8697 - false_negatives_1: 260.9355 - false_positives_1: 293.7419 - loss: 0.3267 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 200.3226 - false_positives_1: 254.4194 - loss: 0.3000
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8694 - false_negatives_1: 269.6562 - false_positives_1: 303.2812 - loss: 0.3272 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 206.8750 - false_positives_1: 262.0312 - loss: 0.2998
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8692 - false_negatives_1: 278.2121 - false_positives_1: 312.8485 - loss: 0.3277 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 213.2121 - false_positives_1: 269.6667 - loss: 0.2996
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8690 - false_negatives_1: 286.5294 - false_positives_1: 322.5882 - loss: 0.3281 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8878 - false_negatives_1: 219.6176 - false_positives_1: 277.0588 - loss: 0.2994
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8688 - false_negatives_1: 295.0286 - false_positives_1: 332.1714 - loss: 0.3285 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 225.8857 - false_positives_1: 284.7143 - loss: 0.2992
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8686 - false_negatives_1: 303.1667 - false_positives_1: 342.0555 - loss: 0.3288 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 232.5000 - false_positives_1: 292.0555 - loss: 0.2990
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8684 - false_negatives_1: 311.7027 - false_positives_1: 351.5676 - loss: 0.3292 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 238.8649 - false_positives_1: 300.0000 - loss: 0.2989
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8682 - false_negatives_1: 320.0000 - false_positives_1: 361.4474 - loss: 0.3296 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 245.4737 - false_positives_1: 307.7632 - loss: 0.2988
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8680 - false_negatives_1: 328.4872 - false_positives_1: 371.1282 - loss: 0.3299 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 251.8718 - false_positives_1: 315.6923 - loss: 0.2987
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8678 - false_negatives_1: 337.0250 - false_positives_1: 380.9250 - loss: 0.3303 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 258.3750 - false_positives_1: 323.5750 - loss: 0.2986
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8676 - false_negatives_1: 345.2683 - false_positives_1: 390.7561 - loss: 0.3306 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 264.7317 - false_positives_1: 331.7805 - loss: 0.2985
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8675 - false_negatives_1: 353.4524 - false_positives_1: 400.4048 - loss: 0.3308 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 271.3810 - false_positives_1: 339.6905 - loss: 0.2984
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8674 - false_negatives_1: 361.6977 - false_positives_1: 409.9070 - loss: 0.3311 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 277.9535 - false_positives_1: 347.8372 - loss: 0.2984
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8672 - false_negatives_1: 369.7046 - false_positives_1: 419.6364 - loss: 0.3313 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 284.5682 - false_positives_1: 355.8636 - loss: 0.2983
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8671 - false_negatives_1: 377.9778 - false_positives_1: 429.0222 - loss: 0.3315 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 291.0222 - false_positives_1: 363.9111 - loss: 0.2982
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8670 - false_negatives_1: 385.9565 - false_positives_1: 438.9348 - loss: 0.3317 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 297.4783 - false_positives_1: 371.8478 - loss: 0.2982
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8669 - false_negatives_1: 394.1277 - false_positives_1: 448.6596 - loss: 0.3319 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 303.9575 - false_positives_1: 379.7872 - loss: 0.2981
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8668 - false_negatives_1: 402.1250 - false_positives_1: 458.4583 - loss: 0.3321 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 310.2500 - false_positives_1: 387.7083 - loss: 0.2980
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8667 - false_negatives_1: 410.2653 - false_positives_1: 468.2245 - loss: 0.3323 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 316.8163 - false_positives_1: 395.4490 - loss: 0.2978
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8666 - false_negatives_1: 418.2400 - false_positives_1: 478.1800 - loss: 0.3325 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8880 - false_negatives_1: 323.2400 - false_positives_1: 403.5000 - loss: 0.2977
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8665 - false_negatives_1: 426.3726 - false_positives_1: 487.8431 - loss: 0.3327 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 330.2353 - false_positives_1: 411.3333 - loss: 0.2977
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8664 - false_negatives_1: 434.3654 - false_positives_1: 497.5962 - loss: 0.3329 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8879 - false_negatives_1: 337.0000 - false_positives_1: 419.7115 - loss: 0.2977
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8663 - false_negatives_1: 442.4717 - false_positives_1: 507.1698 - loss: 0.3331 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8878 - false_negatives_1: 344.0189 - false_positives_1: 427.8679 - loss: 0.2977
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8662 - false_negatives_1: 450.3704 - false_positives_1: 516.8519 - loss: 0.3332 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8878 - false_negatives_1: 350.9445 - false_positives_1: 436.0185 - loss: 0.2977
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8662 - false_negatives_1: 458.2909 - false_positives_1: 526.3273 - loss: 0.3333 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 357.8000 - false_positives_1: 444.1636 - loss: 0.2977
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8661 - false_negatives_1: 466.1786 - false_positives_1: 535.7500 - loss: 0.3334 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 364.6071 - false_positives_1: 452.2857 - loss: 0.2978
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8661 - false_negatives_1: 474.0702 - false_positives_1: 545.3509 - loss: 0.3335 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8877 - false_negatives_1: 371.3860 - false_positives_1: 460.4386 - loss: 0.2978
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8660 - false_negatives_1: 482.1552 - false_positives_1: 554.7759 - loss: 0.3336 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 378.1724 - false_positives_1: 468.5345 - loss: 0.2978
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8660 - false_negatives_1: 490.0000 - false_positives_1: 564.1525 - loss: 0.3337 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8876 - false_negatives_1: 384.8305 - false_positives_1: 476.5254 - loss: 0.2978
``` -Epoch 10: val_loss did not improve from 0.36301 +Epoch 13: val_loss did not improve from 0.37074  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8659 - false_negatives_1: 497.5833 - false_positives_1: 573.2167 - loss: 0.3338 - val_binary_accuracy: 0.8248 - val_false_negatives_1: 632.0000 - val_false_positives_1: 244.0000 - val_loss: 0.3918 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 82ms/step - binary_accuracy: 0.8876 - false_negatives_1: 391.2667 - false_positives_1: 484.2500 - loss: 0.2978 - val_binary_accuracy: 0.8380 - val_false_negatives_1: 364.0000 - val_false_positives_1: 446.0000 - val_loss: 0.3783
``` -Epoch 11/20 +Epoch 14/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 84ms/step - binary_accuracy: 0.8477 - false_negatives_1: 23.0000 - false_positives_1: 16.0000 - loss: 0.3141 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 85ms/step - binary_accuracy: 0.9219 - false_negatives_1: 12.0000 - false_positives_1: 8.0000 - loss: 0.2254
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8574 - false_negatives_1: 29.0000 - false_positives_1: 24.5000 - loss: 0.3045 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 71ms/step - binary_accuracy: 0.9199 - false_negatives_1: 15.5000 - false_positives_1: 15.5000 - loss: 0.2255
```  ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8637 - false_negatives_1: 35.0000 - false_positives_1: 32.3333 - loss: 0.3013 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9197 - false_negatives_1: 19.3333 - false_positives_1: 22.0000 - loss: 0.2239
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8680 - false_negatives_1: 40.5000 - false_positives_1: 40.5000 - loss: 0.3019 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9200 - false_negatives_1: 25.0000 - false_positives_1: 26.2500 - loss: 0.2228
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8705 - false_negatives_1: 47.8000 - false_positives_1: 47.6000 - loss: 0.3025 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9177 - false_negatives_1: 29.0000 - false_positives_1: 35.4000 - loss: 0.2267
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8718 - false_negatives_1: 54.5000 - false_positives_1: 56.1667 - loss: 0.3036 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9153 - false_negatives_1: 36.5000 - false_positives_1: 42.0000 - loss: 0.2321
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8729 - false_negatives_1: 62.0000 - false_positives_1: 63.7143 - loss: 0.3041 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9129 - false_negatives_1: 43.2857 - false_positives_1: 50.0000 - loss: 0.2365
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8735 - false_negatives_1: 68.3750 - false_positives_1: 72.8750 - loss: 0.3050 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9112 - false_negatives_1: 50.2500 - false_positives_1: 57.0000 - loss: 0.2399
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8731 - false_negatives_1: 77.5556 - false_positives_1: 81.3333 - loss: 0.3075 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9101 - false_negatives_1: 56.4444 - false_positives_1: 64.2222 - loss: 0.2421
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8724 - false_negatives_1: 85.4000 - false_positives_1: 92.0000 - loss: 0.3098 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9091 - false_negatives_1: 63.2000 - false_positives_1: 70.9000 - loss: 0.2443
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8718 - false_negatives_1: 93.9091 - false_positives_1: 101.6364 - loss: 0.3118 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9084 - false_negatives_1: 69.3636 - false_positives_1: 78.0000 - loss: 0.2460
``` - + ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8713 - false_negatives_1: 101.3333 - false_positives_1: 112.1667 - loss: 0.3134 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9077 - false_negatives_1: 75.5833 - false_positives_1: 85.0833 - loss: 0.2475
``` - + ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8709 - false_negatives_1: 109.6154 - false_positives_1: 121.7692 - loss: 0.3147 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9072 - false_negatives_1: 82.0000 - false_positives_1: 91.6154 - loss: 0.2488
``` - + ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8706 - false_negatives_1: 117.2143 - false_positives_1: 131.7143 - loss: 0.3157 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9068 - false_negatives_1: 87.6429 - false_positives_1: 98.7143 - loss: 0.2501
``` - + ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8705 - false_negatives_1: 125.0000 - false_positives_1: 140.8667 - loss: 0.3163 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9063 - false_negatives_1: 94.7333 - false_positives_1: 104.9333 - loss: 0.2515
``` - + ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8704 - false_negatives_1: 132.0625 - false_positives_1: 150.6250 - loss: 0.3169 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9059 - false_negatives_1: 101.3125 - false_positives_1: 111.3750 - loss: 0.2526
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8702 - false_negatives_1: 140.4118 - false_positives_1: 159.7647 - loss: 0.3174 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9056 - false_negatives_1: 107.5882 - false_positives_1: 118.0588 - loss: 0.2537
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8699 - false_negatives_1: 148.0556 - false_positives_1: 170.2222 - loss: 0.3182 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9054 - false_negatives_1: 113.7222 - false_positives_1: 124.3333 - loss: 0.2544
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8695 - false_negatives_1: 156.4211 - false_positives_1: 180.1053 - loss: 0.3191 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9054 - false_negatives_1: 119.5263 - false_positives_1: 130.6316 - loss: 0.2549
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8693 - false_negatives_1: 164.2500 - false_positives_1: 189.8500 - loss: 0.3197 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9053 - false_negatives_1: 125.5500 - false_positives_1: 136.7000 - loss: 0.2553
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8692 - false_negatives_1: 171.7143 - false_positives_1: 199.8095 - loss: 0.3203 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9051 - false_negatives_1: 131.1429 - false_positives_1: 143.5714 - loss: 0.2559
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 179.2273 - false_positives_1: 209.4545 - loss: 0.3208 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9048 - false_negatives_1: 138.3182 - false_positives_1: 149.9091 - loss: 0.2569
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 186.6956 - false_positives_1: 218.7391 - loss: 0.3211 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9044 - false_negatives_1: 145.0000 - false_positives_1: 157.8696 - loss: 0.2582
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 193.8333 - false_positives_1: 228.2917 - loss: 0.3214 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9040 - false_negatives_1: 151.7500 - false_positives_1: 165.5000 - loss: 0.2593
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 201.2000 - false_positives_1: 237.5200 - loss: 0.3215 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9036 - false_negatives_1: 158.2000 - false_positives_1: 173.2400 - loss: 0.2603
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8690 - false_negatives_1: 208.1923 - false_positives_1: 247.2692 - loss: 0.3217 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9033 - false_negatives_1: 164.6154 - false_positives_1: 180.8462 - loss: 0.2611
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8689 - false_negatives_1: 216.6296 - false_positives_1: 256.4074 - loss: 0.3222 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9030 - false_negatives_1: 171.1481 - false_positives_1: 188.4444 - loss: 0.2619
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8688 - false_negatives_1: 224.5714 - false_positives_1: 266.1071 - loss: 0.3226 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9027 - false_negatives_1: 177.5714 - false_positives_1: 196.0714 - loss: 0.2625
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 232.3103 - false_positives_1: 275.7242 - loss: 0.3230 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9024 - false_negatives_1: 183.8276 - false_positives_1: 203.6207 - loss: 0.2632
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 239.9000 - false_positives_1: 285.0667 - loss: 0.3234 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9022 - false_negatives_1: 190.0000 - false_positives_1: 211.0333 - loss: 0.2638
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 247.5484 - false_positives_1: 294.1290 - loss: 0.3237 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9021 - false_negatives_1: 196.1613 - false_positives_1: 218.3871 - loss: 0.2643
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 255.0625 - false_positives_1: 303.2188 - loss: 0.3240 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9019 - false_negatives_1: 202.2188 - false_positives_1: 225.7812 - loss: 0.2648
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 262.7879 - false_positives_1: 311.9697 - loss: 0.3242 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9017 - false_negatives_1: 208.2424 - false_positives_1: 233.2121 - loss: 0.2652
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8687 - false_negatives_1: 270.2647 - false_positives_1: 320.7353 - loss: 0.3244 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9016 - false_negatives_1: 214.2941 - false_positives_1: 240.3235 - loss: 0.2656
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8688 - false_negatives_1: 277.6857 - false_positives_1: 329.5428 - loss: 0.3245 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 220.0571 - false_positives_1: 248.1429 - loss: 0.2661
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8689 - false_negatives_1: 285.2500 - false_positives_1: 338.1389 - loss: 0.3246 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9013 - false_negatives_1: 226.8333 - false_positives_1: 255.6111 - loss: 0.2667
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8689 - false_negatives_1: 292.5946 - false_positives_1: 346.8919 - loss: 0.3247 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9010 - false_negatives_1: 233.4324 - false_positives_1: 263.5946 - loss: 0.2672
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8690 - false_negatives_1: 300.0789 - false_positives_1: 355.3684 - loss: 0.3247 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9008 - false_negatives_1: 240.1842 - false_positives_1: 271.4474 - loss: 0.2678
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 307.3846 - false_positives_1: 364.0769 - loss: 0.3248 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9006 - false_negatives_1: 246.7436 - false_positives_1: 279.2820 - loss: 0.2683
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8691 - false_negatives_1: 314.9750 - false_positives_1: 372.5000 - loss: 0.3248 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9004 - false_negatives_1: 253.2000 - false_positives_1: 287.0000 - loss: 0.2687
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8692 - false_negatives_1: 322.2927 - false_positives_1: 381.1707 - loss: 0.3249 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9002 - false_negatives_1: 259.7561 - false_positives_1: 294.5610 - loss: 0.2692
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8693 - false_negatives_1: 329.7381 - false_positives_1: 389.6905 - loss: 0.3249 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9000 - false_negatives_1: 266.1905 - false_positives_1: 302.1667 - loss: 0.2696
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8694 - false_negatives_1: 337.0930 - false_positives_1: 398.2325 - loss: 0.3249 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8999 - false_negatives_1: 272.8372 - false_positives_1: 309.6977 - loss: 0.2700
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8695 - false_negatives_1: 344.5682 - false_positives_1: 406.5000 - loss: 0.3249 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8997 - false_negatives_1: 279.3182 - false_positives_1: 317.5682 - loss: 0.2704
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8695 - false_negatives_1: 351.8000 - false_positives_1: 414.9111 - loss: 0.3249 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8995 - false_negatives_1: 285.9778 - false_positives_1: 325.2000 - loss: 0.2708
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8696 - false_negatives_1: 359.2174 - false_positives_1: 423.2826 - loss: 0.3249 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8994 - false_negatives_1: 292.5869 - false_positives_1: 332.9783 - loss: 0.2712
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8697 - false_negatives_1: 366.4043 - false_positives_1: 431.8936 - loss: 0.3248 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8992 - false_negatives_1: 299.3617 - false_positives_1: 340.6170 - loss: 0.2716
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8698 - false_negatives_1: 374.1042 - false_positives_1: 440.2917 - loss: 0.3248 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8991 - false_negatives_1: 305.9792 - false_positives_1: 348.4583 - loss: 0.2720
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8698 - false_negatives_1: 381.5510 - false_positives_1: 448.9592 - loss: 0.3248 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8989 - false_negatives_1: 312.6939 - false_positives_1: 356.2449 - loss: 0.2724
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8699 - false_negatives_1: 389.0000 - false_positives_1: 457.5800 - loss: 0.3248 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8987 - false_negatives_1: 319.3600 - false_positives_1: 364.0800 - loss: 0.2728
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8699 - false_negatives_1: 396.4706 - false_positives_1: 466.2157 - loss: 0.3248 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8986 - false_negatives_1: 325.9216 - false_positives_1: 371.9608 - loss: 0.2732
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8699 - false_negatives_1: 403.9615 - false_positives_1: 474.7885 - loss: 0.3248 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8985 - false_negatives_1: 332.5192 - false_positives_1: 379.6731 - loss: 0.2735
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8700 - false_negatives_1: 411.3773 - false_positives_1: 483.2642 - loss: 0.3247 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8983 - false_negatives_1: 338.9622 - false_positives_1: 387.5849 - loss: 0.2738
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8701 - false_negatives_1: 418.6482 - false_positives_1: 491.8704 - loss: 0.3247 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8982 - false_negatives_1: 345.5000 - false_positives_1: 395.2778 - loss: 0.2741
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8701 - false_negatives_1: 426.0364 - false_positives_1: 500.4182 - loss: 0.3247 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8981 - false_negatives_1: 351.8909 - false_positives_1: 403.0545 - loss: 0.2744
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8702 - false_negatives_1: 433.3036 - false_positives_1: 509.2143 - loss: 0.3247 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8980 - false_negatives_1: 358.5179 - false_positives_1: 410.6964 - loss: 0.2747
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8702 - false_negatives_1: 441.0702 - false_positives_1: 517.7719 - loss: 0.3247 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8979 - false_negatives_1: 365.0175 - false_positives_1: 418.5614 - loss: 0.2749
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8702 - false_negatives_1: 448.6379 - false_positives_1: 526.6207 - loss: 0.3247 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8977 - false_negatives_1: 371.5862 - false_positives_1: 426.3276 - loss: 0.2752
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8702 - false_negatives_1: 456.2203 - false_positives_1: 535.2881 - loss: 0.3248 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8976 - false_negatives_1: 378.0169 - false_positives_1: 433.9831 - loss: 0.2754
``` -Epoch 11: val_loss did not improve from 0.36301 +Epoch 14: val_loss did not improve from 0.37074  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 84ms/step - binary_accuracy: 0.8702 - false_negatives_1: 463.5500 - false_positives_1: 543.6667 - loss: 0.3248 - val_binary_accuracy: 0.8370 - val_false_negatives_1: 219.0000 - val_false_positives_1: 596.0000 - val_loss: 0.3757 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8975 - false_negatives_1: 384.2333 - false_positives_1: 441.3833 - loss: 0.2757 - val_binary_accuracy: 0.8310 - val_false_negatives_1: 525.0000 - val_false_positives_1: 320.0000 - val_loss: 0.3957
``` -Epoch 12/20 +Epoch 15/20 ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 5s 88ms/step - binary_accuracy: 0.8984 - false_negatives_1: 1.0000 - false_positives_1: 25.0000 - loss: 0.2930 + 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 86ms/step - binary_accuracy: 0.8906 - false_negatives_1: 19.0000 - false_positives_1: 9.0000 - loss: 0.2945
```  ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 8.0000 - false_positives_1: 29.5000 - loss: 0.2879 + 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8887 - false_negatives_1: 21.5000 - false_positives_1: 21.5000 - loss: 0.2950
``` - + ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9004 - false_negatives_1: 13.0000 - false_positives_1: 38.0000 - loss: 0.2882 + 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8880 - false_negatives_1: 30.0000 - false_positives_1: 27.6667 - loss: 0.2954
```  ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9001 - false_negatives_1: 20.0000 - false_positives_1: 44.0000 - loss: 0.2885 + 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8911 - false_negatives_1: 35.5000 - false_positives_1: 33.2500 - loss: 0.2904
```  ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9003 - false_negatives_1: 25.2000 - false_positives_1: 51.4000 - loss: 0.2877 + 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8943 - false_negatives_1: 40.8000 - false_positives_1: 38.0000 - loss: 0.2845
```  ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8993 - false_negatives_1: 32.3333 - false_positives_1: 58.5000 - loss: 0.2896 + 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8967 - false_negatives_1: 45.5000 - false_positives_1: 43.5000 - loss: 0.2799
```  ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8969 - false_negatives_1: 38.7143 - false_positives_1: 69.2857 - loss: 0.2931 + 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8986 - false_negatives_1: 50.5714 - false_positives_1: 48.7143 - loss: 0.2755
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8949 - false_negatives_1: 47.0000 - false_positives_1: 77.8750 - loss: 0.2958 + 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9002 - false_negatives_1: 55.6250 - false_positives_1: 54.0000 - loss: 0.2718
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8933 - false_negatives_1: 54.0000 - false_positives_1: 87.7778 - loss: 0.2980 + 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 60.2222 - false_positives_1: 59.8889 - loss: 0.2695
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8918 - false_negatives_1: 62.1000 - false_positives_1: 96.5000 - loss: 0.3000 + 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9024 - false_negatives_1: 65.6000 - false_positives_1: 65.2000 - loss: 0.2678
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8906 - false_negatives_1: 69.3636 - false_positives_1: 105.9091 - loss: 0.3015 + 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9029 - false_negatives_1: 70.2727 - false_positives_1: 72.4545 - loss: 0.2671
``` - + ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8896 - false_negatives_1: 77.0000 - false_positives_1: 114.8333 - loss: 0.3027 + 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9025 - false_negatives_1: 78.1667 - false_positives_1: 78.5833 - loss: 0.2673
``` - + ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8888 - false_negatives_1: 84.0000 - false_positives_1: 124.0000 - loss: 0.3039 + 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9019 - false_negatives_1: 84.9231 - false_positives_1: 86.6154 - loss: 0.2681
``` - + ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8881 - false_negatives_1: 91.7143 - false_positives_1: 132.5000 - loss: 0.3050 + 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 91.7857 - false_positives_1: 94.0714 - loss: 0.2688
``` - + ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8875 - false_negatives_1: 98.5333 - false_positives_1: 141.5333 - loss: 0.3059 + 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9013 - false_negatives_1: 98.2000 - false_positives_1: 101.2667 - loss: 0.2692
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8871 - false_negatives_1: 105.5625 - false_positives_1: 150.0625 - loss: 0.3066 + 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9011 - false_negatives_1: 104.4375 - false_positives_1: 108.6250 - loss: 0.2697
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8868 - false_negatives_1: 112.5882 - false_positives_1: 158.2353 - loss: 0.3072 + 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9011 - false_negatives_1: 110.4706 - false_positives_1: 115.4706 - loss: 0.2698
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8866 - false_negatives_1: 119.1667 - false_positives_1: 166.2778 - loss: 0.3074 + 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9010 - false_negatives_1: 116.3889 - false_positives_1: 122.6667 - loss: 0.2701
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8865 - false_negatives_1: 126.0000 - false_positives_1: 173.8947 - loss: 0.3076 + 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9010 - false_negatives_1: 122.3684 - false_positives_1: 129.4737 - loss: 0.2703
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8864 - false_negatives_1: 132.4500 - false_positives_1: 181.9500 - loss: 0.3077 + 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9010 - false_negatives_1: 128.1500 - false_positives_1: 136.3500 - loss: 0.2704
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8863 - false_negatives_1: 139.4762 - false_positives_1: 189.5238 - loss: 0.3077 + 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9011 - false_negatives_1: 133.7143 - false_positives_1: 143.0952 - loss: 0.2704
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8862 - false_negatives_1: 145.9545 - false_positives_1: 197.7727 - loss: 0.3076 + 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9012 - false_negatives_1: 139.4091 - false_positives_1: 149.5909 - loss: 0.2703
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8862 - false_negatives_1: 152.7391 - false_positives_1: 205.6087 - loss: 0.3075 + 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9013 - false_negatives_1: 144.9130 - false_positives_1: 156.5652 - loss: 0.2703
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8861 - false_negatives_1: 159.2917 - false_positives_1: 213.4583 - loss: 0.3075 + 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9013 - false_negatives_1: 150.5417 - false_positives_1: 163.3333 - loss: 0.2704
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8861 - false_negatives_1: 166.0800 - false_positives_1: 221.4000 - loss: 0.3074 + 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 155.9200 - false_positives_1: 170.2800 - loss: 0.2704
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 172.7308 - false_positives_1: 229.2692 - loss: 0.3073 + 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 161.4615 - false_positives_1: 177.0385 - loss: 0.2703
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 179.3704 - false_positives_1: 237.0370 - loss: 0.3072 + 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9015 - false_negatives_1: 166.8148 - false_positives_1: 184.0000 - loss: 0.2703
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 186.0000 - false_positives_1: 244.4286 - loss: 0.3071 + 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9016 - false_negatives_1: 172.5000 - false_positives_1: 190.5357 - loss: 0.2702
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 192.6207 - false_positives_1: 252.1724 - loss: 0.3069 + 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9016 - false_negatives_1: 177.8621 - false_positives_1: 197.5862 - loss: 0.2702
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 199.5667 - false_positives_1: 259.6667 - loss: 0.3068 + 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9016 - false_negatives_1: 184.0000 - false_positives_1: 204.2333 - loss: 0.2702
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8860 - false_negatives_1: 206.1935 - false_positives_1: 267.5484 - loss: 0.3067 + 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9016 - false_negatives_1: 189.8710 - false_positives_1: 211.1290 - loss: 0.2702
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8859 - false_negatives_1: 213.5625 - false_positives_1: 275.0625 - loss: 0.3068 + 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 195.9375 - false_positives_1: 218.0000 - loss: 0.2703
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8858 - false_negatives_1: 220.6061 - false_positives_1: 283.4849 - loss: 0.3069 + 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 202.0000 - false_positives_1: 224.8485 - loss: 0.2704
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8857 - false_negatives_1: 228.0882 - false_positives_1: 291.6471 - loss: 0.3072 + 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9015 - false_negatives_1: 208.2059 - false_positives_1: 231.6471 - loss: 0.2705
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8856 - false_negatives_1: 235.4000 - false_positives_1: 299.7429 - loss: 0.3073 + 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 214.3714 - false_positives_1: 238.5714 - loss: 0.2707
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8855 - false_negatives_1: 242.6389 - false_positives_1: 307.7500 - loss: 0.3075 + 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 220.3333 - false_positives_1: 245.4444 - loss: 0.2708
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 249.7568 - false_positives_1: 315.7027 - loss: 0.3076 + 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 226.2432 - false_positives_1: 252.2973 - loss: 0.2708
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 256.7895 - false_positives_1: 323.5526 - loss: 0.3077 + 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 232.0789 - false_positives_1: 259.1316 - loss: 0.2708
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 263.6667 - false_positives_1: 331.2564 - loss: 0.3077 + 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 237.8205 - false_positives_1: 266.0000 - loss: 0.2708
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 270.3500 - false_positives_1: 339.0000 - loss: 0.3077 + 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9014 - false_negatives_1: 243.7000 - false_positives_1: 272.7000 - loss: 0.2708
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 277.2439 - false_positives_1: 346.5854 - loss: 0.3077 + 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 249.4634 - false_positives_1: 279.4146 - loss: 0.2708
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 283.9762 - false_positives_1: 354.2381 - loss: 0.3077 + 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 255.3095 - false_positives_1: 286.0476 - loss: 0.2708
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 290.6744 - false_positives_1: 361.9767 - loss: 0.3077 + 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 261.0930 - false_positives_1: 292.8140 - loss: 0.2708
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 297.2727 - false_positives_1: 369.8182 - loss: 0.3077 + 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9015 - false_negatives_1: 266.8864 - false_positives_1: 299.3864 - loss: 0.2708
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8854 - false_negatives_1: 304.1778 - false_positives_1: 377.5555 - loss: 0.3077 + 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9015 - false_negatives_1: 272.5111 - false_positives_1: 306.2222 - loss: 0.2707
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 310.9131 - false_positives_1: 385.6304 - loss: 0.3078 + 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9015 - false_negatives_1: 278.5869 - false_positives_1: 312.8913 - loss: 0.2708
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 317.8723 - false_positives_1: 393.5745 - loss: 0.3078 + 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 284.4468 - false_positives_1: 319.9787 - loss: 0.2708
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 324.7292 - false_positives_1: 401.6458 - loss: 0.3079 + 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 290.5833 - false_positives_1: 326.9792 - loss: 0.2709
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 331.5714 - false_positives_1: 409.6327 - loss: 0.3079 + 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9014 - false_negatives_1: 296.5714 - false_positives_1: 334.1429 - loss: 0.2709
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8853 - false_negatives_1: 338.4400 - false_positives_1: 417.4400 - loss: 0.3079 + 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 302.5800 - false_positives_1: 341.1200 - loss: 0.2710
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 345.0981 - false_positives_1: 425.4118 - loss: 0.3080 + 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 308.4706 - false_positives_1: 348.1961 - loss: 0.2710
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 352.1346 - false_positives_1: 433.1923 - loss: 0.3080 + 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 314.3654 - false_positives_1: 355.1731 - loss: 0.2710
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 359.0000 - false_positives_1: 441.3019 - loss: 0.3081 + 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 320.2453 - false_positives_1: 362.0755 - loss: 0.2710
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 366.0370 - false_positives_1: 449.1852 - loss: 0.3082 + 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 326.0370 - false_positives_1: 369.0555 - loss: 0.2710
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8852 - false_negatives_1: 373.0000 - false_positives_1: 457.0364 - loss: 0.3082 + 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 331.9455 - false_positives_1: 375.9818 - loss: 0.2710
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8851 - false_negatives_1: 380.1429 - false_positives_1: 464.8036 - loss: 0.3083 + 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9012 - false_negatives_1: 337.7500 - false_positives_1: 382.8929 - loss: 0.2710
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8851 - false_negatives_1: 387.1228 - false_positives_1: 472.7193 - loss: 0.3083 + 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9012 - false_negatives_1: 343.5789 - false_positives_1: 389.7018 - loss: 0.2710
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8851 - false_negatives_1: 394.3621 - false_positives_1: 480.4138 - loss: 0.3084 + 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9013 - false_negatives_1: 349.2758 - false_positives_1: 396.5345 - loss: 0.2710
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8850 - false_negatives_1: 401.4237 - false_positives_1: 488.3390 - loss: 0.3085 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9013 - false_negatives_1: 354.9322 - false_positives_1: 403.1695 - loss: 0.2709
``` -Epoch 12: val_loss did not improve from 0.36301 +Epoch 15: val_loss did not improve from 0.37074  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8850 - false_negatives_1: 408.2500 - false_positives_1: 496.0000 - loss: 0.3085 - val_binary_accuracy: 0.7840 - val_false_negatives_1: 941.0000 - val_false_positives_1: 139.0000 - val_loss: 0.4664 + 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.9013 - false_negatives_1: 360.4000 - false_positives_1: 409.5833 - loss: 0.2709 - val_binary_accuracy: 0.8298 - val_false_negatives_1: 302.0000 - val_false_positives_1: 549.0000 - val_loss: 0.4015
``` -Epoch 13/20 +Epoch 15: early stopping ```
- 1/59 ━━━━━━━━━━━━━━━━━━━━ 4s 85ms/step - binary_accuracy: 0.8242 - false_negatives_1: 39.0000 - false_positives_1: 6.0000 - loss: 0.3575 + 1/20 ━━━━━━━━━━━━━━━━━━━━ 4s 260ms/step
``` - + ```
- 2/59 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8379 - false_negatives_1: 41.5000 - false_positives_1: 19.0000 - loss: 0.3495 + 3/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
``` - + ```
- 3/59 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8442 - false_negatives_1: 48.3333 - false_positives_1: 28.6667 - loss: 0.3458 + 5/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 4/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8521 - false_negatives_1: 53.2500 - false_positives_1: 36.2500 - loss: 0.3383 + 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 5/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8584 - false_negatives_1: 58.2000 - false_positives_1: 43.2000 - loss: 0.3326 + 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 6/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8639 - false_negatives_1: 62.5000 - false_positives_1: 49.8333 - loss: 0.3265 + 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + +``` +
+ 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + +
+``` + +``` +
+ 15/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + +
+``` + +``` +
+ 17/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + +
+``` + +``` +
+ 19/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + +
+``` + +``` +
+ 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 39ms/step + +
+``` + +``` +
+ 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 39ms/step + + +
+``` +---------------------------------------------------------------------------------------------------- +Number of zeros incorrectly classified: 290.0, Number of ones incorrectly classified: 538.0 +Sample ratio for positives: 0.6497584541062802, Sample ratio for negatives:0.3502415458937198 +Starting training with 19999 samples +---------------------------------------------------------------------------------------------------- +Epoch 1/20 + +``` +
+ + 1/79 ━━━━━━━━━━━━━━━━━━━━ 3:32 3s/step - binary_accuracy: 0.9141 - false_negatives_2: 9.0000 - false_positives_2: 13.0000 - loss: 0.2378 + +
+``` + ```
- 7/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8682 - false_negatives_1: 67.7143 - false_positives_1: 55.7143 - loss: 0.3222 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8682 - false_negatives_2: 42.5000 - false_positives_2: 14.0000 - loss: 0.3333
```  ```
- 8/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8712 - false_negatives_1: 73.0000 - false_positives_1: 62.6250 - loss: 0.3195 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8322 - false_negatives_2: 53.6667 - false_positives_2: 45.3333 - loss: 0.4582
```  ```
- 9/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8735 - false_negatives_1: 78.7778 - false_positives_1: 69.4444 - loss: 0.3173 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8222 - false_negatives_2: 65.5000 - false_positives_2: 62.0000 - loss: 0.4954
```  ```
- 10/59 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8751 - false_negatives_1: 84.1000 - false_positives_1: 77.6000 - loss: 0.3159 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8209 - false_negatives_2: 75.4000 - false_positives_2: 73.8000 - loss: 0.5032
```  ```
- 11/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8765 - false_negatives_1: 89.7273 - false_positives_1: 85.2727 - loss: 0.3144 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8223 - false_negatives_2: 84.3333 - false_positives_2: 83.6667 - loss: 0.5009
```  ```
- 12/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8778 - false_negatives_1: 95.4167 - false_positives_1: 92.5000 - loss: 0.3128 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8242 - false_negatives_2: 92.2857 - false_positives_2: 93.7143 - loss: 0.4962
```  ```
- 13/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8791 - false_negatives_1: 101.0000 - false_positives_1: 99.6923 - loss: 0.3114 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8268 - false_negatives_2: 99.8750 - false_positives_2: 102.6250 - loss: 0.4899
```  ```
- 14/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8802 - false_negatives_1: 106.9286 - false_positives_1: 106.1429 - loss: 0.3099 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8293 - false_negatives_2: 107.8889 - false_positives_2: 110.6667 - loss: 0.4831
```  ```
- 15/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8811 - false_negatives_1: 112.3333 - false_positives_1: 113.7333 - loss: 0.3087 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8319 - false_negatives_2: 115.1000 - false_positives_2: 118.7000 - loss: 0.4760
```  ```
- 16/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8817 - false_negatives_1: 119.6250 - false_positives_1: 120.6250 - loss: 0.3081 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8343 - false_negatives_2: 122.3636 - false_positives_2: 126.5455 - loss: 0.4696
```  ```
- 17/59 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8819 - false_negatives_1: 126.5882 - false_positives_1: 128.6471 - loss: 0.3078 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8361 - false_negatives_2: 129.5833 - false_positives_2: 135.2500 - loss: 0.4643
```  ```
- 18/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8822 - false_negatives_1: 133.6667 - false_positives_1: 136.5000 - loss: 0.3075 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8380 - false_negatives_2: 136.6154 - false_positives_2: 143.6154 - loss: 0.4593
```  ```
- 19/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8824 - false_negatives_1: 140.4211 - false_positives_1: 144.4211 - loss: 0.3072 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8397 - false_negatives_2: 143.6429 - false_positives_2: 151.9286 - loss: 0.4545
```  ```
- 20/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8827 - false_negatives_1: 146.8500 - false_positives_1: 152.3000 - loss: 0.3069 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8414 - false_negatives_2: 150.0667 - false_positives_2: 160.4667 - loss: 0.4499
```  ```
- 21/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8830 - false_negatives_1: 153.4762 - false_positives_1: 159.8095 - loss: 0.3067 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8429 - false_negatives_2: 156.5000 - false_positives_2: 168.9375 - loss: 0.4454
```  ```
- 22/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8832 - false_negatives_1: 159.7273 - false_positives_1: 168.0909 - loss: 0.3067 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8444 - false_negatives_2: 162.7647 - false_positives_2: 177.4118 - loss: 0.4411
```  ```
- 23/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8834 - false_negatives_1: 166.3913 - false_positives_1: 176.0000 - loss: 0.3066 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8457 - false_negatives_2: 169.5000 - false_positives_2: 185.6111 - loss: 0.4372
```  ```
- 24/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8835 - false_negatives_1: 172.7500 - false_positives_1: 184.5833 - loss: 0.3065 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8469 - false_negatives_2: 176.0526 - false_positives_2: 193.8421 - loss: 0.4336
```  ```
- 25/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 179.6400 - false_positives_1: 192.8400 - loss: 0.3065 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8481 - false_negatives_2: 182.6000 - false_positives_2: 201.7000 - loss: 0.4300
```  ```
- 26/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 186.3462 - false_positives_1: 201.6923 - loss: 0.3065 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8492 - false_negatives_2: 189.0476 - false_positives_2: 210.1905 - loss: 0.4268
```  ```
- 27/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 193.1852 - false_positives_1: 210.1852 - loss: 0.3065 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8501 - false_negatives_2: 195.8182 - false_positives_2: 218.4091 - loss: 0.4237
```  ```
- 28/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 199.8571 - false_positives_1: 218.7143 - loss: 0.3066 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8511 - false_negatives_2: 202.3044 - false_positives_2: 226.6087 - loss: 0.4208
```  ```
- 29/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8836 - false_negatives_1: 206.6897 - false_positives_1: 227.0345 - loss: 0.3066 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8520 - false_negatives_2: 208.8750 - false_positives_2: 234.7083 - loss: 0.4180
```  ```
- 30/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8837 - false_negatives_1: 213.3000 - false_positives_1: 235.4333 - loss: 0.3066 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8529 - false_negatives_2: 215.3600 - false_positives_2: 242.8000 - loss: 0.4154
```  ```
- 31/59 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8837 - false_negatives_1: 219.9677 - false_positives_1: 243.6129 - loss: 0.3065 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8537 - false_negatives_2: 221.9615 - false_positives_2: 251.0000 - loss: 0.4130
```  ```
- 32/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8838 - false_negatives_1: 226.4062 - false_positives_1: 252.0312 - loss: 0.3063 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8544 - false_negatives_2: 228.4074 - false_positives_2: 259.1852 - loss: 0.4106
```  ```
- 33/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8838 - false_negatives_1: 233.1515 - false_positives_1: 260.1818 - loss: 0.3062 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8552 - false_negatives_2: 234.7143 - false_positives_2: 267.3214 - loss: 0.4083
```  ```
- 34/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8839 - false_negatives_1: 239.6471 - false_positives_1: 268.7353 - loss: 0.3061 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8560 - false_negatives_2: 241.0000 - false_positives_2: 275.1724 - loss: 0.4061
```  ```
- 35/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8839 - false_negatives_1: 246.3143 - false_positives_1: 276.9429 - loss: 0.3060 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8567 - false_negatives_2: 247.2667 - false_positives_2: 283.0000 - loss: 0.4039
```  ```
- 36/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8839 - false_negatives_1: 252.9444 - false_positives_1: 285.3055 - loss: 0.3059 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8574 - false_negatives_2: 253.5161 - false_positives_2: 290.7097 - loss: 0.4018
```  ```
- 37/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8840 - false_negatives_1: 259.5676 - false_positives_1: 293.4324 - loss: 0.3058 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8581 - false_negatives_2: 259.5938 - false_positives_2: 298.4375 - loss: 0.3997
```  ```
- 38/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8840 - false_negatives_1: 266.1053 - false_positives_1: 301.5263 - loss: 0.3056 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8588 - false_negatives_2: 265.7576 - false_positives_2: 305.8485 - loss: 0.3977
```  ```
- 39/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 272.8205 - false_positives_1: 309.5641 - loss: 0.3055 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8595 - false_negatives_2: 271.7647 - false_positives_2: 313.1765 - loss: 0.3957
```  ```
- 40/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 279.4000 - false_positives_1: 317.8250 - loss: 0.3054 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8601 - false_negatives_2: 277.7143 - false_positives_2: 320.4857 - loss: 0.3937
```  ```
- 41/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 286.3903 - false_positives_1: 325.8049 - loss: 0.3053 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8608 - false_negatives_2: 283.5833 - false_positives_2: 327.8333 - loss: 0.3919
```  ```
- 42/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 293.2381 - false_positives_1: 333.9286 - loss: 0.3053 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8614 - false_negatives_2: 289.6757 - false_positives_2: 335.0000 - loss: 0.3900
```  ```
- 43/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8841 - false_negatives_1: 300.0233 - false_positives_1: 341.9535 - loss: 0.3052 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8620 - false_negatives_2: 295.6053 - false_positives_2: 342.5526 - loss: 0.3883
```  ```
- 44/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8842 - false_negatives_1: 306.6136 - false_positives_1: 350.0000 - loss: 0.3051 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8625 - false_negatives_2: 301.9744 - false_positives_2: 349.8974 - loss: 0.3867
```  ```
- 45/59 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8842 - false_negatives_1: 313.1555 - false_positives_1: 357.8222 - loss: 0.3049 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8630 - false_negatives_2: 308.1000 - false_positives_2: 357.5500 - loss: 0.3851
```  ```
- 46/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8843 - false_negatives_1: 319.5000 - false_positives_1: 365.6304 - loss: 0.3048 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8635 - false_negatives_2: 314.3171 - false_positives_2: 364.8781 - loss: 0.3836
```  ```
- 47/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8844 - false_negatives_1: 326.1915 - false_positives_1: 373.2128 - loss: 0.3046 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8640 - false_negatives_2: 320.4762 - false_positives_2: 372.4048 - loss: 0.3822
```  ```
- 48/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8844 - false_negatives_1: 332.6875 - false_positives_1: 381.2292 - loss: 0.3045 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8644 - false_negatives_2: 326.9070 - false_positives_2: 379.8140 - loss: 0.3808
```  ```
- 49/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8844 - false_negatives_1: 339.5306 - false_positives_1: 388.9592 - loss: 0.3044 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8648 - false_negatives_2: 333.2273 - false_positives_2: 387.4773 - loss: 0.3795
```  ```
- 50/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8845 - false_negatives_1: 346.3000 - false_positives_1: 396.6200 - loss: 0.3043 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8652 - false_negatives_2: 339.5555 - false_positives_2: 395.0667 - loss: 0.3782
```  ```
- 51/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8845 - false_negatives_1: 353.1765 - false_positives_1: 404.1765 - loss: 0.3042 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8656 - false_negatives_2: 345.9783 - false_positives_2: 402.4565 - loss: 0.3769
```  ```
- 52/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8846 - false_negatives_1: 359.8654 - false_positives_1: 411.7885 - loss: 0.3041 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8660 - false_negatives_2: 352.2128 - false_positives_2: 409.9362 - loss: 0.3757
```  ```
- 53/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8846 - false_negatives_1: 366.5472 - false_positives_1: 419.3019 - loss: 0.3040 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8664 - false_negatives_2: 358.5417 - false_positives_2: 417.2708 - loss: 0.3745
```  ```
- 54/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8847 - false_negatives_1: 373.2778 - false_positives_1: 426.7408 - loss: 0.3039 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8668 - false_negatives_2: 364.7551 - false_positives_2: 424.7347 - loss: 0.3734
```  ```
- 55/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8848 - false_negatives_1: 380.0000 - false_positives_1: 434.0364 - loss: 0.3037 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8671 - false_negatives_2: 371.2800 - false_positives_2: 432.0600 - loss: 0.3723
```  ```
- 56/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8848 - false_negatives_1: 386.7500 - false_positives_1: 441.3214 - loss: 0.3036 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8675 - false_negatives_2: 377.6471 - false_positives_2: 439.9608 - loss: 0.3713
```  ```
- 57/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8849 - false_negatives_1: 393.3158 - false_positives_1: 448.8070 - loss: 0.3035 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8678 - false_negatives_2: 384.1154 - false_positives_2: 447.6731 - loss: 0.3703
```  ```
- 58/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8850 - false_negatives_1: 399.8276 - false_positives_1: 456.1724 - loss: 0.3033 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8680 - false_negatives_2: 390.4906 - false_positives_2: 455.4906 - loss: 0.3694
```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8850 - false_negatives_1: 406.1695 - false_positives_1: 463.5085 - loss: 0.3032 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8683 - false_negatives_2: 396.7963 - false_positives_2: 463.3518 - loss: 0.3684 -
``` -Epoch 13: val_loss did not improve from 0.36301 + +``` +
+ 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8686 - false_negatives_2: 403.1636 - false_positives_2: 471.0727 - loss: 0.3676 +
+```  ```
- 59/59 ━━━━━━━━━━━━━━━━━━━━ 5s 83ms/step - binary_accuracy: 0.8851 - false_negatives_1: 412.3000 - false_positives_1: 470.6000 - loss: 0.3030 - val_binary_accuracy: 0.8458 - val_false_negatives_1: 445.0000 - val_false_positives_1: 326.0000 - val_loss: 0.3708 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8689 - false_negatives_2: 409.4643 - false_positives_2: 478.8571 - loss: 0.3667 +
+``` + +``` +
+ 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8691 - false_negatives_2: 415.8070 - false_positives_2: 486.7719 - loss: 0.3659
``` -Epoch 13: early stopping + +``` +
+ 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8694 - false_negatives_2: 422.1897 - false_positives_2: 494.7758 - loss: 0.3651 +
+``` + ```
- - 1/20 ━━━━━━━━━━━━━━━━━━━━ 4s 259ms/step + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8696 - false_negatives_2: 428.6102 - false_positives_2: 502.6949 - loss: 0.3643
``` - + ```
- 3/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8699 - false_negatives_2: 434.9167 - false_positives_2: 510.6000 - loss: 0.3636
``` - + ```
- 5/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8701 - false_negatives_2: 441.3607 - false_positives_2: 518.4262 - loss: 0.3629
``` - + ```
- 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8703 - false_negatives_2: 447.7581 - false_positives_2: 526.2742 - loss: 0.3622
``` - + ```
- 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8705 - false_negatives_2: 454.1270 - false_positives_2: 534.0476 - loss: 0.3615 + +
+``` + +``` +
+ 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8707 - false_negatives_2: 460.5156 - false_positives_2: 541.8125 - loss: 0.3608 + +
+``` + +``` +
+ 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8710 - false_negatives_2: 466.7692 - false_positives_2: 549.6154 - loss: 0.3602 + +
+``` + +``` +
+ 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8712 - false_negatives_2: 473.0303 - false_positives_2: 557.3333 - loss: 0.3595 + +
+``` + +``` +
+ 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8714 - false_negatives_2: 479.2239 - false_positives_2: 565.0895 - loss: 0.3589 + +
+``` + +``` +
+ 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8716 - false_negatives_2: 485.4706 - false_positives_2: 572.7500 - loss: 0.3582 + +
+``` + +``` +
+ 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8718 - false_negatives_2: 491.6087 - false_positives_2: 580.4203 - loss: 0.3576 + +
+``` + +``` +
+ 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8720 - false_negatives_2: 497.7429 - false_positives_2: 588.0714 - loss: 0.3570 + +
+``` + +``` +
+ 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8722 - false_negatives_2: 503.9155 - false_positives_2: 595.6901 - loss: 0.3564 + +
+``` + +``` +
+ 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8724 - false_negatives_2: 510.0695 - false_positives_2: 603.4445 - loss: 0.3558
``` - + ```
- 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8726 - false_negatives_2: 516.2328 - false_positives_2: 611.1507 - loss: 0.3553
``` - + ```
- 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8728 - false_negatives_2: 522.3649 - false_positives_2: 618.9730 - loss: 0.3548
``` - + ```
- 15/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8730 - false_negatives_2: 528.6533 - false_positives_2: 626.6667 - loss: 0.3542
``` - + ```
- 17/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8731 - false_negatives_2: 534.8026 - false_positives_2: 634.5658 - loss: 0.3537
``` - + ```
- 19/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8733 - false_negatives_2: 541.0649 - false_positives_2: 642.4026 - loss: 0.3532
``` - + ```
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 40ms/step + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8735 - false_negatives_2: 547.2436 - false_positives_2: 650.2436 - loss: 0.3527 +
``` - +Epoch 1: val_loss did not improve from 0.37074 + + ```
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 40ms/step + 79/79 ━━━━━━━━━━━━━━━━━━━━ 9s 84ms/step - binary_accuracy: 0.8738 - false_negatives_2: 559.2125 - false_positives_2: 665.3375 - loss: 0.3518 - val_binary_accuracy: 0.7932 - val_false_negatives_2: 119.0000 - val_false_positives_2: 915.0000 - val_loss: 0.4949
``` ----------------------------------------------------------------------------------------------------- -Number of zeros incorrectly classified: 492.0, Number of ones incorrectly classified: 325.0 -Sample ratio for positives: 0.397796817625459, Sample ratio for negatives:0.602203182374541 -Starting training with 19999 samples ----------------------------------------------------------------------------------------------------- -Epoch 1/20 +Epoch 2/20 ```
- 1/79 ━━━━━━━━━━━━━━━━━━━━ 3:46 3s/step - binary_accuracy: 0.9180 - false_negatives_2: 10.0000 - false_positives_2: 11.0000 - loss: 0.2373 + 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 92ms/step - binary_accuracy: 0.8750 - false_negatives_2: 2.0000 - false_positives_2: 30.0000 - loss: 0.3469
``` - + ```
- 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8770 - false_negatives_2: 39.5000 - false_positives_2: 13.0000 - loss: 0.3771 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8828 - false_negatives_2: 10.0000 - false_positives_2: 34.0000 - loss: 0.3287
```  ```
- 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8468 - false_negatives_2: 50.0000 - false_positives_2: 39.6667 - loss: 0.4561 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8885 - false_negatives_2: 14.0000 - false_positives_2: 41.0000 - loss: 0.3114
```  ```
- 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8394 - false_negatives_2: 57.0000 - false_positives_2: 57.0000 - loss: 0.4767 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8902 - false_negatives_2: 21.7500 - false_positives_2: 46.2500 - loss: 0.3052
```  ```
- 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8362 - false_negatives_2: 66.2000 - false_positives_2: 70.2000 - loss: 0.4807 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8894 - false_negatives_2: 28.2000 - false_positives_2: 55.4000 - loss: 0.3048
```  ```
- 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8358 - false_negatives_2: 73.3333 - false_positives_2: 83.0000 - loss: 0.4778 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8901 - false_negatives_2: 34.8333 - false_positives_2: 62.0000 - loss: 0.3023
```  ```
- 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8360 - false_negatives_2: 82.0000 - false_positives_2: 93.5714 - loss: 0.4729 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8910 - false_negatives_2: 40.7143 - false_positives_2: 68.8571 - loss: 0.3004
```  ```
- 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8370 - false_negatives_2: 90.3750 - false_positives_2: 103.2500 - loss: 0.4671 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8920 - false_negatives_2: 46.3750 - false_positives_2: 75.2500 - loss: 0.2980
``` - + ```
- 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8383 - false_negatives_2: 98.0000 - false_positives_2: 112.8889 - loss: 0.4611 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8930 - false_negatives_2: 51.7778 - false_positives_2: 81.6667 - loss: 0.2961
``` - + ```
- 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8395 - false_negatives_2: 105.2000 - false_positives_2: 122.8000 - loss: 0.4553 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8942 - false_negatives_2: 56.8000 - false_positives_2: 87.8000 - loss: 0.2938
``` - + ```
- 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8406 - false_negatives_2: 112.9091 - false_positives_2: 132.2727 - loss: 0.4502 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8950 - false_negatives_2: 62.4545 - false_positives_2: 93.8182 - loss: 0.2920
``` - + ```
- 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8419 - false_negatives_2: 120.0000 - false_positives_2: 141.5833 - loss: 0.4452 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8955 - false_negatives_2: 68.0833 - false_positives_2: 100.5833 - loss: 0.2908
``` - + ```
- 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8434 - false_negatives_2: 127.0000 - false_positives_2: 150.1538 - loss: 0.4401 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8957 - false_negatives_2: 74.5385 - false_positives_2: 107.0000 - loss: 0.2901
``` - + ```
- 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8446 - false_negatives_2: 134.0714 - false_positives_2: 158.8571 - loss: 0.4357 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8959 - false_negatives_2: 80.3571 - false_positives_2: 114.2143 - loss: 0.2894
``` - + ```
- 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8457 - false_negatives_2: 141.3333 - false_positives_2: 167.8000 - loss: 0.4319 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8961 - false_negatives_2: 86.3333 - false_positives_2: 121.2667 - loss: 0.2888
``` - + ```
- 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8465 - false_negatives_2: 148.9375 - false_positives_2: 177.1875 - loss: 0.4286 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8961 - false_negatives_2: 92.3750 - false_positives_2: 128.8125 - loss: 0.2885
``` - + ```
- 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8473 - false_negatives_2: 156.7647 - false_positives_2: 186.0588 - loss: 0.4255 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8962 - false_negatives_2: 98.4118 - false_positives_2: 135.9412 - loss: 0.2882
``` - + ```
- 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8479 - false_negatives_2: 164.5556 - false_positives_2: 195.1667 - loss: 0.4227 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8963 - false_negatives_2: 104.3889 - false_positives_2: 143.1667 - loss: 0.2879
```  ```
- 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8486 - false_negatives_2: 172.3684 - false_positives_2: 204.2632 - loss: 0.4199 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8963 - false_negatives_2: 111.0000 - false_positives_2: 149.9474 - loss: 0.2877
```  ```
- 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8493 - false_negatives_2: 180.0000 - false_positives_2: 212.8500 - loss: 0.4172 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8963 - false_negatives_2: 117.3500 - false_positives_2: 157.2500 - loss: 0.2876
```  ```
- 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8500 - false_negatives_2: 187.1905 - false_positives_2: 221.8571 - loss: 0.4145 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8963 - false_negatives_2: 123.4286 - false_positives_2: 164.4286 - loss: 0.2874
```  ```
- 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8505 - false_negatives_2: 195.0909 - false_positives_2: 230.5909 - loss: 0.4121 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8964 - false_negatives_2: 129.5909 - false_positives_2: 171.4545 - loss: 0.2871
```  ```
- 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8511 - false_negatives_2: 202.4783 - false_positives_2: 239.4348 - loss: 0.4098 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8963 - false_negatives_2: 135.4348 - false_positives_2: 179.1739 - loss: 0.2870
```  ```
- 24/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8517 - false_negatives_2: 210.0417 - false_positives_2: 248.0833 - loss: 0.4076 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8963 - false_negatives_2: 141.7500 - false_positives_2: 186.4583 - loss: 0.2868
```  ```
- 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8523 - false_negatives_2: 217.3200 - false_positives_2: 256.8800 - loss: 0.4055 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8963 - false_negatives_2: 147.7200 - false_positives_2: 194.2000 - loss: 0.2867
```  ```
- 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8529 - false_negatives_2: 224.4231 - false_positives_2: 265.4615 - loss: 0.4034 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8962 - false_negatives_2: 154.1538 - false_positives_2: 201.6923 - loss: 0.2865
```  ```
- 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8534 - false_negatives_2: 231.5556 - false_positives_2: 274.0370 - loss: 0.4015 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8961 - false_negatives_2: 160.3704 - false_positives_2: 209.3333 - loss: 0.2863
```  ```
- 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8539 - false_negatives_2: 238.7500 - false_positives_2: 282.4643 - loss: 0.3996 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8960 - false_negatives_2: 167.0000 - false_positives_2: 216.8214 - loss: 0.2862
```  ```
- 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8545 - false_negatives_2: 245.5862 - false_positives_2: 291.0690 - loss: 0.3977 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 173.3448 - false_positives_2: 224.7241 - loss: 0.2861
```  ```
- 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8550 - false_negatives_2: 252.8667 - false_positives_2: 299.3000 - loss: 0.3960 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8958 - false_negatives_2: 179.9333 - false_positives_2: 232.4333 - loss: 0.2861
```  ```
- 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8555 - false_negatives_2: 259.8065 - false_positives_2: 307.9032 - loss: 0.3943 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 186.3871 - false_positives_2: 240.1290 - loss: 0.2860
```  ```
- 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8559 - false_negatives_2: 267.1250 - false_positives_2: 316.1562 - loss: 0.3927 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8956 - false_negatives_2: 192.7188 - false_positives_2: 247.7812 - loss: 0.2860
```  ```
- 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8563 - false_negatives_2: 274.2727 - false_positives_2: 324.4546 - loss: 0.3911 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 199.2121 - false_positives_2: 255.3636 - loss: 0.2859
```  ```
- 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8568 - false_negatives_2: 281.4118 - false_positives_2: 332.5294 - loss: 0.3895 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 205.7353 - false_positives_2: 262.7353 - loss: 0.2859
```  ```
- 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8573 - false_negatives_2: 288.5143 - false_positives_2: 340.5428 - loss: 0.3880 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 212.0286 - false_positives_2: 270.0286 - loss: 0.2858
```  ```
- 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8577 - false_negatives_2: 295.6111 - false_positives_2: 348.5555 - loss: 0.3865 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 218.2222 - false_positives_2: 277.1667 - loss: 0.2857
```  ```
- 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8581 - false_negatives_2: 302.7027 - false_positives_2: 356.7027 - loss: 0.3851 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 224.5135 - false_positives_2: 284.2433 - loss: 0.2856
```  ```
- 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8584 - false_negatives_2: 310.2895 - false_positives_2: 364.6053 - loss: 0.3838 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 230.5526 - false_positives_2: 291.4737 - loss: 0.2855
```  ```
- 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8588 - false_negatives_2: 317.5898 - false_positives_2: 372.7180 - loss: 0.3825 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 236.9231 - false_positives_2: 298.4359 - loss: 0.2854
```  ```
- 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8592 - false_negatives_2: 324.9000 - false_positives_2: 380.6250 - loss: 0.3812 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 243.0750 - false_positives_2: 305.8500 - loss: 0.2853
```  ```
- 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8595 - false_negatives_2: 332.0976 - false_positives_2: 388.6342 - loss: 0.3800 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 249.4390 - false_positives_2: 313.0732 - loss: 0.2853
```  ```
- 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8598 - false_negatives_2: 339.4286 - false_positives_2: 396.4286 - loss: 0.3788 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 255.6190 - false_positives_2: 320.4286 - loss: 0.2852
```  ```
- 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8602 - false_negatives_2: 346.6046 - false_positives_2: 404.5116 - loss: 0.3777 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 261.7675 - false_positives_2: 327.6744 - loss: 0.2852
```  ```
- 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8605 - false_negatives_2: 354.0000 - false_positives_2: 412.4546 - loss: 0.3766 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 267.8409 - false_positives_2: 335.0682 - loss: 0.2851
```  ```
- 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8607 - false_negatives_2: 361.2444 - false_positives_2: 420.6000 - loss: 0.3756 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 274.0222 - false_positives_2: 342.2889 - loss: 0.2850
```  ```
- 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8610 - false_negatives_2: 368.4783 - false_positives_2: 428.6522 - loss: 0.3745 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 280.0000 - false_positives_2: 349.5000 - loss: 0.2849
```  ```
- 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8613 - false_negatives_2: 375.7234 - false_positives_2: 436.7021 - loss: 0.3736 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8954 - false_negatives_2: 285.9575 - false_positives_2: 356.6170 - loss: 0.2848
```  ```
- 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8616 - false_negatives_2: 382.8333 - false_positives_2: 444.8125 - loss: 0.3726 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 291.8542 - false_positives_2: 363.8542 - loss: 0.2847
```  ```
- 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8618 - false_negatives_2: 390.0204 - false_positives_2: 452.8979 - loss: 0.3717 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 297.8776 - false_positives_2: 371.0408 - loss: 0.2846
```  ```
- 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8621 - false_negatives_2: 397.1400 - false_positives_2: 461.2200 - loss: 0.3708 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 303.8800 - false_positives_2: 378.2000 - loss: 0.2845
```  ```
- 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8623 - false_negatives_2: 404.4510 - false_positives_2: 469.3529 - loss: 0.3700 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 309.7059 - false_positives_2: 385.4510 - loss: 0.2844
```  ```
- 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8625 - false_negatives_2: 411.4808 - false_positives_2: 477.7115 - loss: 0.3692 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8955 - false_negatives_2: 315.7500 - false_positives_2: 392.5962 - loss: 0.2843
```  ```
- 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8628 - false_negatives_2: 418.7547 - false_positives_2: 485.8491 - loss: 0.3684 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8956 - false_negatives_2: 321.6415 - false_positives_2: 399.7547 - loss: 0.2842
```  ```
- 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8630 - false_negatives_2: 425.9259 - false_positives_2: 494.0000 - loss: 0.3676 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8956 - false_negatives_2: 327.6111 - false_positives_2: 406.8889 - loss: 0.2841
```  ```
- 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8632 - false_negatives_2: 433.2182 - false_positives_2: 502.2727 - loss: 0.3668 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8956 - false_negatives_2: 333.6182 - false_positives_2: 414.0000 - loss: 0.2840
```  ```
- 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8634 - false_negatives_2: 440.6964 - false_positives_2: 510.4464 - loss: 0.3662 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8956 - false_negatives_2: 339.5536 - false_positives_2: 421.0536 - loss: 0.2839
```  ```
- 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8635 - false_negatives_2: 448.0000 - false_positives_2: 518.8246 - loss: 0.3655 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 345.5263 - false_positives_2: 427.9649 - loss: 0.2838
```  ```
- 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8637 - false_negatives_2: 455.3276 - false_positives_2: 527.0690 - loss: 0.3648 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 351.4138 - false_positives_2: 435.0862 - loss: 0.2837
```  ```
- 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8639 - false_negatives_2: 462.5424 - false_positives_2: 535.4407 - loss: 0.3642 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 357.4746 - false_positives_2: 442.0169 - loss: 0.2836
```  ```
- 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8641 - false_negatives_2: 469.9000 - false_positives_2: 543.7167 - loss: 0.3636 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 363.4167 - false_positives_2: 449.2333 - loss: 0.2835
```  ```
- 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8642 - false_negatives_2: 477.1803 - false_positives_2: 551.9180 - loss: 0.3630 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 369.4754 - false_positives_2: 456.3607 - loss: 0.2834
```  ```
- 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8644 - false_negatives_2: 484.3387 - false_positives_2: 560.1290 - loss: 0.3623 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8957 - false_negatives_2: 375.4516 - false_positives_2: 463.4516 - loss: 0.2834
```  ```
- 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8646 - false_negatives_2: 491.6984 - false_positives_2: 568.1905 - loss: 0.3618 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8958 - false_negatives_2: 381.4762 - false_positives_2: 470.4762 - loss: 0.2833
```  ```
- 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8648 - false_negatives_2: 498.8906 - false_positives_2: 576.3906 - loss: 0.3612 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8958 - false_negatives_2: 387.3906 - false_positives_2: 477.5469 - loss: 0.2832
```  ```
- 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8649 - false_negatives_2: 506.1692 - false_positives_2: 584.5385 - loss: 0.3606 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8958 - false_negatives_2: 393.3692 - false_positives_2: 484.6308 - loss: 0.2832
```  ```
- 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8651 - false_negatives_2: 513.3939 - false_positives_2: 592.6818 - loss: 0.3601 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8958 - false_negatives_2: 399.3636 - false_positives_2: 491.6515 - loss: 0.2831
```  ```
- 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8652 - false_negatives_2: 520.6269 - false_positives_2: 600.7761 - loss: 0.3595 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 405.2537 - false_positives_2: 498.6866 - loss: 0.2831
```  ```
- 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8654 - false_negatives_2: 527.8235 - false_positives_2: 608.8383 - loss: 0.3590 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 411.2500 - false_positives_2: 505.6912 - loss: 0.2830
```  ```
- 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8655 - false_negatives_2: 535.0580 - false_positives_2: 616.8986 - loss: 0.3584 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 417.1449 - false_positives_2: 512.8406 - loss: 0.2830
```  ```
- 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8657 - false_negatives_2: 542.1714 - false_positives_2: 625.0143 - loss: 0.3579 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 423.1714 - false_positives_2: 519.8286 - loss: 0.2829
```  ```
- 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8658 - false_negatives_2: 549.3803 - false_positives_2: 633.0141 - loss: 0.3574 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 429.0704 - false_positives_2: 527.0000 - loss: 0.2829
```  ```
- 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8660 - false_negatives_2: 556.5139 - false_positives_2: 641.1667 - loss: 0.3569 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8959 - false_negatives_2: 435.0278 - false_positives_2: 534.1111 - loss: 0.2828
```  ```
- 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8661 - false_negatives_2: 563.7808 - false_positives_2: 649.2055 - loss: 0.3564 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8960 - false_negatives_2: 441.0137 - false_positives_2: 541.1644 - loss: 0.2828
```  ```
- 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8663 - false_negatives_2: 570.9189 - false_positives_2: 657.3919 - loss: 0.3559 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8960 - false_negatives_2: 446.8919 - false_positives_2: 548.2162 - loss: 0.2827
```  ```
- 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8664 - false_negatives_2: 578.2933 - false_positives_2: 665.4800 - loss: 0.3555 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8960 - false_negatives_2: 452.7867 - false_positives_2: 555.2267 - loss: 0.2826
```  ```
- 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8665 - false_negatives_2: 585.5921 - false_positives_2: 673.6711 - loss: 0.3551 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8960 - false_negatives_2: 458.6316 - false_positives_2: 562.2105 - loss: 0.2826
```  ```
- 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8666 - false_negatives_2: 592.9091 - false_positives_2: 681.8442 - loss: 0.3546 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8961 - false_negatives_2: 464.4416 - false_positives_2: 569.1818 - loss: 0.2825
```  ```
- 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8667 - false_negatives_2: 600.1411 - false_positives_2: 690.0128 - loss: 0.3542 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8961 - false_negatives_2: 470.2436 - false_positives_2: 576.1539 - loss: 0.2824
``` -Epoch 1: val_loss improved from 0.36301 to 0.35152, saving model to AL_Model.keras +Epoch 2: val_loss did not improve from 0.37074  ```
- 79/79 ━━━━━━━━━━━━━━━━━━━━ 10s 85ms/step - binary_accuracy: 0.8670 - false_negatives_2: 614.1125 - false_positives_2: 705.7625 - loss: 0.3534 - val_binary_accuracy: 0.8542 - val_false_negatives_2: 387.0000 - val_false_positives_2: 342.0000 - val_loss: 0.3515 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8962 - false_negatives_2: 481.4125 - false_positives_2: 589.6750 - loss: 0.2823 - val_binary_accuracy: 0.8014 - val_false_negatives_2: 809.0000 - val_false_positives_2: 184.0000 - val_loss: 0.4580
``` -Epoch 2/20 +Epoch 3/20 ```
- 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 91ms/step - binary_accuracy: 0.9180 - false_negatives_2: 9.0000 - false_positives_2: 12.0000 - loss: 0.2507 + 1/79 ━━━━━━━━━━━━━━━━━━━━ 6s 89ms/step - binary_accuracy: 0.8594 - false_negatives_2: 30.0000 - false_positives_2: 6.0000 - loss: 0.3046
```  ```
- 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9199 - false_negatives_2: 16.0000 - false_positives_2: 14.5000 - loss: 0.2499 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 70ms/step - binary_accuracy: 0.8770 - false_negatives_2: 31.5000 - false_positives_2: 13.5000 - loss: 0.2866
```  ```
- 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9167 - false_negatives_2: 20.0000 - false_positives_2: 23.3333 - loss: 0.2550 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8850 - false_negatives_2: 36.0000 - false_positives_2: 19.3333 - loss: 0.2800
```  ```
- 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9141 - false_negatives_2: 26.5000 - false_positives_2: 30.0000 - loss: 0.2574 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8905 - false_negatives_2: 40.0000 - false_positives_2: 25.2500 - loss: 0.2738
```  ```
- 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9125 - false_negatives_2: 33.4000 - false_positives_2: 35.8000 - loss: 0.2591 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8934 - false_negatives_2: 44.8000 - false_positives_2: 31.8000 - loss: 0.2729
```  ```
- 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9117 - false_negatives_2: 39.1667 - false_positives_2: 42.1667 - loss: 0.2592 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8952 - false_negatives_2: 50.0000 - false_positives_2: 38.3333 - loss: 0.2718
```  ```
- 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9096 - false_negatives_2: 47.2857 - false_positives_2: 48.7143 - loss: 0.2614 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8966 - false_negatives_2: 55.4286 - false_positives_2: 44.5714 - loss: 0.2706
```  ```
- 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9077 - false_negatives_2: 53.7500 - false_positives_2: 57.3750 - loss: 0.2638 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8979 - false_negatives_2: 60.5000 - false_positives_2: 50.8750 - loss: 0.2693
```  ```
- 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9053 - false_negatives_2: 63.2222 - false_positives_2: 64.6667 - loss: 0.2666 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8991 - false_negatives_2: 65.3333 - false_positives_2: 56.8889 - loss: 0.2680
```  ```
- 10/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9032 - false_negatives_2: 71.0000 - false_positives_2: 73.8000 - loss: 0.2689 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9004 - false_negatives_2: 70.1000 - false_positives_2: 62.4000 - loss: 0.2662
```  ```
- 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9011 - false_negatives_2: 80.4545 - false_positives_2: 81.7273 - loss: 0.2714 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9014 - false_negatives_2: 74.3636 - false_positives_2: 68.8182 - loss: 0.2651
```  ```
- 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8991 - false_negatives_2: 88.8333 - false_positives_2: 91.5000 - loss: 0.2740 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9019 - false_negatives_2: 80.4167 - false_positives_2: 74.6667 - loss: 0.2645
```  ```
- 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8974 - false_negatives_2: 97.6923 - false_positives_2: 100.0000 - loss: 0.2762 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9020 - false_negatives_2: 85.9231 - false_positives_2: 81.9231 - loss: 0.2646
``` - + ```
- 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8962 - false_negatives_2: 105.8571 - false_positives_2: 108.5000 - loss: 0.2781 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9022 - false_negatives_2: 92.0000 - false_positives_2: 88.4286 - loss: 0.2648
``` - + ```
- 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8951 - false_negatives_2: 113.7333 - false_positives_2: 116.8667 - loss: 0.2796 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9021 - false_negatives_2: 98.0667 - false_positives_2: 95.6000 - loss: 0.2650
``` - + ```
- 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8943 - false_negatives_2: 121.6250 - false_positives_2: 124.9375 - loss: 0.2808 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9021 - false_negatives_2: 104.5000 - false_positives_2: 102.2500 - loss: 0.2652
```  ```
- 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8935 - false_negatives_2: 129.4706 - false_positives_2: 132.9412 - loss: 0.2820 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9020 - false_negatives_2: 110.7059 - false_positives_2: 109.2941 - loss: 0.2654
```  ```
- 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8929 - false_negatives_2: 136.8333 - false_positives_2: 140.9444 - loss: 0.2829 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9020 - false_negatives_2: 116.8333 - false_positives_2: 116.1667 - loss: 0.2656
```  ```
- 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8924 - false_negatives_2: 144.6316 - false_positives_2: 148.3684 - loss: 0.2837 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9020 - false_negatives_2: 122.5789 - false_positives_2: 122.8947 - loss: 0.2655
```  ```
- 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8920 - false_negatives_2: 151.7000 - false_positives_2: 156.5500 - loss: 0.2845 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9021 - false_negatives_2: 128.5000 - false_positives_2: 129.4000 - loss: 0.2655
```  ```
- 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8916 - false_negatives_2: 159.3810 - false_positives_2: 164.1429 - loss: 0.2852 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9023 - false_negatives_2: 134.1905 - false_positives_2: 135.6190 - loss: 0.2654
```  ```
- 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8911 - false_negatives_2: 166.6818 - false_positives_2: 172.1818 - loss: 0.2858 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9024 - false_negatives_2: 139.8182 - false_positives_2: 142.0000 - loss: 0.2653
```  ```
- 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8908 - false_negatives_2: 174.4783 - false_positives_2: 179.7826 - loss: 0.2866 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9026 - false_negatives_2: 145.2609 - false_positives_2: 148.2174 - loss: 0.2651
```  ```
- 24/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8905 - false_negatives_2: 181.9583 - false_positives_2: 187.3333 - loss: 0.2872 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9028 - false_negatives_2: 150.5833 - false_positives_2: 154.4167 - loss: 0.2649
```  ```
- 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8902 - false_negatives_2: 189.2000 - false_positives_2: 194.9600 - loss: 0.2877 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9030 - false_negatives_2: 155.7200 - false_positives_2: 160.5200 - loss: 0.2646
```  ```
- 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8899 - false_negatives_2: 196.6923 - false_positives_2: 202.5769 - loss: 0.2882 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9033 - false_negatives_2: 160.7692 - false_positives_2: 166.4615 - loss: 0.2643
```  ```
- 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8897 - false_negatives_2: 204.0741 - false_positives_2: 210.0370 - loss: 0.2886 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9035 - false_negatives_2: 165.7037 - false_positives_2: 172.6667 - loss: 0.2640
```  ```
- 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8895 - false_negatives_2: 211.3929 - false_positives_2: 217.6071 - loss: 0.2890 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9036 - false_negatives_2: 171.2857 - false_positives_2: 178.6429 - loss: 0.2639
```  ```
- 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8894 - false_negatives_2: 218.5862 - false_positives_2: 225.2069 - loss: 0.2893 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9037 - false_negatives_2: 176.5172 - false_positives_2: 185.4138 - loss: 0.2639
```  ```
- 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8892 - false_negatives_2: 225.7667 - false_positives_2: 232.8000 - loss: 0.2896 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9038 - false_negatives_2: 182.1000 - false_positives_2: 191.8000 - loss: 0.2640
```  ```
- 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8891 - false_negatives_2: 232.7742 - false_positives_2: 240.2903 - loss: 0.2898 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9039 - false_negatives_2: 187.4839 - false_positives_2: 198.3871 - loss: 0.2640
```  ```
- 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8890 - false_negatives_2: 239.7188 - false_positives_2: 247.7500 - loss: 0.2900 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9040 - false_negatives_2: 192.8438 - false_positives_2: 204.7500 - loss: 0.2640
```  ```
- 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8889 - false_negatives_2: 246.9697 - false_positives_2: 255.0000 - loss: 0.2901 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9041 - false_negatives_2: 198.1515 - false_positives_2: 211.0303 - loss: 0.2639
```  ```
- 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8888 - false_negatives_2: 253.7941 - false_positives_2: 262.9118 - loss: 0.2903 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9042 - false_negatives_2: 203.5294 - false_positives_2: 217.3235 - loss: 0.2638
```  ```
- 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8885 - false_negatives_2: 262.0000 - false_positives_2: 270.4857 - loss: 0.2907 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9043 - false_negatives_2: 208.8857 - false_positives_2: 223.4286 - loss: 0.2638
```  ```
- 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8883 - false_negatives_2: 270.0000 - false_positives_2: 278.4445 - loss: 0.2910 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9044 - false_negatives_2: 214.1389 - false_positives_2: 229.4444 - loss: 0.2636
```  ```
- 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8881 - false_negatives_2: 277.6757 - false_positives_2: 286.3243 - loss: 0.2914 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9045 - false_negatives_2: 219.3513 - false_positives_2: 235.4865 - loss: 0.2635
```  ```
- 38/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8879 - false_negatives_2: 285.2368 - false_positives_2: 294.2105 - loss: 0.2917 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9047 - false_negatives_2: 224.5000 - false_positives_2: 241.5000 - loss: 0.2634
```  ```
- 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8878 - false_negatives_2: 292.7692 - false_positives_2: 301.9231 - loss: 0.2919 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9048 - false_negatives_2: 229.6923 - false_positives_2: 247.3846 - loss: 0.2632
```  ```
- 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8876 - false_negatives_2: 300.4000 - false_positives_2: 309.7250 - loss: 0.2922 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9049 - false_negatives_2: 234.8250 - false_positives_2: 253.4000 - loss: 0.2631
```  ```
- 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8875 - false_negatives_2: 307.9024 - false_positives_2: 317.6097 - loss: 0.2925 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9051 - false_negatives_2: 240.1219 - false_positives_2: 259.4146 - loss: 0.2630
```  ```
- 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8874 - false_negatives_2: 315.4286 - false_positives_2: 325.4762 - loss: 0.2928 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9052 - false_negatives_2: 245.2857 - false_positives_2: 265.5952 - loss: 0.2628
```  ```
- 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8872 - false_negatives_2: 322.9070 - false_positives_2: 333.1860 - loss: 0.2930 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9052 - false_negatives_2: 250.6744 - false_positives_2: 271.6279 - loss: 0.2627
```  ```
- 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8872 - false_negatives_2: 330.1818 - false_positives_2: 340.8636 - loss: 0.2932 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9053 - false_negatives_2: 256.1136 - false_positives_2: 277.7273 - loss: 0.2626
```  ```
- 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8871 - false_negatives_2: 337.7111 - false_positives_2: 348.3778 - loss: 0.2934 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9054 - false_negatives_2: 261.5111 - false_positives_2: 283.9556 - loss: 0.2626
```  ```
- 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8870 - false_negatives_2: 345.1304 - false_positives_2: 356.1087 - loss: 0.2936 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9054 - false_negatives_2: 267.1304 - false_positives_2: 290.1087 - loss: 0.2625
```  ```
- 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8869 - false_negatives_2: 352.5319 - false_positives_2: 363.7021 - loss: 0.2938 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9055 - false_negatives_2: 272.6596 - false_positives_2: 296.5745 - loss: 0.2625
```  ```
- 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8868 - false_negatives_2: 359.8333 - false_positives_2: 371.2708 - loss: 0.2940 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9055 - false_negatives_2: 278.1042 - false_positives_2: 303.0625 - loss: 0.2625
```  ```
- 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8868 - false_negatives_2: 367.1021 - false_positives_2: 378.7143 - loss: 0.2941 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9055 - false_negatives_2: 283.7347 - false_positives_2: 309.5918 - loss: 0.2625
```  ```
- 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8867 - false_negatives_2: 374.2200 - false_positives_2: 386.3400 - loss: 0.2942 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9055 - false_negatives_2: 289.2000 - false_positives_2: 316.2000 - loss: 0.2625
```  ```
- 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8866 - false_negatives_2: 381.5294 - false_positives_2: 393.9412 - loss: 0.2943 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9055 - false_negatives_2: 294.7647 - false_positives_2: 322.7059 - loss: 0.2625
```  ```
- 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8866 - false_negatives_2: 388.6538 - false_positives_2: 401.8077 - loss: 0.2945 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9056 - false_negatives_2: 300.2692 - false_positives_2: 329.2115 - loss: 0.2625
```  ```
- 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8865 - false_negatives_2: 396.0000 - false_positives_2: 409.5283 - loss: 0.2946 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9056 - false_negatives_2: 305.6604 - false_positives_2: 335.6981 - loss: 0.2625
```  ```
- 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8864 - false_negatives_2: 403.2037 - false_positives_2: 417.3518 - loss: 0.2947 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9056 - false_negatives_2: 311.2778 - false_positives_2: 342.1852 - loss: 0.2625
```  ```
- 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8864 - false_negatives_2: 410.3273 - false_positives_2: 425.1273 - loss: 0.2948 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9056 - false_negatives_2: 316.8909 - false_positives_2: 348.8182 - loss: 0.2625
```  ```
- 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8864 - false_negatives_2: 417.3750 - false_positives_2: 432.8036 - loss: 0.2949 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9056 - false_negatives_2: 322.3929 - false_positives_2: 355.4286 - loss: 0.2626
```  ```
- 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8863 - false_negatives_2: 424.3684 - false_positives_2: 440.5263 - loss: 0.2950 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9056 - false_negatives_2: 327.9123 - false_positives_2: 362.0000 - loss: 0.2626
```  ```
- 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8863 - false_negatives_2: 431.4828 - false_positives_2: 448.2242 - loss: 0.2950 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 333.2931 - false_positives_2: 368.5172 - loss: 0.2626
```  ```
- 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8862 - false_negatives_2: 438.6441 - false_positives_2: 455.9153 - loss: 0.2951 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 338.6949 - false_positives_2: 374.8813 - loss: 0.2626
```  ```
- 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8862 - false_negatives_2: 445.6833 - false_positives_2: 463.7167 - loss: 0.2952 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 344.0000 - false_positives_2: 381.4000 - loss: 0.2626
```  ```
- 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8862 - false_negatives_2: 452.7213 - false_positives_2: 471.3770 - loss: 0.2953 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 349.6230 - false_positives_2: 387.8033 - loss: 0.2626
```  ```
- 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8861 - false_negatives_2: 459.6129 - false_positives_2: 479.2903 - loss: 0.2954 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 355.1452 - false_positives_2: 394.4193 - loss: 0.2627
```  ```
- 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8861 - false_negatives_2: 466.6667 - false_positives_2: 487.0159 - loss: 0.2955 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 360.7460 - false_positives_2: 400.9048 - loss: 0.2627
```  ```
- 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8861 - false_negatives_2: 473.5938 - false_positives_2: 494.7656 - loss: 0.2955 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 366.2344 - false_positives_2: 407.6094 - loss: 0.2627
```  ```
- 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 480.4923 - false_positives_2: 502.4462 - loss: 0.2956 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 371.8615 - false_positives_2: 414.2615 - loss: 0.2628
```  ```
- 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 487.3182 - false_positives_2: 510.2576 - loss: 0.2957 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9057 - false_negatives_2: 377.4243 - false_positives_2: 420.9697 - loss: 0.2628
```  ```
- 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 494.1194 - false_positives_2: 518.0895 - loss: 0.2957 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 382.9254 - false_positives_2: 427.6119 - loss: 0.2628
```  ```
- 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 500.9412 - false_positives_2: 525.8088 - loss: 0.2958 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 388.3824 - false_positives_2: 434.1471 - loss: 0.2628
```  ```
- 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 507.7391 - false_positives_2: 533.4637 - loss: 0.2958 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 393.7536 - false_positives_2: 440.7826 - loss: 0.2628
```  ```
- 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 514.6286 - false_positives_2: 540.9857 - loss: 0.2958 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 399.1714 - false_positives_2: 447.3286 - loss: 0.2628
```  ```
- 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 521.4507 - false_positives_2: 548.5775 - loss: 0.2959 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 404.5634 - false_positives_2: 453.9437 - loss: 0.2628
```  ```
- 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 528.2639 - false_positives_2: 556.1250 - loss: 0.2959 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 409.9583 - false_positives_2: 460.5417 - loss: 0.2628
```  ```
- 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 535.0137 - false_positives_2: 563.7260 - loss: 0.2959 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9058 - false_negatives_2: 415.2740 - false_positives_2: 467.1507 - loss: 0.2628
```  ```
- 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 541.8108 - false_positives_2: 571.2838 - loss: 0.2959 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 420.6892 - false_positives_2: 473.6351 - loss: 0.2628
```  ```
- 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 548.5600 - false_positives_2: 578.9467 - loss: 0.2960 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 426.0000 - false_positives_2: 480.4133 - loss: 0.2628
```  ```
- 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 555.4079 - false_positives_2: 586.5000 - loss: 0.2960 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9058 - false_negatives_2: 431.4079 - false_positives_2: 487.1053 - loss: 0.2628
```  ```
- 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 562.1948 - false_positives_2: 594.2208 - loss: 0.2960 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9059 - false_negatives_2: 436.7922 - false_positives_2: 493.8182 - loss: 0.2628
```  ```
- 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8860 - false_negatives_2: 569.0769 - false_positives_2: 601.8589 - loss: 0.2960 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9059 - false_negatives_2: 442.2051 - false_positives_2: 500.5385 - loss: 0.2628
``` -Epoch 2: val_loss did not improve from 0.35152 +Epoch 3: val_loss did not improve from 0.37074  ```
- 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 81ms/step - binary_accuracy: 0.8859 - false_negatives_2: 582.3250 - false_positives_2: 616.7125 - loss: 0.2960 - val_binary_accuracy: 0.8144 - val_false_negatives_2: 754.0000 - val_false_positives_2: 174.0000 - val_loss: 0.4200 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.9059 - false_negatives_2: 452.6750 - false_positives_2: 513.5250 - loss: 0.2629 - val_binary_accuracy: 0.8294 - val_false_negatives_2: 302.0000 - val_false_positives_2: 551.0000 - val_loss: 0.3868
``` -Epoch 3/20 +Epoch 4/20 ```
- 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 92ms/step - binary_accuracy: 0.8984 - false_negatives_2: 21.0000 - false_positives_2: 5.0000 - loss: 0.2790 + 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 91ms/step - binary_accuracy: 0.9414 - false_negatives_2: 4.0000 - false_positives_2: 11.0000 - loss: 0.1996
```  ```
- 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8984 - false_negatives_2: 26.0000 - false_positives_2: 13.0000 - loss: 0.2774 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9385 - false_negatives_2: 11.0000 - false_positives_2: 13.0000 - loss: 0.2107
```  ```
- 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8984 - false_negatives_2: 31.3333 - false_positives_2: 20.6667 - loss: 0.2762 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9355 - false_negatives_2: 15.0000 - false_positives_2: 19.0000 - loss: 0.2181
```  ```
- 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8989 - false_negatives_2: 37.7500 - false_positives_2: 26.7500 - loss: 0.2742 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9336 - false_negatives_2: 19.2500 - false_positives_2: 24.7500 - loss: 0.2222
```  ```
- 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8990 - false_negatives_2: 43.0000 - false_positives_2: 34.4000 - loss: 0.2733 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9328 - false_negatives_2: 22.6000 - false_positives_2: 30.6000 - loss: 0.2251
```  ```
- 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8992 - false_negatives_2: 49.3333 - false_positives_2: 40.6667 - loss: 0.2730 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9329 - false_negatives_2: 26.0000 - false_positives_2: 35.3333 - loss: 0.2251
```  ```
- 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8992 - false_negatives_2: 54.7143 - false_positives_2: 48.2857 - loss: 0.2728 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9334 - false_negatives_2: 29.4286 - false_positives_2: 39.5714 - loss: 0.2241
```  ```
- 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8995 - false_negatives_2: 60.7500 - false_positives_2: 54.6250 - loss: 0.2725 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9337 - false_negatives_2: 33.1250 - false_positives_2: 43.6250 - loss: 0.2227
```  ```
- 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8996 - false_negatives_2: 66.2222 - false_positives_2: 61.7778 - loss: 0.2720 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9337 - false_negatives_2: 36.5556 - false_positives_2: 48.6667 - loss: 0.2217
```  ```
- 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9000 - false_negatives_2: 71.7000 - false_positives_2: 68.2000 - loss: 0.2711 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9336 - false_negatives_2: 40.5000 - false_positives_2: 53.4000 - loss: 0.2208
```  ```
- 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9005 - false_negatives_2: 76.9091 - false_positives_2: 74.4545 - loss: 0.2701 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9332 - false_negatives_2: 44.7273 - false_positives_2: 58.8182 - loss: 0.2210
```  ```
- 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9009 - false_negatives_2: 82.4167 - false_positives_2: 80.6667 - loss: 0.2696 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9326 - false_negatives_2: 49.8333 - false_positives_2: 63.9167 - loss: 0.2213
```  ```
- 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9014 - false_negatives_2: 87.5385 - false_positives_2: 86.6154 - loss: 0.2685 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9322 - false_negatives_2: 54.5385 - false_positives_2: 69.0769 - loss: 0.2214
```  ```
- 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9019 - false_negatives_2: 92.8571 - false_positives_2: 92.3571 - loss: 0.2676 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9318 - false_negatives_2: 59.7143 - false_positives_2: 73.9286 - loss: 0.2216
```  ```
- 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9024 - false_negatives_2: 98.0000 - false_positives_2: 98.1333 - loss: 0.2667 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9315 - false_negatives_2: 64.4667 - false_positives_2: 78.9333 - loss: 0.2217
```  ```
- 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9028 - false_negatives_2: 103.5625 - false_positives_2: 103.6875 - loss: 0.2659 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9311 - false_negatives_2: 69.0625 - false_positives_2: 84.4375 - loss: 0.2216
``` - + ```
- 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9029 - false_negatives_2: 108.7059 - false_positives_2: 110.5294 - loss: 0.2656 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9308 - false_negatives_2: 73.6471 - false_positives_2: 89.9412 - loss: 0.2218
``` - + ```
- 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9028 - false_negatives_2: 115.5556 - false_positives_2: 116.7222 - loss: 0.2655 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9304 - false_negatives_2: 78.2778 - false_positives_2: 95.5000 - loss: 0.2220
``` - + ```
- 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9027 - false_negatives_2: 121.9474 - false_positives_2: 123.4211 - loss: 0.2655 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9301 - false_negatives_2: 82.9474 - false_positives_2: 101.0000 - loss: 0.2222
``` - + ```
- 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9026 - false_negatives_2: 128.2500 - false_positives_2: 130.3000 - loss: 0.2656 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9298 - false_negatives_2: 87.3500 - false_positives_2: 106.6500 - loss: 0.2223
``` - + ```
- 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9025 - false_negatives_2: 134.7619 - false_positives_2: 136.9524 - loss: 0.2657 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9295 - false_negatives_2: 92.3810 - false_positives_2: 112.1429 - loss: 0.2226
``` - + ```
- 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9024 - false_negatives_2: 141.0000 - false_positives_2: 143.9545 - loss: 0.2658 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9292 - false_negatives_2: 97.2727 - false_positives_2: 117.8636 - loss: 0.2231
``` - + ```
- 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9024 - false_negatives_2: 147.3913 - false_positives_2: 150.5652 - loss: 0.2658 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9289 - false_negatives_2: 102.4348 - false_positives_2: 123.3043 - loss: 0.2235
```  ```
- 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9023 - false_negatives_2: 153.3333 - false_positives_2: 157.6250 - loss: 0.2659 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9285 - false_negatives_2: 107.3750 - false_positives_2: 129.3750 - loss: 0.2240
```  ```
- 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9022 - false_negatives_2: 159.9200 - false_positives_2: 164.4400 - loss: 0.2661 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9281 - false_negatives_2: 112.9200 - false_positives_2: 135.0400 - loss: 0.2245
```  ```
- 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9021 - false_negatives_2: 166.3462 - false_positives_2: 171.1923 - loss: 0.2663 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9277 - false_negatives_2: 118.1923 - false_positives_2: 141.4615 - loss: 0.2251
```  ```
- 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9020 - false_negatives_2: 172.6667 - false_positives_2: 178.0000 - loss: 0.2664 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9273 - false_negatives_2: 123.9259 - false_positives_2: 147.7037 - loss: 0.2257
```  ```
- 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9019 - false_negatives_2: 178.8214 - false_positives_2: 184.7143 - loss: 0.2665 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9269 - false_negatives_2: 129.5357 - false_positives_2: 153.9643 - loss: 0.2263
```  ```
- 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9019 - false_negatives_2: 184.9310 - false_positives_2: 191.2759 - loss: 0.2666 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9265 - false_negatives_2: 134.9655 - false_positives_2: 160.3448 - loss: 0.2268
```  ```
- 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9019 - false_negatives_2: 190.9333 - false_positives_2: 197.8667 - loss: 0.2666 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9261 - false_negatives_2: 140.2667 - false_positives_2: 166.6333 - loss: 0.2273
```  ```
- 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9019 - false_negatives_2: 197.1290 - false_positives_2: 204.4516 - loss: 0.2667 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9258 - false_negatives_2: 145.4194 - false_positives_2: 172.7742 - loss: 0.2277
```  ```
- 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9019 - false_negatives_2: 203.0625 - false_positives_2: 211.4375 - loss: 0.2668 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9256 - false_negatives_2: 150.6875 - false_positives_2: 178.7188 - loss: 0.2280
```  ```
- 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9018 - false_negatives_2: 209.8485 - false_positives_2: 218.0909 - loss: 0.2670 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9253 - false_negatives_2: 155.7273 - false_positives_2: 184.6970 - loss: 0.2284
```  ```
- 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9016 - false_negatives_2: 216.5000 - false_positives_2: 225.2059 - loss: 0.2673 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9251 - false_negatives_2: 160.9706 - false_positives_2: 190.5294 - loss: 0.2287
```  ```
- 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9015 - false_negatives_2: 223.2571 - false_positives_2: 232.0571 - loss: 0.2676 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9249 - false_negatives_2: 165.9714 - false_positives_2: 196.6857 - loss: 0.2290
```  ```
- 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9014 - false_negatives_2: 230.0000 - false_positives_2: 238.9444 - loss: 0.2678 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9246 - false_negatives_2: 171.4444 - false_positives_2: 202.7222 - loss: 0.2294
```  ```
- 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9013 - false_negatives_2: 236.5946 - false_positives_2: 245.7297 - loss: 0.2681 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9244 - false_negatives_2: 176.6216 - false_positives_2: 208.8919 - loss: 0.2298
```  ```
- 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9012 - false_negatives_2: 243.0263 - false_positives_2: 252.5789 - loss: 0.2683 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9242 - false_negatives_2: 181.6842 - false_positives_2: 215.0789 - loss: 0.2301
```  ```
- 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9011 - false_negatives_2: 249.6923 - false_positives_2: 259.3590 - loss: 0.2685 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9240 - false_negatives_2: 186.8205 - false_positives_2: 221.3590 - loss: 0.2304
```  ```
- 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9011 - false_negatives_2: 256.2750 - false_positives_2: 266.1000 - loss: 0.2687 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9238 - false_negatives_2: 191.9250 - false_positives_2: 227.6000 - loss: 0.2307
```  ```
- 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9010 - false_negatives_2: 262.7805 - false_positives_2: 272.7317 - loss: 0.2688 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9236 - false_negatives_2: 197.0976 - false_positives_2: 233.7073 - loss: 0.2311
```  ```
- 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9010 - false_negatives_2: 269.0476 - false_positives_2: 279.5000 - loss: 0.2689 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9234 - false_negatives_2: 202.1905 - false_positives_2: 239.9048 - loss: 0.2314
```  ```
- 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9009 - false_negatives_2: 275.6744 - false_positives_2: 286.0930 - loss: 0.2691 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9232 - false_negatives_2: 207.3954 - false_positives_2: 246.0465 - loss: 0.2317
```  ```
- 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9008 - false_negatives_2: 282.0682 - false_positives_2: 293.4773 - loss: 0.2694 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9230 - false_negatives_2: 212.7045 - false_positives_2: 252.1364 - loss: 0.2319
```  ```
- 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9007 - false_negatives_2: 288.9778 - false_positives_2: 300.7333 - loss: 0.2697 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9228 - false_negatives_2: 217.8445 - false_positives_2: 258.6889 - loss: 0.2322
```  ```
- 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9006 - false_negatives_2: 295.7826 - false_positives_2: 307.9565 - loss: 0.2700 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9226 - false_negatives_2: 223.4565 - false_positives_2: 265.1304 - loss: 0.2326
```  ```
- 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9004 - false_negatives_2: 302.5107 - false_positives_2: 315.1702 - loss: 0.2703 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9224 - false_negatives_2: 229.0000 - false_positives_2: 271.5957 - loss: 0.2329
```  ```
- 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9004 - false_negatives_2: 309.1458 - false_positives_2: 322.2500 - loss: 0.2705 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9222 - false_negatives_2: 234.3750 - false_positives_2: 278.0000 - loss: 0.2332
```  ```
- 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9003 - false_negatives_2: 315.7551 - false_positives_2: 329.2857 - loss: 0.2707 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9220 - false_negatives_2: 239.7755 - false_positives_2: 284.2857 - loss: 0.2335
```  ```
- 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9002 - false_negatives_2: 322.4200 - false_positives_2: 336.2800 - loss: 0.2710 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9219 - false_negatives_2: 245.1200 - false_positives_2: 290.6000 - loss: 0.2338
```  ```
- 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9001 - false_negatives_2: 329.0000 - false_positives_2: 343.3529 - loss: 0.2712 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9217 - false_negatives_2: 250.5098 - false_positives_2: 296.7647 - loss: 0.2340
```  ```
- 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9000 - false_negatives_2: 335.5192 - false_positives_2: 350.4038 - loss: 0.2714 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9215 - false_negatives_2: 255.8846 - false_positives_2: 302.9808 - loss: 0.2343
```  ```
- 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9000 - false_negatives_2: 342.0189 - false_positives_2: 357.4151 - loss: 0.2715 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9214 - false_negatives_2: 261.2830 - false_positives_2: 309.2264 - loss: 0.2346
```  ```
- 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8999 - false_negatives_2: 348.5000 - false_positives_2: 364.3704 - loss: 0.2717 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9212 - false_negatives_2: 266.6296 - false_positives_2: 315.5185 - loss: 0.2348
```  ```
- 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8999 - false_negatives_2: 354.8909 - false_positives_2: 371.4364 - loss: 0.2719 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9211 - false_negatives_2: 271.9818 - false_positives_2: 321.6727 - loss: 0.2351
```  ```
- 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8998 - false_negatives_2: 361.5714 - false_positives_2: 378.3571 - loss: 0.2720 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9210 - false_negatives_2: 277.2321 - false_positives_2: 327.8393 - loss: 0.2353
```  ```
- 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8997 - false_negatives_2: 368.1404 - false_positives_2: 385.5789 - loss: 0.2722 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9208 - false_negatives_2: 282.5088 - false_positives_2: 334.0000 - loss: 0.2355
```  ```
- 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8996 - false_negatives_2: 374.7758 - false_positives_2: 392.7242 - loss: 0.2724 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9207 - false_negatives_2: 287.8448 - false_positives_2: 340.0172 - loss: 0.2357
```  ```
- 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8996 - false_negatives_2: 381.3390 - false_positives_2: 399.7966 - loss: 0.2725 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9206 - false_negatives_2: 293.0339 - false_positives_2: 346.2034 - loss: 0.2359
```  ```
- 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8995 - false_negatives_2: 387.8167 - false_positives_2: 406.9500 - loss: 0.2727 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9205 - false_negatives_2: 298.5833 - false_positives_2: 352.2500 - loss: 0.2362
```  ```
- 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8995 - false_negatives_2: 394.3607 - false_positives_2: 414.0984 - loss: 0.2728 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9204 - false_negatives_2: 304.0164 - false_positives_2: 358.5901 - loss: 0.2364
```  ```
- 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8994 - false_negatives_2: 400.9516 - false_positives_2: 421.1774 - loss: 0.2729 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9202 - false_negatives_2: 309.4355 - false_positives_2: 364.8065 - loss: 0.2366
```  ```
- 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8993 - false_negatives_2: 407.5079 - false_positives_2: 428.2698 - loss: 0.2730 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9201 - false_negatives_2: 314.7619 - false_positives_2: 371.0000 - loss: 0.2368
```  ```
- 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8993 - false_negatives_2: 413.9688 - false_positives_2: 435.2812 - loss: 0.2731 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9200 - false_negatives_2: 320.1406 - false_positives_2: 377.2031 - loss: 0.2371
```  ```
- 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8992 - false_negatives_2: 420.3692 - false_positives_2: 442.4154 - loss: 0.2732 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9199 - false_negatives_2: 325.5077 - false_positives_2: 383.3692 - loss: 0.2372
```  ```
- 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8992 - false_negatives_2: 426.9091 - false_positives_2: 449.4849 - loss: 0.2733 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9198 - false_negatives_2: 330.8182 - false_positives_2: 389.5606 - loss: 0.2374
```  ```
- 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8991 - false_negatives_2: 433.3284 - false_positives_2: 456.7314 - loss: 0.2734 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9197 - false_negatives_2: 336.0597 - false_positives_2: 395.6866 - loss: 0.2376
```  ```
- 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8991 - false_negatives_2: 440.0588 - false_positives_2: 463.8382 - loss: 0.2735 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9196 - false_negatives_2: 341.3824 - false_positives_2: 401.8088 - loss: 0.2378
```  ```
- 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8990 - false_negatives_2: 446.6522 - false_positives_2: 470.9420 - loss: 0.2737 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9195 - false_negatives_2: 346.6232 - false_positives_2: 407.9276 - loss: 0.2379
```  ```
- 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8990 - false_negatives_2: 453.1714 - false_positives_2: 478.1571 - loss: 0.2738 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9194 - false_negatives_2: 351.8429 - false_positives_2: 414.0143 - loss: 0.2381
```  ```
- 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8989 - false_negatives_2: 459.7465 - false_positives_2: 485.3098 - loss: 0.2739 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9194 - false_negatives_2: 357.0986 - false_positives_2: 420.0704 - loss: 0.2382
```  ```
- 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8989 - false_negatives_2: 466.3889 - false_positives_2: 492.4028 - loss: 0.2740 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9193 - false_negatives_2: 362.2500 - false_positives_2: 426.1528 - loss: 0.2383
```  ```
- 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8988 - false_negatives_2: 473.0685 - false_positives_2: 499.5479 - loss: 0.2741 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9192 - false_negatives_2: 367.5891 - false_positives_2: 432.1644 - loss: 0.2384
```  ```
- 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8988 - false_negatives_2: 479.6487 - false_positives_2: 506.6757 - loss: 0.2743 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9191 - false_negatives_2: 372.8513 - false_positives_2: 438.2973 - loss: 0.2386
```  ```
- 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8987 - false_negatives_2: 486.3600 - false_positives_2: 513.7333 - loss: 0.2744 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9190 - false_negatives_2: 378.2800 - false_positives_2: 444.2800 - loss: 0.2387
```  ```
- 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8986 - false_negatives_2: 492.9737 - false_positives_2: 520.9605 - loss: 0.2745 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9190 - false_negatives_2: 383.6053 - false_positives_2: 450.3553 - loss: 0.2388
```  ```
- 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8986 - false_negatives_2: 499.7532 - false_positives_2: 528.1039 - loss: 0.2746 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9189 - false_negatives_2: 389.1169 - false_positives_2: 456.3636 - loss: 0.2389
```  ```
- 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8985 - false_negatives_2: 506.4359 - false_positives_2: 535.2949 - loss: 0.2748 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9188 - false_negatives_2: 394.5513 - false_positives_2: 462.4359 - loss: 0.2391
``` -Epoch 3: val_loss did not improve from 0.35152 +Epoch 4: val_loss did not improve from 0.37074  ```
- 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 81ms/step - binary_accuracy: 0.8984 - false_negatives_2: 519.3250 - false_positives_2: 549.2125 - loss: 0.2750 - val_binary_accuracy: 0.8488 - val_false_negatives_2: 276.0000 - val_false_positives_2: 480.0000 - val_loss: 0.3571 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.9187 - false_negatives_2: 405.0625 - false_positives_2: 474.1250 - loss: 0.2393 - val_binary_accuracy: 0.8268 - val_false_negatives_2: 225.0000 - val_false_positives_2: 641.0000 - val_loss: 0.4197
``` -Epoch 4/20 +Epoch 5/20 ```
- 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 91ms/step - binary_accuracy: 0.9141 - false_negatives_2: 5.0000 - false_positives_2: 17.0000 - loss: 0.2496 + 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 93ms/step - binary_accuracy: 0.9180 - false_negatives_2: 1.0000 - false_positives_2: 20.0000 - loss: 0.2546
```  ```
- 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9150 - false_negatives_2: 10.0000 - false_positives_2: 22.5000 - loss: 0.2432 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 71ms/step - binary_accuracy: 0.9219 - false_negatives_2: 8.5000 - false_positives_2: 21.0000 - loss: 0.2421
``` - + ```
- 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9147 - false_negatives_2: 15.6667 - false_positives_2: 28.0000 - loss: 0.2408 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9232 - false_negatives_2: 12.0000 - false_positives_2: 26.6667 - loss: 0.2376
```  ```
- 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9163 - false_negatives_2: 19.5000 - false_positives_2: 33.5000 - loss: 0.2369 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9219 - false_negatives_2: 16.5000 - false_positives_2: 33.5000 - loss: 0.2396
```  ```
- 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9172 - false_negatives_2: 24.4000 - false_positives_2: 38.2000 - loss: 0.2337 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9225 - false_negatives_2: 20.4000 - false_positives_2: 38.8000 - loss: 0.2379
```  ```
- 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9180 - false_negatives_2: 29.0000 - false_positives_2: 43.1667 - loss: 0.2316 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9234 - false_negatives_2: 24.0000 - false_positives_2: 43.8333 - loss: 0.2361
```  ```
- 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9182 - false_negatives_2: 35.2857 - false_positives_2: 47.2857 - loss: 0.2314 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9236 - false_negatives_2: 28.4286 - false_positives_2: 48.8571 - loss: 0.2350
```  ```
- 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9179 - false_negatives_2: 40.3750 - false_positives_2: 53.3750 - loss: 0.2318 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 71ms/step - binary_accuracy: 0.9245 - false_negatives_2: 32.0000 - false_positives_2: 53.5000 - loss: 0.2336
```  ```
- 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9175 - false_negatives_2: 46.8889 - false_positives_2: 58.4444 - loss: 0.2328 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9248 - false_negatives_2: 36.0000 - false_positives_2: 58.4444 - loss: 0.2326
```  ```
- 10/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9166 - false_negatives_2: 52.4000 - false_positives_2: 65.8000 - loss: 0.2345 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9254 - false_negatives_2: 39.5000 - false_positives_2: 63.3000 - loss: 0.2312
```  ```
- 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9153 - false_negatives_2: 59.8182 - false_positives_2: 72.6364 - loss: 0.2370 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9259 - false_negatives_2: 43.4545 - false_positives_2: 67.7273 - loss: 0.2300
```  ```
- 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9142 - false_negatives_2: 66.6667 - false_positives_2: 79.9167 - loss: 0.2390 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9264 - false_negatives_2: 47.2500 - false_positives_2: 72.0833 - loss: 0.2286
```  ```
- 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9132 - false_negatives_2: 74.0000 - false_positives_2: 86.3846 - loss: 0.2407 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 51.2308 - false_positives_2: 76.5385 - loss: 0.2274
```  ```
- 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9125 - false_negatives_2: 80.7143 - false_positives_2: 93.0714 - loss: 0.2420 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9271 - false_negatives_2: 55.0714 - false_positives_2: 81.0714 - loss: 0.2265
```  ```
- 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9119 - false_negatives_2: 87.2667 - false_positives_2: 99.6667 - loss: 0.2433 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9275 - false_negatives_2: 58.6667 - false_positives_2: 85.4667 - loss: 0.2256
```  ```
- 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9113 - false_negatives_2: 94.1875 - false_positives_2: 105.8750 - loss: 0.2445 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9279 - false_negatives_2: 62.3750 - false_positives_2: 89.8125 - loss: 0.2248
``` - + ```
- 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9108 - false_negatives_2: 100.8824 - false_positives_2: 112.2941 - loss: 0.2456 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 66.2353 - false_positives_2: 93.9412 - loss: 0.2240
``` - + ```
- 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9104 - false_negatives_2: 107.3889 - false_positives_2: 118.6667 - loss: 0.2465 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9285 - false_negatives_2: 69.8333 - false_positives_2: 98.7778 - loss: 0.2235
``` - + ```
- 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9101 - false_negatives_2: 113.6316 - false_positives_2: 125.1053 - loss: 0.2472 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9285 - false_negatives_2: 74.7368 - false_positives_2: 103.2632 - loss: 0.2234
``` - + ```
- 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9098 - false_negatives_2: 119.5500 - false_positives_2: 131.5000 - loss: 0.2477 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9284 - false_negatives_2: 79.3000 - false_positives_2: 108.6500 - loss: 0.2235
``` - + ```
- 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_2: 125.4762 - false_positives_2: 137.8095 - loss: 0.2482 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9283 - false_negatives_2: 84.0000 - false_positives_2: 113.9524 - loss: 0.2236
``` - + ```
- 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9094 - false_negatives_2: 131.4091 - false_positives_2: 144.3636 - loss: 0.2486 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 88.4545 - false_positives_2: 119.0909 - loss: 0.2236
``` - + ```
- 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9092 - false_negatives_2: 137.2609 - false_positives_2: 150.6522 - loss: 0.2489 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 93.0000 - false_positives_2: 124.0000 - loss: 0.2236
``` - + ```
- 24/79 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9091 - false_negatives_2: 143.0417 - false_positives_2: 156.8333 - loss: 0.2490 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 97.3333 - false_positives_2: 128.9167 - loss: 0.2235
``` - + ```
- 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9090 - false_negatives_2: 148.7200 - false_positives_2: 163.1200 - loss: 0.2493 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 101.6400 - false_positives_2: 133.8000 - loss: 0.2235
```  ```
- 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9089 - false_negatives_2: 154.5769 - false_positives_2: 169.1923 - loss: 0.2495 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 106.1538 - false_positives_2: 138.6154 - loss: 0.2234
```  ```
- 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9088 - false_negatives_2: 160.2222 - false_positives_2: 175.5926 - loss: 0.2497 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 110.6667 - false_positives_2: 143.5556 - loss: 0.2235
```  ```
- 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9087 - false_negatives_2: 166.3214 - false_positives_2: 181.6429 - loss: 0.2500 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9282 - false_negatives_2: 115.2143 - false_positives_2: 148.5357 - loss: 0.2236
```  ```
- 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9086 - false_negatives_2: 172.0690 - false_positives_2: 188.0345 - loss: 0.2503 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9281 - false_negatives_2: 119.6552 - false_positives_2: 153.7241 - loss: 0.2237
```  ```
- 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9085 - false_negatives_2: 178.3000 - false_positives_2: 194.0333 - loss: 0.2505 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9281 - false_negatives_2: 124.2667 - false_positives_2: 158.7333 - loss: 0.2238
```  ```
- 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9084 - false_negatives_2: 184.4516 - false_positives_2: 200.2903 - loss: 0.2508 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9280 - false_negatives_2: 128.6452 - false_positives_2: 164.2258 - loss: 0.2240
```  ```
- 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9083 - false_negatives_2: 190.5000 - false_positives_2: 206.4688 - loss: 0.2511 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9279 - false_negatives_2: 133.9375 - false_positives_2: 169.4688 - loss: 0.2242
```  ```
- 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9082 - false_negatives_2: 196.3939 - false_positives_2: 212.6667 - loss: 0.2514 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9277 - false_negatives_2: 138.9394 - false_positives_2: 175.0000 - loss: 0.2245
```  ```
- 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9081 - false_negatives_2: 202.4412 - false_positives_2: 218.7941 - loss: 0.2516 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9276 - false_negatives_2: 143.9706 - false_positives_2: 180.2941 - loss: 0.2247
```  ```
- 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9080 - false_negatives_2: 208.4000 - false_positives_2: 224.9429 - loss: 0.2519 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9275 - false_negatives_2: 148.9429 - false_positives_2: 185.6000 - loss: 0.2249
```  ```
- 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9080 - false_negatives_2: 214.4167 - false_positives_2: 231.0000 - loss: 0.2521 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9274 - false_negatives_2: 153.9444 - false_positives_2: 190.9167 - loss: 0.2251
```  ```
- 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9079 - false_negatives_2: 220.3513 - false_positives_2: 236.9730 - loss: 0.2523 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9273 - false_negatives_2: 158.8378 - false_positives_2: 196.2703 - loss: 0.2253
```  ```
- 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9079 - false_negatives_2: 226.1579 - false_positives_2: 243.0526 - loss: 0.2524 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9271 - false_negatives_2: 163.8684 - false_positives_2: 201.6316 - loss: 0.2255
```  ```
- 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9078 - false_negatives_2: 232.4872 - false_positives_2: 248.9231 - loss: 0.2526 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9270 - false_negatives_2: 168.8974 - false_positives_2: 206.9231 - loss: 0.2257
```  ```
- 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9077 - false_negatives_2: 238.5750 - false_positives_2: 255.4250 - loss: 0.2529 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9269 - false_negatives_2: 173.8500 - false_positives_2: 212.2750 - loss: 0.2259
```  ```
- 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9076 - false_negatives_2: 245.1707 - false_positives_2: 261.7561 - loss: 0.2532 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9269 - false_negatives_2: 178.8293 - false_positives_2: 217.4390 - loss: 0.2260
```  ```
- 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9075 - false_negatives_2: 251.6667 - false_positives_2: 268.1429 - loss: 0.2536 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 183.6429 - false_positives_2: 222.7857 - loss: 0.2261
```  ```
- 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9074 - false_negatives_2: 258.1860 - false_positives_2: 274.4419 - loss: 0.2538 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9267 - false_negatives_2: 188.4651 - false_positives_2: 228.0698 - loss: 0.2262
```  ```
- 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9073 - false_negatives_2: 264.5227 - false_positives_2: 280.8182 - loss: 0.2541 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9266 - false_negatives_2: 193.2500 - false_positives_2: 233.3182 - loss: 0.2263
```  ```
- 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9072 - false_negatives_2: 270.8445 - false_positives_2: 287.1333 - loss: 0.2544 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9266 - false_negatives_2: 198.0667 - false_positives_2: 238.5333 - loss: 0.2263
```  ```
- 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9071 - false_negatives_2: 277.0652 - false_positives_2: 293.4565 - loss: 0.2546 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9265 - false_negatives_2: 202.7609 - false_positives_2: 243.8478 - loss: 0.2264
```  ```
- 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9070 - false_negatives_2: 283.7021 - false_positives_2: 299.6596 - loss: 0.2548 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9265 - false_negatives_2: 207.5106 - false_positives_2: 248.9787 - loss: 0.2265
```  ```
- 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9069 - false_negatives_2: 290.0833 - false_positives_2: 306.4167 - loss: 0.2551 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9264 - false_negatives_2: 212.1667 - false_positives_2: 254.2500 - loss: 0.2265
```  ```
- 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9068 - false_negatives_2: 296.5510 - false_positives_2: 313.0204 - loss: 0.2554 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9264 - false_negatives_2: 216.8571 - false_positives_2: 259.3878 - loss: 0.2266
```  ```
- 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9067 - false_negatives_2: 302.9800 - false_positives_2: 319.5600 - loss: 0.2557 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9263 - false_negatives_2: 221.5200 - false_positives_2: 264.6600 - loss: 0.2266
```  ```
- 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9066 - false_negatives_2: 309.5098 - false_positives_2: 326.0000 - loss: 0.2560 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9263 - false_negatives_2: 226.1569 - false_positives_2: 269.8824 - loss: 0.2266
```  ```
- 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9065 - false_negatives_2: 315.9423 - false_positives_2: 332.4808 - loss: 0.2562 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9263 - false_negatives_2: 230.7692 - false_positives_2: 275.0385 - loss: 0.2266
```  ```
- 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9064 - false_negatives_2: 322.3207 - false_positives_2: 338.9057 - loss: 0.2564 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9262 - false_negatives_2: 235.2830 - false_positives_2: 280.3396 - loss: 0.2267
```  ```
- 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9063 - false_negatives_2: 328.6482 - false_positives_2: 345.3333 - loss: 0.2566 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9262 - false_negatives_2: 239.8519 - false_positives_2: 285.4630 - loss: 0.2267
```  ```
- 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9063 - false_negatives_2: 335.1091 - false_positives_2: 351.6909 - loss: 0.2568 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9262 - false_negatives_2: 244.3636 - false_positives_2: 290.8000 - loss: 0.2267
```  ```
- 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9062 - false_negatives_2: 341.3929 - false_positives_2: 358.2321 - loss: 0.2569 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9261 - false_negatives_2: 249.0536 - false_positives_2: 296.0357 - loss: 0.2268
```  ```
- 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9061 - false_negatives_2: 347.9825 - false_positives_2: 364.6667 - loss: 0.2571 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9261 - false_negatives_2: 253.6491 - false_positives_2: 301.2982 - loss: 0.2268
```  ```
- 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9060 - false_negatives_2: 354.4138 - false_positives_2: 371.3103 - loss: 0.2573 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9261 - false_negatives_2: 258.2069 - false_positives_2: 306.6035 - loss: 0.2268
```  ```
- 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9059 - false_negatives_2: 361.0339 - false_positives_2: 377.8305 - loss: 0.2575 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9260 - false_negatives_2: 262.7627 - false_positives_2: 311.8813 - loss: 0.2268
```  ```
- 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9058 - false_negatives_2: 367.5667 - false_positives_2: 384.3833 - loss: 0.2577 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9260 - false_negatives_2: 267.3500 - false_positives_2: 317.0667 - loss: 0.2268
```  ```
- 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9057 - false_negatives_2: 374.0820 - false_positives_2: 390.9344 - loss: 0.2579 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9260 - false_negatives_2: 271.9016 - false_positives_2: 322.4262 - loss: 0.2268
```  ```
- 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9057 - false_negatives_2: 380.4839 - false_positives_2: 397.4677 - loss: 0.2580 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9259 - false_negatives_2: 276.5000 - false_positives_2: 327.6613 - loss: 0.2268
```  ```
- 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9056 - false_negatives_2: 386.8889 - false_positives_2: 404.0000 - loss: 0.2582 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9259 - false_negatives_2: 280.9841 - false_positives_2: 333.0317 - loss: 0.2268
```  ```
- 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9055 - false_negatives_2: 393.2812 - false_positives_2: 410.5000 - loss: 0.2583 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9259 - false_negatives_2: 285.6719 - false_positives_2: 338.3281 - loss: 0.2268
```  ```
- 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9055 - false_negatives_2: 399.6000 - false_positives_2: 416.9385 - loss: 0.2584 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9258 - false_negatives_2: 290.2462 - false_positives_2: 343.7692 - loss: 0.2268
```  ```
- 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9054 - false_negatives_2: 405.9091 - false_positives_2: 423.4697 - loss: 0.2586 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9258 - false_negatives_2: 294.8485 - false_positives_2: 349.1060 - loss: 0.2268
```  ```
- 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9054 - false_negatives_2: 412.3134 - false_positives_2: 429.9105 - loss: 0.2587 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9258 - false_negatives_2: 299.4328 - false_positives_2: 354.5075 - loss: 0.2268
```  ```
- 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9053 - false_negatives_2: 418.6176 - false_positives_2: 436.6471 - loss: 0.2588 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9257 - false_negatives_2: 304.1471 - false_positives_2: 359.7941 - loss: 0.2269
```  ```
- 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9052 - false_negatives_2: 425.0724 - false_positives_2: 443.2754 - loss: 0.2590 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9257 - false_negatives_2: 308.7826 - false_positives_2: 365.2319 - loss: 0.2269
```  ```
- 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9052 - false_negatives_2: 431.3857 - false_positives_2: 449.8857 - loss: 0.2591 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9256 - false_negatives_2: 313.4000 - false_positives_2: 370.6571 - loss: 0.2269
```  ```
- 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9051 - false_negatives_2: 437.6338 - false_positives_2: 456.5070 - loss: 0.2592 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9256 - false_negatives_2: 318.0000 - false_positives_2: 376.0282 - loss: 0.2270
```  ```
- 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9051 - false_negatives_2: 443.9028 - false_positives_2: 463.0417 - loss: 0.2593 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9256 - false_negatives_2: 322.5972 - false_positives_2: 381.3750 - loss: 0.2270
```  ```
- 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9050 - false_negatives_2: 450.0822 - false_positives_2: 469.6028 - loss: 0.2594 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9256 - false_negatives_2: 327.1781 - false_positives_2: 386.6712 - loss: 0.2270
```  ```
- 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9050 - false_negatives_2: 456.3378 - false_positives_2: 476.2027 - loss: 0.2595 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 331.7162 - false_positives_2: 391.9460 - loss: 0.2270
```  ```
- 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9049 - false_negatives_2: 462.6000 - false_positives_2: 482.8000 - loss: 0.2596 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 336.2267 - false_positives_2: 397.1733 - loss: 0.2270
```  ```
- 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9049 - false_negatives_2: 468.7895 - false_positives_2: 489.4079 - loss: 0.2596 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 340.6711 - false_positives_2: 402.4605 - loss: 0.2270
```  ```
- 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9048 - false_negatives_2: 475.0260 - false_positives_2: 495.9610 - loss: 0.2597 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 345.3247 - false_positives_2: 407.6623 - loss: 0.2270
```  ```
- 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9048 - false_negatives_2: 481.1795 - false_positives_2: 502.5898 - loss: 0.2598 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 349.8718 - false_positives_2: 413.0898 - loss: 0.2270
``` -Epoch 4: val_loss did not improve from 0.35152 +Epoch 5: val_loss did not improve from 0.37074  ```
- 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 81ms/step - binary_accuracy: 0.9047 - false_negatives_2: 493.0250 - false_positives_2: 515.3500 - loss: 0.2600 - val_binary_accuracy: 0.8386 - val_false_negatives_2: 184.0000 - val_false_positives_2: 623.0000 - val_loss: 0.4070 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.9254 - false_negatives_2: 358.6500 - false_positives_2: 423.5625 - loss: 0.2270 - val_binary_accuracy: 0.8228 - val_false_negatives_2: 611.0000 - val_false_positives_2: 275.0000 - val_loss: 0.4233
``` -Epoch 5/20 +Epoch 6/20 ```
- 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 91ms/step - binary_accuracy: 0.9180 - false_negatives_2: 4.0000 - false_positives_2: 17.0000 - loss: 0.2250 + 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 92ms/step - binary_accuracy: 0.8984 - false_negatives_2: 24.0000 - false_positives_2: 2.0000 - loss: 0.2527
```  ```
- 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9238 - false_negatives_2: 7.5000 - false_positives_2: 21.0000 - loss: 0.2198 + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 70ms/step - binary_accuracy: 0.8994 - false_negatives_2: 25.5000 - false_positives_2: 13.0000 - loss: 0.2556
``` - + ```
- 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9258 - false_negatives_2: 11.3333 - false_positives_2: 25.6667 - loss: 0.2236 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9030 - false_negatives_2: 29.6667 - false_positives_2: 19.0000 - loss: 0.2501
```  ```
- 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9263 - false_negatives_2: 15.5000 - false_positives_2: 30.7500 - loss: 0.2269 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9067 - false_negatives_2: 33.0000 - false_positives_2: 24.5000 - loss: 0.2451
```  ```
- 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9266 - false_negatives_2: 20.4000 - false_positives_2: 35.0000 - loss: 0.2298 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9109 - false_negatives_2: 36.2000 - false_positives_2: 28.4000 - loss: 0.2402
```  ```
- 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9270 - false_negatives_2: 25.3333 - false_positives_2: 39.0000 - loss: 0.2297 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9138 - false_negatives_2: 38.8333 - false_positives_2: 33.3333 - loss: 0.2368
```  ```
- 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9273 - false_negatives_2: 29.8571 - false_positives_2: 43.4286 - loss: 0.2292 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9153 - false_negatives_2: 44.0000 - false_positives_2: 37.1429 - loss: 0.2345
```  ```
- 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9277 - false_negatives_2: 34.0000 - false_positives_2: 48.0000 - loss: 0.2280 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9166 - false_negatives_2: 48.2500 - false_positives_2: 41.7500 - loss: 0.2326
```  ```
- 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9276 - false_negatives_2: 38.6667 - false_positives_2: 52.8889 - loss: 0.2277 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9174 - false_negatives_2: 53.2222 - false_positives_2: 46.4444 - loss: 0.2311
```  ```
- 10/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9275 - false_negatives_2: 43.2000 - false_positives_2: 58.1000 - loss: 0.2274 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9182 - false_negatives_2: 57.4000 - false_positives_2: 51.2000 - loss: 0.2295
```  ```
- 11/79 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9270 - false_negatives_2: 48.7273 - false_positives_2: 63.3636 - loss: 0.2274 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9191 - false_negatives_2: 61.5455 - false_positives_2: 55.7273 - loss: 0.2279
```  ```
- 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9265 - false_negatives_2: 53.5833 - false_positives_2: 69.3333 - loss: 0.2273 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9199 - false_negatives_2: 65.2500 - false_positives_2: 60.5000 - loss: 0.2263
```  ```
- 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9261 - false_negatives_2: 58.6923 - false_positives_2: 74.7692 - loss: 0.2274 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9207 - false_negatives_2: 68.9231 - false_positives_2: 64.8462 - loss: 0.2247
```  ```
- 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9258 - false_negatives_2: 63.9286 - false_positives_2: 80.0000 - loss: 0.2274 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9217 - false_negatives_2: 72.1429 - false_positives_2: 69.0714 - loss: 0.2230
```  ```
- 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9256 - false_negatives_2: 68.6667 - false_positives_2: 85.5333 - loss: 0.2271 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9225 - false_negatives_2: 75.5333 - false_positives_2: 73.0667 - loss: 0.2214
```  ```
- 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9254 - false_negatives_2: 73.5625 - false_positives_2: 90.6875 - loss: 0.2268 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9231 - false_negatives_2: 78.6250 - false_positives_2: 77.9375 - loss: 0.2203
```  ```
- 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9253 - false_negatives_2: 78.1765 - false_positives_2: 96.0588 - loss: 0.2265 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9235 - false_negatives_2: 83.0000 - false_positives_2: 82.4706 - loss: 0.2196
```  ```
- 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9252 - false_negatives_2: 83.4444 - false_positives_2: 101.0000 - loss: 0.2264 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9238 - false_negatives_2: 87.0556 - false_positives_2: 87.2778 - loss: 0.2191
``` - + ```
- 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9248 - false_negatives_2: 88.5263 - false_positives_2: 106.9474 - loss: 0.2266 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9241 - false_negatives_2: 91.2105 - false_positives_2: 92.0526 - loss: 0.2186
``` - + ```
- 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9245 - false_negatives_2: 94.0000 - false_positives_2: 112.6000 - loss: 0.2268 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9243 - false_negatives_2: 95.3000 - false_positives_2: 97.1000 - loss: 0.2181
``` - + ```
- 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9242 - false_negatives_2: 99.3810 - false_positives_2: 118.1429 - loss: 0.2270 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9246 - false_negatives_2: 99.4762 - false_positives_2: 101.9524 - loss: 0.2178
```  ```
- 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9240 - false_negatives_2: 104.6818 - false_positives_2: 123.6364 - loss: 0.2271 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9248 - false_negatives_2: 103.4091 - false_positives_2: 106.7273 - loss: 0.2174
```  ```
- 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9237 - false_negatives_2: 110.0000 - false_positives_2: 129.3913 - loss: 0.2273 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9251 - false_negatives_2: 107.3478 - false_positives_2: 111.4348 - loss: 0.2170
```  ```
- 24/79 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9235 - false_negatives_2: 115.5000 - false_positives_2: 134.8750 - loss: 0.2275 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9253 - false_negatives_2: 111.4583 - false_positives_2: 116.1667 - loss: 0.2167
```  ```
- 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9233 - false_negatives_2: 120.8400 - false_positives_2: 140.4800 - loss: 0.2277 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9254 - false_negatives_2: 115.6000 - false_positives_2: 121.0400 - loss: 0.2165
```  ```
- 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9231 - false_negatives_2: 126.3077 - false_positives_2: 145.9231 - loss: 0.2279 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9255 - false_negatives_2: 120.0000 - false_positives_2: 125.8077 - loss: 0.2163
```  ```
- 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9229 - false_negatives_2: 131.6296 - false_positives_2: 151.5556 - loss: 0.2280 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9257 - false_negatives_2: 124.1852 - false_positives_2: 130.7407 - loss: 0.2161
```  ```
- 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9227 - false_negatives_2: 137.0714 - false_positives_2: 157.0000 - loss: 0.2281 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9258 - false_negatives_2: 128.4286 - false_positives_2: 135.6786 - loss: 0.2159
```  ```
- 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9225 - false_negatives_2: 142.3448 - false_positives_2: 162.9310 - loss: 0.2282 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9259 - false_negatives_2: 132.6552 - false_positives_2: 140.4138 - loss: 0.2157
```  ```
- 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9223 - false_negatives_2: 148.0667 - false_positives_2: 168.7667 - loss: 0.2284 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9260 - false_negatives_2: 136.7667 - false_positives_2: 145.1667 - loss: 0.2154
```  ```
- 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9220 - false_negatives_2: 153.6452 - false_positives_2: 174.9032 - loss: 0.2287 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9261 - false_negatives_2: 140.8387 - false_positives_2: 150.0323 - loss: 0.2153
```  ```
- 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9217 - false_negatives_2: 159.5938 - false_positives_2: 180.8750 - loss: 0.2291 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9262 - false_negatives_2: 144.9688 - false_positives_2: 154.8438 - loss: 0.2151
```  ```
- 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9215 - false_negatives_2: 165.3636 - false_positives_2: 187.0909 - loss: 0.2294 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9264 - false_negatives_2: 149.0303 - false_positives_2: 159.4848 - loss: 0.2149
```  ```
- 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9212 - false_negatives_2: 171.1765 - false_positives_2: 193.1471 - loss: 0.2297 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9265 - false_negatives_2: 153.0882 - false_positives_2: 164.1765 - loss: 0.2147
```  ```
- 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9210 - false_negatives_2: 176.9714 - false_positives_2: 199.2286 - loss: 0.2300 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 157.2857 - false_positives_2: 168.6857 - loss: 0.2145
```  ```
- 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9208 - false_negatives_2: 182.7500 - false_positives_2: 205.2778 - loss: 0.2302 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9267 - false_negatives_2: 161.3056 - false_positives_2: 173.4444 - loss: 0.2144
```  ```
- 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9205 - false_negatives_2: 188.7297 - false_positives_2: 211.2162 - loss: 0.2305 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 165.9460 - false_positives_2: 177.9730 - loss: 0.2143
```  ```
- 38/79 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9203 - false_negatives_2: 194.6316 - false_positives_2: 217.3947 - loss: 0.2307 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 170.3947 - false_positives_2: 183.1842 - loss: 0.2142
```  ```
- 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9201 - false_negatives_2: 200.4615 - false_positives_2: 223.6410 - loss: 0.2309 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 174.9231 - false_positives_2: 188.2821 - loss: 0.2142
```  ```
- 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9199 - false_negatives_2: 206.5750 - false_positives_2: 229.7000 - loss: 0.2312 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 179.3750 - false_positives_2: 193.3750 - loss: 0.2141
```  ```
- 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9196 - false_negatives_2: 212.4390 - false_positives_2: 236.1951 - loss: 0.2315 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 183.7073 - false_positives_2: 198.5122 - loss: 0.2141
```  ```
- 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9194 - false_negatives_2: 218.5714 - false_positives_2: 242.5476 - loss: 0.2318 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 187.9524 - false_positives_2: 203.6667 - loss: 0.2140
```  ```
- 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9192 - false_negatives_2: 224.6512 - false_positives_2: 248.9070 - loss: 0.2321 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 192.3488 - false_positives_2: 208.6744 - loss: 0.2140
```  ```
- 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9190 - false_negatives_2: 230.5909 - false_positives_2: 255.1818 - loss: 0.2323 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 196.6364 - false_positives_2: 213.7045 - loss: 0.2139
```  ```
- 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9188 - false_negatives_2: 236.3778 - false_positives_2: 261.4000 - loss: 0.2326 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 200.8222 - false_positives_2: 218.6889 - loss: 0.2139
```  ```
- 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9186 - false_negatives_2: 242.1522 - false_positives_2: 267.6087 - loss: 0.2328 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9270 - false_negatives_2: 204.9565 - false_positives_2: 223.6956 - loss: 0.2138
```  ```
- 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9185 - false_negatives_2: 247.8298 - false_positives_2: 273.5957 - loss: 0.2329 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9270 - false_negatives_2: 209.3404 - false_positives_2: 228.7021 - loss: 0.2138
```  ```
- 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9183 - false_negatives_2: 253.5000 - false_positives_2: 279.8333 - loss: 0.2331 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9270 - false_negatives_2: 213.6042 - false_positives_2: 233.8750 - loss: 0.2137
```  ```
- 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9182 - false_negatives_2: 259.2857 - false_positives_2: 285.9796 - loss: 0.2333 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9270 - false_negatives_2: 218.1225 - false_positives_2: 238.8980 - loss: 0.2137
```  ```
- 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9180 - false_negatives_2: 265.0400 - false_positives_2: 292.2400 - loss: 0.2335 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9270 - false_negatives_2: 222.5400 - false_positives_2: 244.1600 - loss: 0.2137
```  ```
- 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9178 - false_negatives_2: 270.9804 - false_positives_2: 298.3726 - loss: 0.2337 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 227.1569 - false_positives_2: 249.3922 - loss: 0.2138
```  ```
- 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9177 - false_negatives_2: 276.7308 - false_positives_2: 304.9038 - loss: 0.2339 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 231.6346 - false_positives_2: 254.7115 - loss: 0.2138
```  ```
- 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9175 - false_negatives_2: 282.8868 - false_positives_2: 311.2642 - loss: 0.2342 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 236.1698 - false_positives_2: 259.9434 - loss: 0.2138
```  ```
- 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9173 - false_negatives_2: 288.9445 - false_positives_2: 318.0000 - loss: 0.2345 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9269 - false_negatives_2: 240.7222 - false_positives_2: 265.1296 - loss: 0.2138
```  ```
- 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9171 - false_negatives_2: 295.0545 - false_positives_2: 324.6727 - loss: 0.2347 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9269 - false_negatives_2: 245.2909 - false_positives_2: 270.3818 - loss: 0.2138
```  ```
- 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9170 - false_negatives_2: 301.0357 - false_positives_2: 331.2500 - loss: 0.2350 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9269 - false_negatives_2: 249.8571 - false_positives_2: 275.6071 - loss: 0.2138
```  ```
- 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9168 - false_negatives_2: 307.0000 - false_positives_2: 337.8246 - loss: 0.2352 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 254.4561 - false_positives_2: 280.7368 - loss: 0.2138
```  ```
- 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9166 - false_negatives_2: 312.9655 - false_positives_2: 344.4138 - loss: 0.2354 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 258.9828 - false_positives_2: 285.8965 - loss: 0.2139
```  ```
- 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9165 - false_negatives_2: 318.9492 - false_positives_2: 350.9661 - loss: 0.2356 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 263.5254 - false_positives_2: 291.0678 - loss: 0.2139
```  ```
- 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9163 - false_negatives_2: 324.8333 - false_positives_2: 357.5167 - loss: 0.2358 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 268.0333 - false_positives_2: 296.1333 - loss: 0.2139
```  ```
- 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_2: 330.7541 - false_positives_2: 363.9180 - loss: 0.2361 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 272.4262 - false_positives_2: 301.2951 - loss: 0.2139
```  ```
- 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_2: 336.5645 - false_positives_2: 370.3548 - loss: 0.2362 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 276.9355 - false_positives_2: 306.3065 - loss: 0.2139
```  ```
- 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9160 - false_negatives_2: 342.3968 - false_positives_2: 376.6984 - loss: 0.2364 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 281.3651 - false_positives_2: 311.5555 - loss: 0.2139
```  ```
- 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9158 - false_negatives_2: 348.1406 - false_positives_2: 383.0938 - loss: 0.2366 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9268 - false_negatives_2: 286.0000 - false_positives_2: 316.6719 - loss: 0.2140
```  ```
- 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9157 - false_negatives_2: 354.0308 - false_positives_2: 389.3385 - loss: 0.2368 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9268 - false_negatives_2: 290.5385 - false_positives_2: 321.9077 - loss: 0.2140
```  ```
- 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9156 - false_negatives_2: 359.8030 - false_positives_2: 395.7879 - loss: 0.2370 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9267 - false_negatives_2: 295.1818 - false_positives_2: 327.2121 - loss: 0.2141
```  ```
- 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9155 - false_negatives_2: 365.6716 - false_positives_2: 402.1194 - loss: 0.2372 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9267 - false_negatives_2: 299.7761 - false_positives_2: 332.5075 - loss: 0.2141
```  ```
- 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9154 - false_negatives_2: 371.4559 - false_positives_2: 408.5000 - loss: 0.2373 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9267 - false_negatives_2: 304.3824 - false_positives_2: 337.7941 - loss: 0.2142
```  ```
- 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9153 - false_negatives_2: 377.1014 - false_positives_2: 414.8261 - loss: 0.2375 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9267 - false_negatives_2: 308.9276 - false_positives_2: 343.1014 - loss: 0.2142
```  ```
- 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9152 - false_negatives_2: 382.7571 - false_positives_2: 421.0428 - loss: 0.2377 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 313.4857 - false_positives_2: 348.3714 - loss: 0.2143
```  ```
- 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9151 - false_negatives_2: 388.3521 - false_positives_2: 427.3380 - loss: 0.2378 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 318.0282 - false_positives_2: 353.5916 - loss: 0.2143
```  ```
- 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9151 - false_negatives_2: 393.9445 - false_positives_2: 433.6111 - loss: 0.2379 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 322.5695 - false_positives_2: 358.7917 - loss: 0.2144
```  ```
- 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9150 - false_negatives_2: 399.5068 - false_positives_2: 439.8904 - loss: 0.2381 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 327.0274 - false_positives_2: 364.0000 - loss: 0.2144
```  ```
- 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9149 - false_negatives_2: 405.0270 - false_positives_2: 446.1487 - loss: 0.2382 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 331.5946 - false_positives_2: 369.1487 - loss: 0.2145
```  ```
- 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9148 - false_negatives_2: 410.6267 - false_positives_2: 452.3333 - loss: 0.2383 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9266 - false_negatives_2: 336.0933 - false_positives_2: 374.3467 - loss: 0.2145
```  ```
- 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9148 - false_negatives_2: 416.2500 - false_positives_2: 458.5263 - loss: 0.2385 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9265 - false_negatives_2: 340.6711 - false_positives_2: 379.5000 - loss: 0.2146
```  ```
- 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9147 - false_negatives_2: 421.8571 - false_positives_2: 464.7662 - loss: 0.2386 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9265 - false_negatives_2: 345.2208 - false_positives_2: 384.7662 - loss: 0.2146
```  ```
- 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9146 - false_negatives_2: 427.4102 - false_positives_2: 471.0128 - loss: 0.2387 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9265 - false_negatives_2: 349.8590 - false_positives_2: 389.9359 - loss: 0.2147
``` -Epoch 5: val_loss did not improve from 0.35152 +Epoch 6: val_loss did not improve from 0.37074  ```
- 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 81ms/step - binary_accuracy: 0.9145 - false_negatives_2: 438.1250 - false_positives_2: 483.0875 - loss: 0.2389 - val_binary_accuracy: 0.8496 - val_false_negatives_2: 418.0000 - val_false_positives_2: 334.0000 - val_loss: 0.3857 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.9265 - false_negatives_2: 358.8375 - false_positives_2: 399.9875 - loss: 0.2148 - val_binary_accuracy: 0.8272 - val_false_negatives_2: 581.0000 - val_false_positives_2: 283.0000 - val_loss: 0.4415
``` -Epoch 5: early stopping +Epoch 7/20 ```
- 1/20 ━━━━━━━━━━━━━━━━━━━━ 4s 263ms/step - -
-``` - -``` -
- 3/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step - -
-``` - -``` -
- 5/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
-``` - -``` -
- 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
-``` - -``` -
- 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
-``` - -``` -
- 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
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- 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
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- 15/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
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- 17/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
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- 19/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step - -
-``` - -``` -
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 39ms/step + 1/79 ━━━━━━━━━━━━━━━━━━━━ 7s 91ms/step - binary_accuracy: 0.9531 - false_negatives_2: 10.0000 - false_positives_2: 2.0000 - loss: 0.1453
``` - + ```
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 39ms/step - + 2/79 ━━━━━━━━━━━━━━━━━━━━ 5s 71ms/step - binary_accuracy: 0.9453 - false_negatives_2: 12.5000 - false_positives_2: 9.5000 - loss: 0.1618
``` ----------------------------------------------------------------------------------------------------- -Number of zeros incorrectly classified: 445.0, Number of ones incorrectly classified: 341.0 -Sample ratio for positives: 0.43384223918575066, Sample ratio for negatives:0.5661577608142494 -Starting training with 24998 samples ----------------------------------------------------------------------------------------------------- -Epoch 1/20 - + ```
- - 1/98 ━━━━━━━━━━━━━━━━━━━━ 4:32 3s/step - binary_accuracy: 0.9141 - false_negatives_3: 10.0000 - false_positives_3: 12.0000 - loss: 0.2568 + 3/79 ━━━━━━━━━━━━━━━━━━━━ 5s 71ms/step - binary_accuracy: 0.9457 - false_negatives_2: 15.3333 - false_positives_2: 13.0000 - loss: 0.1638
```  ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9082 - false_negatives_3: 21.0000 - false_positives_3: 15.0000 - loss: 0.2619 + 4/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9459 - false_negatives_2: 18.2500 - false_positives_2: 16.7500 - loss: 0.1644
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.8885 - false_negatives_3: 25.0000 - false_positives_3: 37.6667 - loss: 0.3055 + 5/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9451 - false_negatives_2: 22.6000 - false_positives_2: 20.2000 - loss: 0.1677
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.8709 - false_negatives_3: 44.0000 - false_positives_3: 49.5000 - loss: 0.3463 + 6/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9446 - false_negatives_2: 26.1667 - false_positives_2: 24.3333 - loss: 0.1702
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.8627 - false_negatives_3: 56.4000 - false_positives_3: 62.0000 - loss: 0.3658 + 7/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9443 - false_negatives_2: 29.8571 - false_positives_2: 28.1429 - loss: 0.1721
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8594 - false_negatives_3: 67.0000 - false_positives_3: 71.8333 - loss: 0.3738 + 8/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9441 - false_negatives_2: 32.8750 - false_positives_2: 32.6250 - loss: 0.1738
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8577 - false_negatives_3: 76.2857 - false_positives_3: 81.7143 - loss: 0.3777 + 9/79 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.9438 - false_negatives_2: 36.5556 - false_positives_2: 36.6667 - loss: 0.1751
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8569 - false_negatives_3: 85.1250 - false_positives_3: 91.2500 - loss: 0.3796 + 10/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 39.7000 - false_positives_2: 41.5000 - loss: 0.1765
```  ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8570 - false_negatives_3: 93.0000 - false_positives_3: 100.2222 - loss: 0.3798 - -
-``` - -``` -
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8575 - false_negatives_3: 100.5000 - false_positives_3: 108.6000 - loss: 0.3787 - -
-``` - -``` -
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8581 - false_negatives_3: 107.4545 - false_positives_3: 117.5455 - loss: 0.3773 - -
-``` - -``` -
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8586 - false_negatives_3: 114.7500 - false_positives_3: 126.2500 - loss: 0.3758 - -
-``` - -``` -
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8592 - false_negatives_3: 121.8462 - false_positives_3: 135.0000 - loss: 0.3742 - -
-``` - -``` -
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8599 - false_negatives_3: 128.6429 - false_positives_3: 143.2143 - loss: 0.3722 - -
-``` - -``` -
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8608 - false_negatives_3: 135.2667 - false_positives_3: 150.8667 - loss: 0.3701 - -
-``` - -``` -
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8617 - false_negatives_3: 141.8125 - false_positives_3: 158.5000 - loss: 0.3681 - -
-``` - -``` -
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8625 - false_negatives_3: 148.4118 - false_positives_3: 166.0588 - loss: 0.3663 - -
-``` - -``` -
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8632 - false_negatives_3: 155.2778 - false_positives_3: 173.8889 - loss: 0.3647 - -
-``` - -``` -
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8637 - false_negatives_3: 162.2105 - false_positives_3: 181.8947 - loss: 0.3631 + 11/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9433 - false_negatives_2: 42.8182 - false_positives_2: 45.7273 - loss: 0.1773
``` - + ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.8643 - false_negatives_3: 169.1000 - false_positives_3: 189.8500 - loss: 0.3617 + 12/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9433 - false_negatives_2: 45.8333 - false_positives_2: 49.9167 - loss: 0.1781
``` - + ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.8648 - false_negatives_3: 175.6190 - false_positives_3: 197.9524 - loss: 0.3602 + 13/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 48.6154 - false_positives_2: 54.0000 - loss: 0.1784
``` - + ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.8653 - false_negatives_3: 182.8182 - false_positives_3: 205.6818 - loss: 0.3588 + 14/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 51.9286 - false_positives_2: 58.0000 - loss: 0.1789
``` - + ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.8658 - false_negatives_3: 189.7826 - false_positives_3: 213.6956 - loss: 0.3575 + 15/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 54.9333 - false_positives_2: 62.1333 - loss: 0.1792
``` - + ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.8661 - false_negatives_3: 197.0833 - false_positives_3: 221.6250 - loss: 0.3563 + 16/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 58.1250 - false_positives_2: 66.0625 - loss: 0.1794
``` - + ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8665 - false_negatives_3: 204.3200 - false_positives_3: 229.6400 - loss: 0.3553 + 17/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9435 - false_negatives_2: 61.2353 - false_positives_2: 69.7647 - loss: 0.1793
``` - + ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8668 - false_negatives_3: 211.8462 - false_positives_3: 237.5385 - loss: 0.3543 + 18/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9436 - false_negatives_2: 64.2222 - false_positives_2: 73.5556 - loss: 0.1791
``` - + ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8671 - false_negatives_3: 219.1852 - false_positives_3: 245.8889 - loss: 0.3534 + 19/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9436 - false_negatives_2: 67.3684 - false_positives_2: 77.2105 - loss: 0.1790
``` - + ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8673 - false_negatives_3: 226.7500 - false_positives_3: 254.0357 - loss: 0.3526 + 20/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9437 - false_negatives_2: 70.5000 - false_positives_2: 81.1000 - loss: 0.1790
``` - + ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8675 - false_negatives_3: 234.2414 - false_positives_3: 262.1035 - loss: 0.3518 + 21/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9437 - false_negatives_2: 73.7619 - false_positives_2: 84.8095 - loss: 0.1789
``` - + ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8678 - false_negatives_3: 241.5667 - false_positives_3: 270.2333 - loss: 0.3510 + 22/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9437 - false_negatives_2: 77.0455 - false_positives_2: 88.5909 - loss: 0.1789
``` - + ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8680 - false_negatives_3: 249.4194 - false_positives_3: 278.1290 - loss: 0.3503 + 23/79 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.9438 - false_negatives_2: 80.5217 - false_positives_2: 92.2174 - loss: 0.1789
``` - + ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8682 - false_negatives_3: 257.1250 - false_positives_3: 286.4688 - loss: 0.3497 + 24/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9438 - false_negatives_2: 83.7917 - false_positives_2: 96.1250 - loss: 0.1790
``` - + ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8683 - false_negatives_3: 264.7576 - false_positives_3: 294.8182 - loss: 0.3492 + 25/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9437 - false_negatives_2: 87.6800 - false_positives_2: 99.8800 - loss: 0.1791
``` - + ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8685 - false_negatives_3: 272.2647 - false_positives_3: 303.0882 - loss: 0.3486 + 26/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9436 - false_negatives_2: 91.3077 - false_positives_2: 104.0000 - loss: 0.1793
``` - + ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8686 - false_negatives_3: 279.9429 - false_positives_3: 311.1143 - loss: 0.3481 + 27/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9435 - false_negatives_2: 95.1111 - false_positives_2: 108.0370 - loss: 0.1795
``` - + ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8688 - false_negatives_3: 287.3889 - false_positives_3: 319.5833 - loss: 0.3476 + 28/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9434 - false_negatives_2: 98.8571 - false_positives_2: 112.2500 - loss: 0.1797
``` - + ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8689 - false_negatives_3: 294.9460 - false_positives_3: 327.9189 - loss: 0.3471 + 29/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9433 - false_negatives_2: 102.6897 - false_positives_2: 116.3793 - loss: 0.1799
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8691 - false_negatives_3: 302.2632 - false_positives_3: 336.3947 - loss: 0.3466 + 30/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9432 - false_negatives_2: 106.4667 - false_positives_2: 120.6000 - loss: 0.1801
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8692 - false_negatives_3: 309.7436 - false_positives_3: 344.6667 - loss: 0.3462 + 31/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9431 - false_negatives_2: 110.1936 - false_positives_2: 124.9032 - loss: 0.1803
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8693 - false_negatives_3: 317.2000 - false_positives_3: 352.8750 - loss: 0.3457 + 32/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9430 - false_negatives_2: 114.0000 - false_positives_2: 129.0312 - loss: 0.1805
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8695 - false_negatives_3: 324.6585 - false_positives_3: 361.2683 - loss: 0.3453 + 33/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9430 - false_negatives_2: 117.6061 - false_positives_2: 133.1212 - loss: 0.1807
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8696 - false_negatives_3: 332.5476 - false_positives_3: 369.4762 - loss: 0.3450 + 34/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9429 - false_negatives_2: 121.4706 - false_positives_2: 137.0588 - loss: 0.1809
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8696 - false_negatives_3: 340.1395 - false_positives_3: 378.2325 - loss: 0.3446 + 35/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9428 - false_negatives_2: 125.1714 - false_positives_2: 141.3143 - loss: 0.1811
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8697 - false_negatives_3: 347.8409 - false_positives_3: 386.8636 - loss: 0.3443 + 36/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9427 - false_negatives_2: 129.0000 - false_positives_2: 145.3611 - loss: 0.1813
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8697 - false_negatives_3: 355.7333 - false_positives_3: 395.4445 - loss: 0.3441 + 37/79 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.9427 - false_negatives_2: 132.6757 - false_positives_2: 149.4865 - loss: 0.1815
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8698 - false_negatives_3: 363.6304 - false_positives_3: 404.1304 - loss: 0.3438 + 38/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9427 - false_negatives_2: 136.2368 - false_positives_2: 153.5263 - loss: 0.1817
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8698 - false_negatives_3: 371.5745 - false_positives_3: 412.8298 - loss: 0.3436 + 39/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9426 - false_negatives_2: 139.7692 - false_positives_2: 157.4872 - loss: 0.1818
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8698 - false_negatives_3: 379.4792 - false_positives_3: 421.5625 - loss: 0.3433 + 40/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9426 - false_negatives_2: 143.3250 - false_positives_2: 161.4500 - loss: 0.1819
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8699 - false_negatives_3: 387.2653 - false_positives_3: 430.3469 - loss: 0.3431 + 41/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9426 - false_negatives_2: 146.8781 - false_positives_2: 165.4146 - loss: 0.1821
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8699 - false_negatives_3: 395.1000 - false_positives_3: 439.0000 - loss: 0.3429 + 42/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9426 - false_negatives_2: 150.3095 - false_positives_2: 169.3810 - loss: 0.1822
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8699 - false_negatives_3: 402.7843 - false_positives_3: 447.8824 - loss: 0.3427 + 43/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9425 - false_negatives_2: 153.8372 - false_positives_2: 173.4186 - loss: 0.1823
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8700 - false_negatives_3: 410.7308 - false_positives_3: 456.5577 - loss: 0.3425 + 44/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9425 - false_negatives_2: 157.3864 - false_positives_2: 177.4318 - loss: 0.1825
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8700 - false_negatives_3: 418.5660 - false_positives_3: 465.1698 - loss: 0.3423 + 45/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9425 - false_negatives_2: 160.8889 - false_positives_2: 181.5556 - loss: 0.1826
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8700 - false_negatives_3: 426.2778 - false_positives_3: 473.9074 - loss: 0.3421 + 46/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9424 - false_negatives_2: 164.5435 - false_positives_2: 185.6739 - loss: 0.1828
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8700 - false_negatives_3: 434.1454 - false_positives_3: 482.6000 - loss: 0.3419 + 47/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9424 - false_negatives_2: 168.1064 - false_positives_2: 189.9787 - loss: 0.1829
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 441.9286 - false_positives_3: 491.4286 - loss: 0.3417 + 48/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9423 - false_negatives_2: 171.8958 - false_positives_2: 194.2500 - loss: 0.1831
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 449.9474 - false_positives_3: 500.0877 - loss: 0.3415 + 49/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9423 - false_negatives_2: 175.5714 - false_positives_2: 198.5102 - loss: 0.1833
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 457.8448 - false_positives_3: 508.8965 - loss: 0.3414 + 50/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9422 - false_negatives_2: 179.3200 - false_positives_2: 202.8000 - loss: 0.1835
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 465.8644 - false_positives_3: 517.5255 - loss: 0.3412 + 51/79 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.9422 - false_negatives_2: 183.0000 - false_positives_2: 207.1373 - loss: 0.1836
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 473.6667 - false_positives_3: 526.2833 - loss: 0.3410 + 52/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9421 - false_negatives_2: 186.7308 - false_positives_2: 211.4808 - loss: 0.1838
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8701 - false_negatives_3: 481.5246 - false_positives_3: 534.9836 - loss: 0.3408 + 53/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9420 - false_negatives_2: 190.5094 - false_positives_2: 215.8302 - loss: 0.1840
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8702 - false_negatives_3: 489.3548 - false_positives_3: 543.6451 - loss: 0.3407 + 54/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9420 - false_negatives_2: 194.3148 - false_positives_2: 220.1667 - loss: 0.1842
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8702 - false_negatives_3: 497.2222 - false_positives_3: 552.2222 - loss: 0.3405 + 55/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9419 - false_negatives_2: 198.0909 - false_positives_2: 224.4545 - loss: 0.1843
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8702 - false_negatives_3: 505.0000 - false_positives_3: 560.8125 - loss: 0.3403 + 56/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9419 - false_negatives_2: 201.8929 - false_positives_2: 228.6786 - loss: 0.1845
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8702 - false_negatives_3: 512.9231 - false_positives_3: 569.3538 - loss: 0.3401 + 57/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9418 - false_negatives_2: 205.6667 - false_positives_2: 232.9298 - loss: 0.1847
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8703 - false_negatives_3: 520.6667 - false_positives_3: 578.0303 - loss: 0.3400 + 58/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9418 - false_negatives_2: 209.5862 - false_positives_2: 237.1379 - loss: 0.1848
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8703 - false_negatives_3: 528.4926 - false_positives_3: 586.6567 - loss: 0.3398 + 59/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9417 - false_negatives_2: 213.4237 - false_positives_2: 241.4576 - loss: 0.1850
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8703 - false_negatives_3: 536.2647 - false_positives_3: 595.3088 - loss: 0.3397 + 60/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9417 - false_negatives_2: 217.3500 - false_positives_2: 245.7000 - loss: 0.1851
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8703 - false_negatives_3: 543.9710 - false_positives_3: 603.9130 - loss: 0.3395 + 61/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9416 - false_negatives_2: 221.2131 - false_positives_2: 249.9344 - loss: 0.1853
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8704 - false_negatives_3: 551.6714 - false_positives_3: 612.3857 - loss: 0.3393 + 62/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9416 - false_negatives_2: 225.0968 - false_positives_2: 254.1452 - loss: 0.1854
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8704 - false_negatives_3: 559.2817 - false_positives_3: 620.8873 - loss: 0.3392 + 63/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9415 - false_negatives_2: 228.9365 - false_positives_2: 258.3492 - loss: 0.1856
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8705 - false_negatives_3: 566.8472 - false_positives_3: 629.3055 - loss: 0.3390 + 64/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9415 - false_negatives_2: 232.7812 - false_positives_2: 262.5625 - loss: 0.1857
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8705 - false_negatives_3: 574.3561 - false_positives_3: 637.6849 - loss: 0.3388 + 65/79 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.9415 - false_negatives_2: 236.6000 - false_positives_2: 266.7385 - loss: 0.1859
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8706 - false_negatives_3: 581.7973 - false_positives_3: 646.0270 - loss: 0.3386 + 66/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9414 - false_negatives_2: 240.3788 - false_positives_2: 270.9546 - loss: 0.1860
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8706 - false_negatives_3: 589.5467 - false_positives_3: 654.2800 - loss: 0.3384 + 67/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9414 - false_negatives_2: 244.2239 - false_positives_2: 275.2090 - loss: 0.1861
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8706 - false_negatives_3: 597.1316 - false_positives_3: 662.9211 - loss: 0.3383 + 68/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9413 - false_negatives_2: 248.0441 - false_positives_2: 279.4265 - loss: 0.1863
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8706 - false_negatives_3: 605.0000 - false_positives_3: 671.4156 - loss: 0.3381 + 69/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9413 - false_negatives_2: 251.8261 - false_positives_2: 283.6522 - loss: 0.1864
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8707 - false_negatives_3: 612.8718 - false_positives_3: 679.8589 - loss: 0.3380 + 70/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9413 - false_negatives_2: 255.6572 - false_positives_2: 287.8714 - loss: 0.1865
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8707 - false_negatives_3: 620.7089 - false_positives_3: 688.2911 - loss: 0.3379 + 71/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9412 - false_negatives_2: 259.4507 - false_positives_2: 292.0423 - loss: 0.1867
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8707 - false_negatives_3: 628.5250 - false_positives_3: 696.6875 - loss: 0.3377 + 72/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9412 - false_negatives_2: 263.1667 - false_positives_2: 296.3750 - loss: 0.1868
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8707 - false_negatives_3: 636.2716 - false_positives_3: 705.0988 - loss: 0.3376 + 73/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9412 - false_negatives_2: 267.0411 - false_positives_2: 300.6575 - loss: 0.1869
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8708 - false_negatives_3: 643.9756 - false_positives_3: 713.5366 - loss: 0.3375 + 74/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9411 - false_negatives_2: 270.8513 - false_positives_2: 305.0540 - loss: 0.1871
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8708 - false_negatives_3: 651.7470 - false_positives_3: 721.9036 - loss: 0.3374 + 75/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9411 - false_negatives_2: 274.8400 - false_positives_2: 309.4000 - loss: 0.1872
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8708 - false_negatives_3: 659.4167 - false_positives_3: 730.2738 - loss: 0.3372 + 76/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9410 - false_negatives_2: 278.7632 - false_positives_2: 313.9079 - loss: 0.1874
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8709 - false_negatives_3: 667.1059 - false_positives_3: 738.5529 - loss: 0.3371 + 77/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9410 - false_negatives_2: 282.8182 - false_positives_2: 318.3377 - loss: 0.1876
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8709 - false_negatives_3: 674.7209 - false_positives_3: 746.7442 - loss: 0.3370 + 78/79 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.9409 - false_negatives_2: 286.7820 - false_positives_2: 322.7949 - loss: 0.1877 +
``` +Epoch 7: val_loss did not improve from 0.37074 +  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8709 - false_negatives_3: 682.3333 - false_positives_3: 754.9196 - loss: 0.3368 + 79/79 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.9408 - false_negatives_2: 294.4375 - false_positives_2: 331.4000 - loss: 0.1880 - val_binary_accuracy: 0.8266 - val_false_negatives_2: 528.0000 - val_false_positives_2: 339.0000 - val_loss: 0.4419 +
``` - +Epoch 7: early stopping + ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8710 - false_negatives_3: 690.0000 - false_positives_3: 763.0568 - loss: 0.3367 + + 1/20 ━━━━━━━━━━━━━━━━━━━━ 5s 267ms/step
``` - + ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8710 - false_negatives_3: 697.6068 - false_positives_3: 771.2584 - loss: 0.3365 + 3/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
``` - + ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8711 - false_negatives_3: 705.3222 - false_positives_3: 779.3444 - loss: 0.3364 + 5/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8711 - false_negatives_3: 712.9231 - false_positives_3: 787.5604 - loss: 0.3363 + 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8711 - false_negatives_3: 720.7500 - false_positives_3: 795.6630 - loss: 0.3361 + 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8712 - false_negatives_3: 728.4623 - false_positives_3: 803.8817 - loss: 0.3360 + 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8712 - false_negatives_3: 736.2128 - false_positives_3: 812.0851 - loss: 0.3359 + 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8712 - false_negatives_3: 743.9895 - false_positives_3: 820.2211 - loss: 0.3358 + 15/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8713 - false_negatives_3: 751.7188 - false_positives_3: 828.4167 - loss: 0.3357 + 17/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8713 - false_negatives_3: 759.4846 - false_positives_3: 836.5980 - loss: 0.3355 + 19/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step
``` - + ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8713 - false_negatives_3: 767.1938 - false_positives_3: 844.7245 - loss: 0.3354 + 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 39ms/step -
``` -Epoch 1: val_loss did not improve from 0.35152 - - + ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 11s 83ms/step - binary_accuracy: 0.8713 - false_negatives_3: 774.7475 - false_positives_3: 852.6869 - loss: 0.3353 - val_binary_accuracy: 0.8380 - val_false_negatives_3: 544.0000 - val_false_positives_3: 266.0000 - val_loss: 0.3590 + 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 39ms/step
``` -Epoch 2/20 +---------------------------------------------------------------------------------------------------- +Number of zeros incorrectly classified: 376.0, Number of ones incorrectly classified: 442.0 +Sample ratio for positives: 0.5403422982885085, Sample ratio for negatives:0.45965770171149145 +Starting training with 24998 samples +---------------------------------------------------------------------------------------------------- +Epoch 1/20 ```
- 1/98 ━━━━━━━━━━━━━━━━━━━━ 9s 93ms/step - binary_accuracy: 0.9102 - false_negatives_3: 18.0000 - false_positives_3: 5.0000 - loss: 0.2548 + 1/98 ━━━━━━━━━━━━━━━━━━━━ 4:35 3s/step - binary_accuracy: 0.9141 - false_negatives_3: 12.0000 - false_positives_3: 10.0000 - loss: 0.2815
``` - + ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9014 - false_negatives_3: 23.0000 - false_positives_3: 16.0000 - loss: 0.2644 + 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8809 - false_negatives_3: 13.0000 - false_positives_3: 37.0000 - loss: 0.3311
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9000 - false_negatives_3: 28.3333 - false_positives_3: 24.0000 - loss: 0.2681 + 3/98 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8442 - false_negatives_3: 45.6667 - false_positives_3: 46.3333 - loss: 0.4062
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8984 - false_negatives_3: 36.7500 - false_positives_3: 29.7500 - loss: 0.2704 + 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8292 - false_negatives_3: 63.7500 - false_positives_3: 60.5000 - loss: 0.4340
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8967 - false_negatives_3: 43.0000 - false_positives_3: 38.4000 - loss: 0.2727 + 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8237 - false_negatives_3: 76.6000 - false_positives_3: 73.6000 - loss: 0.4436
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8946 - false_negatives_3: 52.6667 - false_positives_3: 44.8333 - loss: 0.2761 + 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8216 - false_negatives_3: 87.1667 - false_positives_3: 86.3333 - loss: 0.4461
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8934 - false_negatives_3: 60.4286 - false_positives_3: 52.1429 - loss: 0.2781 + 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8216 - false_negatives_3: 96.4286 - false_positives_3: 98.0000 - loss: 0.4454
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8930 - false_negatives_3: 67.5000 - false_positives_3: 59.2500 - loss: 0.2785 + 8/98 ━━━━━━━━━━━━━━━━━━━━ 7s 78ms/step - binary_accuracy: 0.8224 - false_negatives_3: 105.5000 - false_positives_3: 108.5000 - loss: 0.4435
``` - + ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8929 - false_negatives_3: 74.2222 - false_positives_3: 66.1111 - loss: 0.2789 + 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8234 - false_negatives_3: 113.5556 - false_positives_3: 119.8889 - loss: 0.4411
``` - + ```
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8933 - false_negatives_3: 80.4000 - false_positives_3: 72.3000 - loss: 0.2787 + 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8242 - false_negatives_3: 121.7000 - false_positives_3: 131.5000 - loss: 0.4386
``` - + ```
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8937 - false_negatives_3: 86.2727 - false_positives_3: 78.6364 - loss: 0.2786 + 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8252 - false_negatives_3: 130.2727 - false_positives_3: 142.0909 - loss: 0.4360
``` - + ```
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8938 - false_negatives_3: 92.6667 - false_positives_3: 85.2500 - loss: 0.2789 + 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.8262 - false_negatives_3: 138.0833 - false_positives_3: 153.5000 - loss: 0.4337
``` - + ```
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8939 - false_negatives_3: 98.6154 - false_positives_3: 92.6154 - loss: 0.2795 + 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8271 - false_negatives_3: 146.3077 - false_positives_3: 164.1538 - loss: 0.4314
``` - + ```
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8937 - false_negatives_3: 106.0000 - false_positives_3: 99.5000 - loss: 0.2802 + 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8281 - false_negatives_3: 154.0714 - false_positives_3: 175.0714 - loss: 0.4292
``` - + ```
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8931 - false_negatives_3: 112.6667 - false_positives_3: 108.6000 - loss: 0.2815 + 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8292 - false_negatives_3: 161.6000 - false_positives_3: 185.4000 - loss: 0.4268
```  ```
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8924 - false_negatives_3: 120.7500 - false_positives_3: 116.8125 - loss: 0.2828 + 16/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8302 - false_negatives_3: 168.7500 - false_positives_3: 196.0000 - loss: 0.4245
```  ```
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8918 - false_negatives_3: 128.8824 - false_positives_3: 125.0588 - loss: 0.2840 + 17/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8311 - false_negatives_3: 176.2941 - false_positives_3: 206.4118 - loss: 0.4226
```  ```
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8913 - false_negatives_3: 136.5556 - false_positives_3: 133.1667 - loss: 0.2849 + 18/98 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.8319 - false_negatives_3: 183.8889 - false_positives_3: 217.1111 - loss: 0.4208
```  ```
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8910 - false_negatives_3: 144.2105 - false_positives_3: 140.8421 - loss: 0.2857 + 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8327 - false_negatives_3: 191.6842 - false_positives_3: 227.5789 - loss: 0.4191
```  ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8906 - false_negatives_3: 151.8000 - false_positives_3: 148.5000 - loss: 0.2864 + 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8333 - false_negatives_3: 199.7000 - false_positives_3: 238.3000 - loss: 0.4177
```  ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8904 - false_negatives_3: 159.3810 - false_positives_3: 156.0476 - loss: 0.2870 + 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8339 - false_negatives_3: 207.7619 - false_positives_3: 248.9048 - loss: 0.4163
```  ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8901 - false_negatives_3: 166.7273 - false_positives_3: 163.8182 - loss: 0.2876 + 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8345 - false_negatives_3: 215.5909 - false_positives_3: 259.2727 - loss: 0.4150
```  ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8899 - false_negatives_3: 174.0000 - false_positives_3: 171.3913 - loss: 0.2879 + 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8351 - false_negatives_3: 223.3478 - false_positives_3: 269.7391 - loss: 0.4136
```  ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8898 - false_negatives_3: 181.1667 - false_positives_3: 178.7917 - loss: 0.2883 + 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8356 - false_negatives_3: 231.6250 - false_positives_3: 280.2083 - loss: 0.4125
```  ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8897 - false_negatives_3: 188.2400 - false_positives_3: 186.2400 - loss: 0.2885 + 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8360 - false_negatives_3: 239.9200 - false_positives_3: 290.7600 - loss: 0.4114
```  ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8897 - false_negatives_3: 195.0000 - false_positives_3: 193.6538 - loss: 0.2887 + 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8364 - false_negatives_3: 248.0385 - false_positives_3: 301.5000 - loss: 0.4103
```  ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8896 - false_negatives_3: 201.9630 - false_positives_3: 200.8148 - loss: 0.2889 + 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8368 - false_negatives_3: 256.3704 - false_positives_3: 311.9259 - loss: 0.4093
```  ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8895 - false_negatives_3: 208.5714 - false_positives_3: 208.8571 - loss: 0.2891 + 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8372 - false_negatives_3: 264.3929 - false_positives_3: 322.6071 - loss: 0.4082
```  ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8894 - false_negatives_3: 215.7586 - false_positives_3: 216.5517 - loss: 0.2894 + 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8376 - false_negatives_3: 272.4483 - false_positives_3: 333.2069 - loss: 0.4071
```  ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8892 - false_negatives_3: 222.8000 - false_positives_3: 224.8667 - loss: 0.2897 + 30/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8380 - false_negatives_3: 280.2667 - false_positives_3: 343.6667 - loss: 0.4061
```  ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8890 - false_negatives_3: 230.0323 - false_positives_3: 232.9677 - loss: 0.2901 + 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8384 - false_negatives_3: 288.2258 - false_positives_3: 353.9355 - loss: 0.4050
```  ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8889 - false_negatives_3: 236.9688 - false_positives_3: 241.0938 - loss: 0.2903 + 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8387 - false_negatives_3: 296.2500 - false_positives_3: 364.3125 - loss: 0.4040
```  ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8887 - false_negatives_3: 244.0000 - false_positives_3: 249.3030 - loss: 0.2906 + 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8391 - false_negatives_3: 304.2121 - false_positives_3: 374.4849 - loss: 0.4030
```  ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8886 - false_negatives_3: 251.1765 - false_positives_3: 257.3235 - loss: 0.2909 + 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8395 - false_negatives_3: 312.1176 - false_positives_3: 384.5000 - loss: 0.4021
```  ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8885 - false_negatives_3: 258.1714 - false_positives_3: 265.2571 - loss: 0.2911 + 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8399 - false_negatives_3: 319.9429 - false_positives_3: 394.5143 - loss: 0.4011
```  ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8884 - false_negatives_3: 265.3055 - false_positives_3: 273.0000 - loss: 0.2913 + 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8402 - false_negatives_3: 327.9167 - false_positives_3: 404.5833 - loss: 0.4002
```  ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8883 - false_negatives_3: 272.3243 - false_positives_3: 280.8649 - loss: 0.2915 + 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8406 - false_negatives_3: 335.9189 - false_positives_3: 414.3784 - loss: 0.3993
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8882 - false_negatives_3: 279.3421 - false_positives_3: 288.4737 - loss: 0.2916 + 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8409 - false_negatives_3: 343.7632 - false_positives_3: 424.4737 - loss: 0.3985
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8882 - false_negatives_3: 286.3077 - false_positives_3: 296.1795 - loss: 0.2917 + 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8412 - false_negatives_3: 351.5385 - false_positives_3: 434.3590 - loss: 0.3976
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8881 - false_negatives_3: 293.3000 - false_positives_3: 303.7250 - loss: 0.2918 + 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8416 - false_negatives_3: 359.2250 - false_positives_3: 444.1750 - loss: 0.3968
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8881 - false_negatives_3: 300.2927 - false_positives_3: 311.2927 - loss: 0.2919 + 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8419 - false_negatives_3: 367.1707 - false_positives_3: 453.9024 - loss: 0.3960
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8880 - false_negatives_3: 307.1905 - false_positives_3: 318.8333 - loss: 0.2920 + 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8422 - false_negatives_3: 375.0714 - false_positives_3: 463.5238 - loss: 0.3952
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8880 - false_negatives_3: 314.2791 - false_positives_3: 326.3256 - loss: 0.2920 + 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8425 - false_negatives_3: 382.8605 - false_positives_3: 473.2791 - loss: 0.3944
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8880 - false_negatives_3: 321.2273 - false_positives_3: 333.9773 - loss: 0.2921 + 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8428 - false_negatives_3: 390.7500 - false_positives_3: 482.8182 - loss: 0.3937
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8879 - false_negatives_3: 328.3333 - false_positives_3: 341.5555 - loss: 0.2922 + 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8431 - false_negatives_3: 398.3778 - false_positives_3: 492.6222 - loss: 0.3929
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8878 - false_negatives_3: 335.3044 - false_positives_3: 349.4565 - loss: 0.2923 + 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8434 - false_negatives_3: 406.0652 - false_positives_3: 502.1087 - loss: 0.3922
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8878 - false_negatives_3: 342.2553 - false_positives_3: 357.3192 - loss: 0.2925 + 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8437 - false_negatives_3: 413.7021 - false_positives_3: 511.8723 - loss: 0.3915
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8877 - false_negatives_3: 349.2708 - false_positives_3: 364.9792 - loss: 0.2926 + 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8439 - false_negatives_3: 421.6875 - false_positives_3: 521.3958 - loss: 0.3909
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8877 - false_negatives_3: 356.0612 - false_positives_3: 372.7755 - loss: 0.2927 + 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8442 - false_negatives_3: 429.4082 - false_positives_3: 531.3469 - loss: 0.3903
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8877 - false_negatives_3: 362.9800 - false_positives_3: 380.4200 - loss: 0.2928 + 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8444 - false_negatives_3: 437.3800 - false_positives_3: 541.1200 - loss: 0.3897
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8876 - false_negatives_3: 369.9019 - false_positives_3: 388.1765 - loss: 0.2929 + 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8446 - false_negatives_3: 445.1569 - false_positives_3: 551.0196 - loss: 0.3891
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8876 - false_negatives_3: 376.8269 - false_positives_3: 395.8846 - loss: 0.2929 + 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8449 - false_negatives_3: 452.8654 - false_positives_3: 561.0000 - loss: 0.3886
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8876 - false_negatives_3: 383.7358 - false_positives_3: 403.5472 - loss: 0.2930 + 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8451 - false_negatives_3: 460.6038 - false_positives_3: 570.8491 - loss: 0.3881
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8876 - false_negatives_3: 390.7592 - false_positives_3: 411.1296 - loss: 0.2931 + 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8453 - false_negatives_3: 468.2592 - false_positives_3: 580.7778 - loss: 0.3875
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8875 - false_negatives_3: 397.8000 - false_positives_3: 418.7455 - loss: 0.2932 + 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8455 - false_negatives_3: 475.8909 - false_positives_3: 590.7091 - loss: 0.3870
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8875 - false_negatives_3: 404.8750 - false_positives_3: 426.4286 - loss: 0.2933 + 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8457 - false_negatives_3: 483.6250 - false_positives_3: 600.4464 - loss: 0.3865
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8875 - false_negatives_3: 411.8421 - false_positives_3: 434.0877 - loss: 0.2934 + 57/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8459 - false_negatives_3: 491.1579 - false_positives_3: 610.2456 - loss: 0.3860
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 418.8793 - false_positives_3: 441.7242 - loss: 0.2934 + 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8462 - false_negatives_3: 498.6207 - false_positives_3: 619.9138 - loss: 0.3855
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 425.8813 - false_positives_3: 449.3220 - loss: 0.2935 + 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8464 - false_negatives_3: 506.0169 - false_positives_3: 629.5424 - loss: 0.3850
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 432.8000 - false_positives_3: 456.8000 - loss: 0.2935 + 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8466 - false_negatives_3: 513.3167 - false_positives_3: 639.5167 - loss: 0.3845
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 439.7705 - false_positives_3: 464.2459 - loss: 0.2936 + 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8468 - false_negatives_3: 521.0492 - false_positives_3: 649.2951 - loss: 0.3840
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 446.7742 - false_positives_3: 471.6935 - loss: 0.2936 + 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8469 - false_negatives_3: 528.5968 - false_positives_3: 659.3549 - loss: 0.3836
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 453.7143 - false_positives_3: 479.1587 - loss: 0.2937 + 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8471 - false_negatives_3: 536.2540 - false_positives_3: 669.3174 - loss: 0.3831
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8874 - false_negatives_3: 460.7344 - false_positives_3: 486.5000 - loss: 0.2937 + 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8473 - false_negatives_3: 543.9844 - false_positives_3: 679.2344 - loss: 0.3827
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8873 - false_negatives_3: 467.6308 - false_positives_3: 494.0461 - loss: 0.2938 + 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8474 - false_negatives_3: 551.6616 - false_positives_3: 689.2000 - loss: 0.3823
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8873 - false_negatives_3: 474.9394 - false_positives_3: 501.3940 - loss: 0.2938 + 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8476 - false_negatives_3: 559.3788 - false_positives_3: 699.1061 - loss: 0.3820
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8873 - false_negatives_3: 482.1045 - false_positives_3: 509.0895 - loss: 0.2939 + 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8477 - false_negatives_3: 567.0448 - false_positives_3: 709.1343 - loss: 0.3816
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8872 - false_negatives_3: 489.5441 - false_positives_3: 516.6030 - loss: 0.2940 + 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8479 - false_negatives_3: 574.8530 - false_positives_3: 719.0441 - loss: 0.3812
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8872 - false_negatives_3: 496.8986 - false_positives_3: 524.1739 - loss: 0.2941 + 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8480 - false_negatives_3: 582.6522 - false_positives_3: 729.0290 - loss: 0.3809
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8872 - false_negatives_3: 504.2429 - false_positives_3: 531.7286 - loss: 0.2941 + 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8481 - false_negatives_3: 590.4572 - false_positives_3: 739.0428 - loss: 0.3805
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8871 - false_negatives_3: 511.5211 - false_positives_3: 539.2958 - loss: 0.2942 + 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8483 - false_negatives_3: 598.2394 - false_positives_3: 749.1690 - loss: 0.3802
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8871 - false_negatives_3: 518.7639 - false_positives_3: 546.8055 - loss: 0.2942 + 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8484 - false_negatives_3: 605.9722 - false_positives_3: 759.1945 - loss: 0.3799
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8871 - false_negatives_3: 526.0411 - false_positives_3: 554.2466 - loss: 0.2943 + 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8485 - false_negatives_3: 613.6986 - false_positives_3: 769.2328 - loss: 0.3796
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8871 - false_negatives_3: 533.2027 - false_positives_3: 561.7297 - loss: 0.2943 + 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8486 - false_negatives_3: 621.5000 - false_positives_3: 779.2027 - loss: 0.3792
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8871 - false_negatives_3: 540.4667 - false_positives_3: 569.1334 - loss: 0.2944 + 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8488 - false_negatives_3: 629.1866 - false_positives_3: 789.2667 - loss: 0.3789
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 547.6184 - false_positives_3: 576.5921 - loss: 0.2944 + 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8489 - false_negatives_3: 636.9605 - false_positives_3: 799.2368 - loss: 0.3786
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 554.7662 - false_positives_3: 584.0130 - loss: 0.2944 + 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8490 - false_negatives_3: 644.8701 - false_positives_3: 809.1429 - loss: 0.3783
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 561.8205 - false_positives_3: 591.5641 - loss: 0.2945 + 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8491 - false_negatives_3: 652.6795 - false_positives_3: 819.2051 - loss: 0.3780
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 568.9620 - false_positives_3: 599.0000 - loss: 0.2945 + 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8492 - false_negatives_3: 660.5316 - false_positives_3: 829.1772 - loss: 0.3778
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 576.0500 - false_positives_3: 606.4750 - loss: 0.2945 + 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8493 - false_negatives_3: 668.3875 - false_positives_3: 839.2875 - loss: 0.3775
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 583.1235 - false_positives_3: 613.9877 - loss: 0.2946 + 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8494 - false_negatives_3: 676.3087 - false_positives_3: 849.3580 - loss: 0.3772
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 590.3536 - false_positives_3: 621.4025 - loss: 0.2946 + 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8495 - false_negatives_3: 684.1464 - false_positives_3: 859.4756 - loss: 0.3769
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8870 - false_negatives_3: 597.4578 - false_positives_3: 628.9398 - loss: 0.2946 + 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8496 - false_negatives_3: 691.9759 - false_positives_3: 869.4819 - loss: 0.3767
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 604.6548 - false_positives_3: 636.4286 - loss: 0.2946 + 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8497 - false_negatives_3: 699.8452 - false_positives_3: 879.4762 - loss: 0.3764
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 611.7765 - false_positives_3: 643.9529 - loss: 0.2947 + 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8498 - false_negatives_3: 707.6470 - false_positives_3: 889.3765 - loss: 0.3762
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 618.8488 - false_positives_3: 651.4418 - loss: 0.2947 + 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8499 - false_negatives_3: 715.4070 - false_positives_3: 899.2907 - loss: 0.3759
```  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 625.8391 - false_positives_3: 659.0115 - loss: 0.2947 + 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8500 - false_negatives_3: 723.2643 - false_positives_3: 909.1379 - loss: 0.3756
```  ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 632.8864 - false_positives_3: 666.5227 - loss: 0.2947 + 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8501 - false_negatives_3: 731.0455 - false_positives_3: 919.1591 - loss: 0.3754
```  ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 639.9326 - false_positives_3: 674.0225 - loss: 0.2948 + 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8502 - false_negatives_3: 738.9775 - false_positives_3: 929.0562 - loss: 0.3752
```  ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 646.9333 - false_positives_3: 681.5111 - loss: 0.2948 + 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8503 - false_negatives_3: 746.8555 - false_positives_3: 939.0111 - loss: 0.3749
```  ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 653.9231 - false_positives_3: 688.8681 - loss: 0.2948 + 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8503 - false_negatives_3: 754.7143 - false_positives_3: 948.9231 - loss: 0.3747
```  ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 660.8261 - false_positives_3: 696.3261 - loss: 0.2948 + 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8504 - false_negatives_3: 762.5217 - false_positives_3: 958.8152 - loss: 0.3745
```  ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 667.8925 - false_positives_3: 703.6774 - loss: 0.2948 + 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8505 - false_negatives_3: 770.3333 - false_positives_3: 968.7527 - loss: 0.3742
```  ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 674.8511 - false_positives_3: 711.1808 - loss: 0.2948 + 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8506 - false_negatives_3: 778.3085 - false_positives_3: 978.5851 - loss: 0.3740
```  ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 681.9158 - false_positives_3: 718.6000 - loss: 0.2949 + 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8507 - false_negatives_3: 786.1579 - false_positives_3: 988.7368 - loss: 0.3738
```  ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 688.9062 - false_positives_3: 726.0625 - loss: 0.2949 + 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8507 - false_negatives_3: 794.1979 - false_positives_3: 998.7188 - loss: 0.3736
```  ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 695.9382 - false_positives_3: 733.4742 - loss: 0.2949 + 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8508 - false_negatives_3: 802.1031 - false_positives_3: 1008.8557 - loss: 0.3734
``` - + ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8869 - false_negatives_3: 702.8878 - false_positives_3: 740.8265 - loss: 0.2949 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8509 - false_negatives_3: 809.9184 - false_positives_3: 1018.9286 - loss: 0.3732
``` -Epoch 2: val_loss improved from 0.35152 to 0.34519, saving model to AL_Model.keras +Epoch 1: val_loss improved from 0.37074 to 0.36196, saving model to AL_Model.keras - + ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 80ms/step - binary_accuracy: 0.8869 - false_negatives_3: 709.6970 - false_positives_3: 748.0303 - loss: 0.2949 - val_binary_accuracy: 0.8564 - val_false_negatives_3: 309.0000 - val_false_positives_3: 409.0000 - val_loss: 0.3452 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 11s 83ms/step - binary_accuracy: 0.8509 - false_negatives_3: 817.5757 - false_positives_3: 1028.7980 - loss: 0.3731 - val_binary_accuracy: 0.8424 - val_false_negatives_3: 368.0000 - val_false_positives_3: 420.0000 - val_loss: 0.3620
``` -Epoch 3/20 +Epoch 2/20 ```
- 1/98 ━━━━━━━━━━━━━━━━━━━━ 9s 95ms/step - binary_accuracy: 0.8711 - false_negatives_3: 8.0000 - false_positives_3: 25.0000 - loss: 0.3349 + 1/98 ━━━━━━━━━━━━━━━━━━━━ 8s 92ms/step - binary_accuracy: 0.8945 - false_negatives_3: 15.0000 - false_positives_3: 12.0000 - loss: 0.2567
``` - + ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8691 - false_negatives_3: 22.0000 - false_positives_3: 28.5000 - loss: 0.3311 + 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9053 - false_negatives_3: 17.0000 - false_positives_3: 18.0000 - loss: 0.2463
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8737 - false_negatives_3: 28.6667 - false_positives_3: 35.0000 - loss: 0.3199 + 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9047 - false_negatives_3: 21.6667 - false_positives_3: 26.3333 - loss: 0.2491
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8748 - false_negatives_3: 36.2500 - false_positives_3: 42.7500 - loss: 0.3166 + 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9022 - false_negatives_3: 26.0000 - false_positives_3: 37.0000 - loss: 0.2550
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8768 - false_negatives_3: 43.0000 - false_positives_3: 49.6000 - loss: 0.3131 + 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9003 - false_negatives_3: 32.0000 - false_positives_3: 45.8000 - loss: 0.2596
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8780 - false_negatives_3: 49.8333 - false_positives_3: 57.0000 - loss: 0.3102 + 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8976 - false_negatives_3: 37.6667 - false_positives_3: 56.8333 - loss: 0.2642
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8788 - false_negatives_3: 57.2857 - false_positives_3: 64.1429 - loss: 0.3083 + 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8955 - false_negatives_3: 44.7143 - false_positives_3: 66.2857 - loss: 0.2674
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8797 - false_negatives_3: 64.1250 - false_positives_3: 71.3750 - loss: 0.3062 + 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8937 - false_negatives_3: 51.3750 - false_positives_3: 76.2500 - loss: 0.2709
```  ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8806 - false_negatives_3: 71.1111 - false_positives_3: 78.0000 - loss: 0.3040 + 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8923 - false_negatives_3: 57.6667 - false_positives_3: 86.2222 - loss: 0.2741
```  ```
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8815 - false_negatives_3: 77.2000 - false_positives_3: 85.3000 - loss: 0.3020 + 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8911 - false_negatives_3: 64.7000 - false_positives_3: 95.3000 - loss: 0.2767
```  ```
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8821 - false_negatives_3: 84.7273 - false_positives_3: 91.7273 - loss: 0.3003 + 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8903 - false_negatives_3: 71.2727 - false_positives_3: 104.4545 - loss: 0.2787
``` - + ```
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8825 - false_negatives_3: 91.3333 - false_positives_3: 99.3333 - loss: 0.2992 + 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8896 - false_negatives_3: 78.3333 - false_positives_3: 112.8333 - loss: 0.2804
``` - + ```
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8830 - false_negatives_3: 98.3846 - false_positives_3: 105.9231 - loss: 0.2980 + 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8891 - false_negatives_3: 85.0769 - false_positives_3: 121.3077 - loss: 0.2818
```  ```
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8834 - false_negatives_3: 105.0000 - false_positives_3: 113.2857 - loss: 0.2971 + 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8885 - false_negatives_3: 92.7143 - false_positives_3: 129.6429 - loss: 0.2832
``` - + ```
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8837 - false_negatives_3: 112.2000 - false_positives_3: 120.3333 - loss: 0.2964 + 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8879 - false_negatives_3: 99.9333 - false_positives_3: 138.4667 - loss: 0.2846
``` - + ```
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8839 - false_negatives_3: 119.5625 - false_positives_3: 127.1875 - loss: 0.2957 + 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8873 - false_negatives_3: 107.7500 - false_positives_3: 146.6875 - loss: 0.2861
```  ```
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 126.6471 - false_positives_3: 134.2941 - loss: 0.2951 + 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8868 - false_negatives_3: 114.9412 - false_positives_3: 155.8235 - loss: 0.2876
```  ```
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8844 - false_negatives_3: 133.7778 - false_positives_3: 141.1667 - loss: 0.2946 + 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8859 - false_negatives_3: 124.2222 - false_positives_3: 164.3333 - loss: 0.2894
```  ```
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8848 - false_negatives_3: 140.8421 - false_positives_3: 147.4737 - loss: 0.2939 + 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8852 - false_negatives_3: 133.0000 - false_positives_3: 173.2105 - loss: 0.2911
```  ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8851 - false_negatives_3: 147.7000 - false_positives_3: 153.7500 - loss: 0.2933 + 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 141.4000 - false_positives_3: 182.0000 - loss: 0.2926
```  ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8855 - false_negatives_3: 154.4762 - false_positives_3: 160.0476 - loss: 0.2925 + 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 149.4762 - false_positives_3: 190.9048 - loss: 0.2939
```  ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8859 - false_negatives_3: 161.0909 - false_positives_3: 166.2727 - loss: 0.2917 + 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8835 - false_negatives_3: 157.7727 - false_positives_3: 199.8636 - loss: 0.2951
```  ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8863 - false_negatives_3: 167.5652 - false_positives_3: 172.5217 - loss: 0.2909 + 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8829 - false_negatives_3: 166.0000 - false_positives_3: 209.3478 - loss: 0.2963
```  ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8866 - false_negatives_3: 174.3750 - false_positives_3: 178.4167 - loss: 0.2902 + 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8824 - false_negatives_3: 174.4583 - false_positives_3: 218.5000 - loss: 0.2975
```  ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8870 - false_negatives_3: 180.7600 - false_positives_3: 184.9200 - loss: 0.2896 + 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8819 - false_negatives_3: 182.9200 - false_positives_3: 227.6400 - loss: 0.2986
```  ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8872 - false_negatives_3: 187.8846 - false_positives_3: 191.0769 - loss: 0.2892 + 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8815 - false_negatives_3: 190.9231 - false_positives_3: 236.9231 - loss: 0.2996
```  ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8874 - false_negatives_3: 194.5185 - false_positives_3: 197.7778 - loss: 0.2888 + 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8811 - false_negatives_3: 199.0741 - false_positives_3: 245.8889 - loss: 0.3004
```  ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8876 - false_negatives_3: 201.2500 - false_positives_3: 204.2857 - loss: 0.2885 + 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8807 - false_negatives_3: 207.1429 - false_positives_3: 254.8929 - loss: 0.3012
```  ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8878 - false_negatives_3: 207.7586 - false_positives_3: 211.1035 - loss: 0.2881 + 29/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8804 - false_negatives_3: 215.2759 - false_positives_3: 263.9655 - loss: 0.3019
```  ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.8880 - false_negatives_3: 214.3667 - false_positives_3: 217.6667 - loss: 0.2877 + 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8801 - false_negatives_3: 223.3333 - false_positives_3: 272.9333 - loss: 0.3025
```  ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8882 - false_negatives_3: 220.7742 - false_positives_3: 224.3548 - loss: 0.2873 + 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8798 - false_negatives_3: 231.4194 - false_positives_3: 281.7742 - loss: 0.3031
```  ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8884 - false_negatives_3: 227.4375 - false_positives_3: 230.8750 - loss: 0.2869 + 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8795 - false_negatives_3: 239.3125 - false_positives_3: 290.7812 - loss: 0.3036
```  ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8886 - false_negatives_3: 233.8788 - false_positives_3: 237.3636 - loss: 0.2865 + 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8793 - false_negatives_3: 247.3030 - false_positives_3: 299.6364 - loss: 0.3042
```  ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8888 - false_negatives_3: 240.4706 - false_positives_3: 243.7647 - loss: 0.2862 + 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8790 - false_negatives_3: 255.2059 - false_positives_3: 308.6176 - loss: 0.3047
```  ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8890 - false_negatives_3: 246.8571 - false_positives_3: 250.5429 - loss: 0.2859 + 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8788 - false_negatives_3: 263.1143 - false_positives_3: 317.4000 - loss: 0.3052
```  ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8891 - false_negatives_3: 253.5556 - false_positives_3: 257.0278 - loss: 0.2856 + 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8787 - false_negatives_3: 271.0000 - false_positives_3: 326.1667 - loss: 0.3056
```  ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8893 - false_negatives_3: 260.0270 - false_positives_3: 264.0540 - loss: 0.2855 + 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8785 - false_negatives_3: 278.7297 - false_positives_3: 334.8649 - loss: 0.3060
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8894 - false_negatives_3: 266.6842 - false_positives_3: 270.7895 - loss: 0.2854 + 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8784 - false_negatives_3: 286.3421 - false_positives_3: 343.4211 - loss: 0.3063
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8895 - false_negatives_3: 273.1282 - false_positives_3: 277.6923 - loss: 0.2852 + 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8783 - false_negatives_3: 293.8462 - false_positives_3: 351.7436 - loss: 0.3066
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8896 - false_negatives_3: 279.6750 - false_positives_3: 284.4500 - loss: 0.2851 + 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8782 - false_negatives_3: 301.1250 - false_positives_3: 360.3750 - loss: 0.3069
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8897 - false_negatives_3: 286.1951 - false_positives_3: 291.2195 - loss: 0.2850 + 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8781 - false_negatives_3: 309.1707 - false_positives_3: 368.6829 - loss: 0.3072
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8899 - false_negatives_3: 292.6190 - false_positives_3: 297.9048 - loss: 0.2848 + 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8779 - false_negatives_3: 316.9048 - false_positives_3: 377.8571 - loss: 0.3077
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8900 - false_negatives_3: 299.0465 - false_positives_3: 304.6512 - loss: 0.2847 + 43/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8777 - false_negatives_3: 324.7675 - false_positives_3: 386.8605 - loss: 0.3081
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8901 - false_negatives_3: 305.4773 - false_positives_3: 311.3409 - loss: 0.2846 + 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8776 - false_negatives_3: 332.4091 - false_positives_3: 395.7954 - loss: 0.3085
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8902 - false_negatives_3: 311.9556 - false_positives_3: 317.9778 - loss: 0.2845 + 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8775 - false_negatives_3: 340.0222 - false_positives_3: 404.7778 - loss: 0.3088
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8903 - false_negatives_3: 318.3913 - false_positives_3: 324.6522 - loss: 0.2844 + 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8774 - false_negatives_3: 347.5869 - false_positives_3: 413.7174 - loss: 0.3092
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8904 - false_negatives_3: 325.0851 - false_positives_3: 331.1702 - loss: 0.2843 + 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8773 - false_negatives_3: 355.1702 - false_positives_3: 422.5532 - loss: 0.3095
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8905 - false_negatives_3: 331.6042 - false_positives_3: 338.0208 - loss: 0.2843 + 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8772 - false_negatives_3: 362.5208 - false_positives_3: 431.3333 - loss: 0.3098
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8906 - false_negatives_3: 338.1429 - false_positives_3: 344.7755 - loss: 0.2842 + 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8771 - false_negatives_3: 370.0612 - false_positives_3: 440.1224 - loss: 0.3100
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8907 - false_negatives_3: 344.5600 - false_positives_3: 351.7400 - loss: 0.2841 + 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8770 - false_negatives_3: 377.4600 - false_positives_3: 449.2000 - loss: 0.3103
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8907 - false_negatives_3: 350.9804 - false_positives_3: 358.7059 - loss: 0.2841 + 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8769 - false_negatives_3: 385.1961 - false_positives_3: 458.0981 - loss: 0.3106
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8908 - false_negatives_3: 357.4423 - false_positives_3: 365.5962 - loss: 0.2840 + 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8768 - false_negatives_3: 392.9038 - false_positives_3: 467.1154 - loss: 0.3109
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8909 - false_negatives_3: 363.7736 - false_positives_3: 372.5094 - loss: 0.2839 + 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8767 - false_negatives_3: 400.5472 - false_positives_3: 476.0755 - loss: 0.3112
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8910 - false_negatives_3: 370.2408 - false_positives_3: 379.3148 - loss: 0.2839 + 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8766 - false_negatives_3: 408.0926 - false_positives_3: 485.1111 - loss: 0.3114
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8910 - false_negatives_3: 376.6727 - false_positives_3: 386.1273 - loss: 0.2838 + 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8765 - false_negatives_3: 416.0545 - false_positives_3: 493.9273 - loss: 0.3117
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8911 - false_negatives_3: 383.1250 - false_positives_3: 392.9286 - loss: 0.2837 + 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8764 - false_negatives_3: 423.8036 - false_positives_3: 502.9286 - loss: 0.3120
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8912 - false_negatives_3: 389.5439 - false_positives_3: 399.7018 - loss: 0.2836 + 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8763 - false_negatives_3: 431.4737 - false_positives_3: 511.8596 - loss: 0.3122
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8913 - false_negatives_3: 395.9310 - false_positives_3: 406.4655 - loss: 0.2835 + 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8763 - false_negatives_3: 439.0517 - false_positives_3: 520.9310 - loss: 0.3125
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8913 - false_negatives_3: 402.2881 - false_positives_3: 413.1526 - loss: 0.2834 + 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8762 - false_negatives_3: 446.7119 - false_positives_3: 529.8813 - loss: 0.3127
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8914 - false_negatives_3: 408.5667 - false_positives_3: 419.9000 - loss: 0.2833 + 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8761 - false_negatives_3: 454.2167 - false_positives_3: 539.0167 - loss: 0.3129
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8915 - false_negatives_3: 414.8197 - false_positives_3: 426.5574 - loss: 0.2832 + 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8760 - false_negatives_3: 461.7213 - false_positives_3: 548.0328 - loss: 0.3132
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8916 - false_negatives_3: 421.1129 - false_positives_3: 433.2742 - loss: 0.2831 + 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8760 - false_negatives_3: 469.1613 - false_positives_3: 557.1129 - loss: 0.3134
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8916 - false_negatives_3: 427.3175 - false_positives_3: 439.9683 - loss: 0.2830 + 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8759 - false_negatives_3: 476.7302 - false_positives_3: 566.0317 - loss: 0.3136
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8917 - false_negatives_3: 433.5312 - false_positives_3: 446.5938 - loss: 0.2829 + 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8758 - false_negatives_3: 484.1719 - false_positives_3: 575.2500 - loss: 0.3138
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8918 - false_negatives_3: 439.6461 - false_positives_3: 453.2308 - loss: 0.2828 + 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8758 - false_negatives_3: 491.6308 - false_positives_3: 584.3077 - loss: 0.3140
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8919 - false_negatives_3: 445.7121 - false_positives_3: 459.7879 - loss: 0.2826 + 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8757 - false_negatives_3: 499.0454 - false_positives_3: 593.2879 - loss: 0.3141
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8920 - false_negatives_3: 451.6567 - false_positives_3: 466.5672 - loss: 0.2825 + 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8756 - false_negatives_3: 506.4328 - false_positives_3: 602.3881 - loss: 0.3143
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8921 - false_negatives_3: 457.8971 - false_positives_3: 473.2059 - loss: 0.2824 + 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8756 - false_negatives_3: 513.9265 - false_positives_3: 611.3088 - loss: 0.3145
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8921 - false_negatives_3: 464.0290 - false_positives_3: 479.9276 - loss: 0.2823 + 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8755 - false_negatives_3: 521.2464 - false_positives_3: 620.4493 - loss: 0.3147
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8922 - false_negatives_3: 470.1571 - false_positives_3: 486.6857 - loss: 0.2822 + 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8755 - false_negatives_3: 528.7714 - false_positives_3: 629.5000 - loss: 0.3149
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8923 - false_negatives_3: 476.2958 - false_positives_3: 493.4366 - loss: 0.2822 + 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8754 - false_negatives_3: 536.1690 - false_positives_3: 638.6057 - loss: 0.3151
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8923 - false_negatives_3: 482.3889 - false_positives_3: 500.1528 - loss: 0.2821 + 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8754 - false_negatives_3: 543.6528 - false_positives_3: 647.6805 - loss: 0.3152
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8924 - false_negatives_3: 488.4932 - false_positives_3: 506.8767 - loss: 0.2820 + 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8753 - false_negatives_3: 551.0137 - false_positives_3: 656.8630 - loss: 0.3154
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8925 - false_negatives_3: 494.5946 - false_positives_3: 513.6622 - loss: 0.2819 + 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8753 - false_negatives_3: 558.3378 - false_positives_3: 666.0270 - loss: 0.3156
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8925 - false_negatives_3: 500.9067 - false_positives_3: 520.4933 - loss: 0.2818 + 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8752 - false_negatives_3: 565.6000 - false_positives_3: 675.2800 - loss: 0.3157
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8926 - false_negatives_3: 507.1184 - false_positives_3: 527.4079 - loss: 0.2818 + 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8752 - false_negatives_3: 572.8026 - false_positives_3: 684.4211 - loss: 0.3159
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8926 - false_negatives_3: 513.4675 - false_positives_3: 534.2338 - loss: 0.2817 + 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8752 - false_negatives_3: 580.0260 - false_positives_3: 693.5455 - loss: 0.3160
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8927 - false_negatives_3: 519.7308 - false_positives_3: 541.1154 - loss: 0.2817 + 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8751 - false_negatives_3: 587.2308 - false_positives_3: 702.7308 - loss: 0.3162
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8927 - false_negatives_3: 526.0000 - false_positives_3: 547.9874 - loss: 0.2816 + 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8751 - false_negatives_3: 594.5316 - false_positives_3: 711.8101 - loss: 0.3163
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8928 - false_negatives_3: 532.2125 - false_positives_3: 554.8375 - loss: 0.2815 + 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8751 - false_negatives_3: 601.7625 - false_positives_3: 720.9625 - loss: 0.3165
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8928 - false_negatives_3: 538.3827 - false_positives_3: 561.6543 - loss: 0.2815 + 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8750 - false_negatives_3: 609.0494 - false_positives_3: 729.9877 - loss: 0.3166
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8929 - false_negatives_3: 544.5610 - false_positives_3: 568.4634 - loss: 0.2814 + 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8750 - false_negatives_3: 616.2805 - false_positives_3: 739.0122 - loss: 0.3167
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8929 - false_negatives_3: 550.6385 - false_positives_3: 575.3615 - loss: 0.2813 + 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8750 - false_negatives_3: 623.5663 - false_positives_3: 747.9759 - loss: 0.3168
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8929 - false_negatives_3: 556.9286 - false_positives_3: 582.2024 - loss: 0.2813 + 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8749 - false_negatives_3: 630.7500 - false_positives_3: 757.0238 - loss: 0.3169
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8930 - false_negatives_3: 563.0941 - false_positives_3: 589.2471 - loss: 0.2812 + 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8749 - false_negatives_3: 638.1882 - false_positives_3: 765.9647 - loss: 0.3171
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8930 - false_negatives_3: 569.2907 - false_positives_3: 596.1744 - loss: 0.2812 + 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8749 - false_negatives_3: 645.5698 - false_positives_3: 775.1047 - loss: 0.3172
```  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8931 - false_negatives_3: 575.4598 - false_positives_3: 603.1839 - loss: 0.2812 + 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8748 - false_negatives_3: 653.0230 - false_positives_3: 784.2529 - loss: 0.3173
```  ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8931 - false_negatives_3: 581.6932 - false_positives_3: 610.1705 - loss: 0.2811 + 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8748 - false_negatives_3: 660.4659 - false_positives_3: 793.4091 - loss: 0.3174
```  ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8931 - false_negatives_3: 587.9326 - false_positives_3: 617.2247 - loss: 0.2811 + 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8748 - false_negatives_3: 667.8652 - false_positives_3: 802.5393 - loss: 0.3176
```  ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8931 - false_negatives_3: 594.4000 - false_positives_3: 624.2000 - loss: 0.2811 + 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8747 - false_negatives_3: 675.3333 - false_positives_3: 811.6111 - loss: 0.3177
```  ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 600.7692 - false_positives_3: 631.3077 - loss: 0.2811 + 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8747 - false_negatives_3: 682.7802 - false_positives_3: 820.6594 - loss: 0.3178
```  ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 607.1739 - false_positives_3: 638.3696 - loss: 0.2810 + 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8747 - false_negatives_3: 690.2500 - false_positives_3: 829.6957 - loss: 0.3179
```  ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 613.5591 - false_positives_3: 645.4731 - loss: 0.2810 + 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8746 - false_negatives_3: 697.6344 - false_positives_3: 838.8602 - loss: 0.3180
```  ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 620.0638 - false_positives_3: 652.5638 - loss: 0.2810 + 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8746 - false_negatives_3: 705.1383 - false_positives_3: 847.9681 - loss: 0.3181
```  ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 626.5158 - false_positives_3: 659.7053 - loss: 0.2810 + 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8745 - false_negatives_3: 712.5895 - false_positives_3: 857.1579 - loss: 0.3182
```  ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8932 - false_negatives_3: 633.0625 - false_positives_3: 666.8021 - loss: 0.2810 + 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8745 - false_negatives_3: 719.9688 - false_positives_3: 866.4167 - loss: 0.3183
```  ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8933 - false_negatives_3: 639.5051 - false_positives_3: 673.9691 - loss: 0.2810 + 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8745 - false_negatives_3: 727.3712 - false_positives_3: 875.6495 - loss: 0.3184
```  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8933 - false_negatives_3: 646.0612 - false_positives_3: 681.0919 - loss: 0.2810 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8744 - false_negatives_3: 734.7449 - false_positives_3: 884.7755 - loss: 0.3185
``` -Epoch 3: val_loss did not improve from 0.34519 +Epoch 2: val_loss did not improve from 0.36196  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 80ms/step - binary_accuracy: 0.8933 - false_negatives_3: 652.4849 - false_positives_3: 688.0707 - loss: 0.2810 - val_binary_accuracy: 0.8448 - val_false_negatives_3: 236.0000 - val_false_positives_3: 540.0000 - val_loss: 0.3598 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8744 - false_negatives_3: 741.9697 - false_positives_3: 893.7172 - loss: 0.3186 - val_binary_accuracy: 0.8316 - val_false_negatives_3: 202.0000 - val_false_positives_3: 640.0000 - val_loss: 0.3792
``` -Epoch 4/20 +Epoch 3/20 ```
- 1/98 ━━━━━━━━━━━━━━━━━━━━ 9s 94ms/step - binary_accuracy: 0.9141 - false_negatives_3: 5.0000 - false_positives_3: 17.0000 - loss: 0.2438 + 1/98 ━━━━━━━━━━━━━━━━━━━━ 8s 90ms/step - binary_accuracy: 0.9180 - false_negatives_3: 2.0000 - false_positives_3: 19.0000 - loss: 0.2528
```  ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9170 - false_negatives_3: 11.5000 - false_positives_3: 20.0000 - loss: 0.2470 + 2/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8975 - false_negatives_3: 16.5000 - false_positives_3: 25.5000 - loss: 0.2816
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9169 - false_negatives_3: 17.3333 - false_positives_3: 25.0000 - loss: 0.2520 + 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8887 - false_negatives_3: 23.6667 - false_positives_3: 37.3333 - loss: 0.2928
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9174 - false_negatives_3: 22.7500 - false_positives_3: 29.7500 - loss: 0.2522 + 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8845 - false_negatives_3: 32.2500 - false_positives_3: 46.2500 - loss: 0.2979
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9167 - false_negatives_3: 29.0000 - false_positives_3: 35.0000 - loss: 0.2521 + 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8828 - false_negatives_3: 39.2000 - false_positives_3: 55.4000 - loss: 0.3004
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.9166 - false_negatives_3: 34.0000 - false_positives_3: 40.8333 - loss: 0.2514 + 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8826 - false_negatives_3: 45.0000 - false_positives_3: 64.1667 - loss: 0.3010
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9170 - false_negatives_3: 39.1429 - false_positives_3: 45.7143 - loss: 0.2495 + 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8825 - false_negatives_3: 51.2857 - false_positives_3: 72.4286 - loss: 0.3006
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9175 - false_negatives_3: 44.0000 - false_positives_3: 50.5000 - loss: 0.2478 + 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8826 - false_negatives_3: 58.1250 - false_positives_3: 80.0000 - loss: 0.2999
```  ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9177 - false_negatives_3: 49.0000 - false_positives_3: 55.5556 - loss: 0.2468 + 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8829 - false_negatives_3: 64.2222 - false_positives_3: 88.0000 - loss: 0.2994
```  ```
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9179 - false_negatives_3: 54.2000 - false_positives_3: 60.6000 - loss: 0.2461 + 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8829 - false_negatives_3: 71.6000 - false_positives_3: 95.4000 - loss: 0.2993
```  ```
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9180 - false_negatives_3: 59.1818 - false_positives_3: 65.8182 - loss: 0.2454 + 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8828 - false_negatives_3: 78.5455 - false_positives_3: 103.5455 - loss: 0.2995
``` - + ```
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9183 - false_negatives_3: 63.9167 - false_positives_3: 70.7500 - loss: 0.2445 + 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8828 - false_negatives_3: 85.7500 - false_positives_3: 111.1667 - loss: 0.2999
``` - + ```
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9184 - false_negatives_3: 69.0000 - false_positives_3: 75.9231 - loss: 0.2439 + 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8830 - false_negatives_3: 92.5385 - false_positives_3: 118.3846 - loss: 0.3000
``` - + ```
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9185 - false_negatives_3: 74.3571 - false_positives_3: 80.7143 - loss: 0.2433 + 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8832 - false_negatives_3: 99.5714 - false_positives_3: 125.6429 - loss: 0.3001
``` - + ```
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9184 - false_negatives_3: 79.4667 - false_positives_3: 86.4000 - loss: 0.2431 + 15/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8834 - false_negatives_3: 106.1333 - false_positives_3: 133.0667 - loss: 0.3002
``` - + ```
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9183 - false_negatives_3: 85.1250 - false_positives_3: 91.9375 - loss: 0.2431 + 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8837 - false_negatives_3: 112.6250 - false_positives_3: 140.3750 - loss: 0.3002
``` - + ```
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9181 - false_negatives_3: 90.5294 - false_positives_3: 97.5882 - loss: 0.2433 + 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8839 - false_negatives_3: 119.1765 - false_positives_3: 147.7059 - loss: 0.3002
``` - + ```
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9180 - false_negatives_3: 96.3333 - false_positives_3: 103.0000 - loss: 0.2435 + 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 125.8333 - false_positives_3: 155.0000 - loss: 0.3004
``` - + ```
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9179 - false_negatives_3: 101.9474 - false_positives_3: 108.4737 - loss: 0.2437 + 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8843 - false_negatives_3: 131.8947 - false_positives_3: 162.8947 - loss: 0.3004
```  ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9177 - false_negatives_3: 107.4500 - false_positives_3: 114.0500 - loss: 0.2439 + 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8845 - false_negatives_3: 138.5500 - false_positives_3: 170.3500 - loss: 0.3005
```  ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9176 - false_negatives_3: 113.1905 - false_positives_3: 119.5238 - loss: 0.2439 + 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 144.9524 - false_positives_3: 178.3810 - loss: 0.3007
```  ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9175 - false_negatives_3: 118.9091 - false_positives_3: 125.1364 - loss: 0.2441 + 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 151.4091 - false_positives_3: 186.2273 - loss: 0.3008
```  ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9173 - false_negatives_3: 124.6957 - false_positives_3: 130.7391 - loss: 0.2442 + 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8847 - false_negatives_3: 157.6956 - false_positives_3: 194.3478 - loss: 0.3010
```  ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9172 - false_negatives_3: 130.4167 - false_positives_3: 136.2083 - loss: 0.2442 + 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8847 - false_negatives_3: 164.7917 - false_positives_3: 202.2083 - loss: 0.3013
```  ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9171 - false_negatives_3: 136.0800 - false_positives_3: 141.8800 - loss: 0.2444 + 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8847 - false_negatives_3: 171.5600 - false_positives_3: 210.5200 - loss: 0.3016
```  ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9169 - false_negatives_3: 141.8462 - false_positives_3: 147.5769 - loss: 0.2446 + 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 178.7308 - false_positives_3: 218.4615 - loss: 0.3019
```  ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9168 - false_negatives_3: 147.5556 - false_positives_3: 153.3704 - loss: 0.2448 + 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 185.8148 - false_positives_3: 226.2963 - loss: 0.3022
```  ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9166 - false_negatives_3: 153.6786 - false_positives_3: 158.9643 - loss: 0.2450 + 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8846 - false_negatives_3: 192.5357 - false_positives_3: 234.7500 - loss: 0.3025
```  ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9165 - false_negatives_3: 159.4483 - false_positives_3: 165.0000 - loss: 0.2453 + 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.8845 - false_negatives_3: 199.7586 - false_positives_3: 242.9310 - loss: 0.3029
```  ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9163 - false_negatives_3: 165.7667 - false_positives_3: 170.8667 - loss: 0.2456 + 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8844 - false_negatives_3: 206.9667 - false_positives_3: 251.1333 - loss: 0.3031
```  ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 171.8710 - false_positives_3: 177.0968 - loss: 0.2460 + 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 214.1290 - false_positives_3: 259.2581 - loss: 0.3034
```  ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9158 - false_negatives_3: 177.7812 - false_positives_3: 183.4062 - loss: 0.2463 + 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 221.0312 - false_positives_3: 267.3750 - loss: 0.3036
```  ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9157 - false_negatives_3: 183.7576 - false_positives_3: 189.6061 - loss: 0.2466 + 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 228.2727 - false_positives_3: 275.2424 - loss: 0.3038
```  ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9155 - false_negatives_3: 189.7647 - false_positives_3: 195.9412 - loss: 0.2469 + 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 235.1765 - false_positives_3: 283.0588 - loss: 0.3040
```  ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9153 - false_negatives_3: 195.8000 - false_positives_3: 202.3714 - loss: 0.2473 + 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 242.0286 - false_positives_3: 290.8286 - loss: 0.3041
```  ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9151 - false_negatives_3: 201.7778 - false_positives_3: 208.7500 - loss: 0.2476 + 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 248.8333 - false_positives_3: 298.9722 - loss: 0.3043
```  ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9149 - false_negatives_3: 207.5405 - false_positives_3: 215.1351 - loss: 0.2478 + 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 255.8649 - false_positives_3: 306.8378 - loss: 0.3045
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9148 - false_negatives_3: 213.3684 - false_positives_3: 221.3947 - loss: 0.2481 + 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8843 - false_negatives_3: 262.6579 - false_positives_3: 315.0526 - loss: 0.3047
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9146 - false_negatives_3: 219.1026 - false_positives_3: 227.7179 - loss: 0.2483 + 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 269.8974 - false_positives_3: 322.9487 - loss: 0.3049
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9145 - false_negatives_3: 224.9000 - false_positives_3: 234.0750 - loss: 0.2485 + 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 276.9000 - false_positives_3: 331.1500 - loss: 0.3051
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9143 - false_negatives_3: 230.7073 - false_positives_3: 240.3902 - loss: 0.2487 + 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 283.7317 - false_positives_3: 339.2195 - loss: 0.3053
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9142 - false_negatives_3: 236.3333 - false_positives_3: 246.6429 - loss: 0.2489 + 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 290.6190 - false_positives_3: 347.2619 - loss: 0.3054
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9141 - false_negatives_3: 242.1861 - false_positives_3: 252.7674 - loss: 0.2491 + 43/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 297.5116 - false_positives_3: 355.2325 - loss: 0.3056
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9140 - false_negatives_3: 247.8182 - false_positives_3: 259.0909 - loss: 0.2492 + 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 304.2954 - false_positives_3: 363.1818 - loss: 0.3058
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9139 - false_negatives_3: 253.5556 - false_positives_3: 265.2222 - loss: 0.2494 + 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 310.9333 - false_positives_3: 371.2667 - loss: 0.3059
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9138 - false_negatives_3: 259.1087 - false_positives_3: 271.7174 - loss: 0.2495 + 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 317.7609 - false_positives_3: 379.1522 - loss: 0.3060
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9137 - false_negatives_3: 265.0425 - false_positives_3: 278.0000 - loss: 0.2497 + 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 324.4468 - false_positives_3: 387.2766 - loss: 0.3061
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9136 - false_negatives_3: 270.8958 - false_positives_3: 284.3125 - loss: 0.2498 + 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 331.3750 - false_positives_3: 395.3750 - loss: 0.3063
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9135 - false_negatives_3: 276.6327 - false_positives_3: 290.7551 - loss: 0.2499 + 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 338.2245 - false_positives_3: 403.4490 - loss: 0.3064
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9134 - false_negatives_3: 282.5200 - false_positives_3: 297.0600 - loss: 0.2501 + 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 345.0600 - false_positives_3: 411.5000 - loss: 0.3065
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9132 - false_negatives_3: 288.2549 - false_positives_3: 303.5686 - loss: 0.2502 + 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 351.8824 - false_positives_3: 419.6078 - loss: 0.3066
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9131 - false_negatives_3: 294.4038 - false_positives_3: 310.0577 - loss: 0.2504 + 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 358.7500 - false_positives_3: 427.5962 - loss: 0.3066
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9130 - false_negatives_3: 300.4528 - false_positives_3: 316.6793 - loss: 0.2506 + 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 365.5660 - false_positives_3: 435.5472 - loss: 0.3067
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9128 - false_negatives_3: 306.5370 - false_positives_3: 323.2408 - loss: 0.2508 + 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 372.4259 - false_positives_3: 443.4630 - loss: 0.3068
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9127 - false_negatives_3: 312.6545 - false_positives_3: 329.7091 - loss: 0.2509 + 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 379.2909 - false_positives_3: 451.3273 - loss: 0.3068
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9126 - false_negatives_3: 318.6964 - false_positives_3: 336.2500 - loss: 0.2511 + 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 386.1607 - false_positives_3: 459.2143 - loss: 0.3069
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9125 - false_negatives_3: 324.7544 - false_positives_3: 342.7719 - loss: 0.2513 + 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8842 - false_negatives_3: 393.1053 - false_positives_3: 467.1930 - loss: 0.3069
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9124 - false_negatives_3: 330.8276 - false_positives_3: 349.3621 - loss: 0.2514 + 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 400.0517 - false_positives_3: 475.2586 - loss: 0.3070
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9123 - false_negatives_3: 337.0339 - false_positives_3: 355.7797 - loss: 0.2516 + 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8842 - false_negatives_3: 407.0508 - false_positives_3: 483.1864 - loss: 0.3070
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_3: 343.1000 - false_positives_3: 362.3167 - loss: 0.2517 + 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 413.8833 - false_positives_3: 491.4667 - loss: 0.3071
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_3: 349.2295 - false_positives_3: 368.8197 - loss: 0.2519 + 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 420.8524 - false_positives_3: 499.5574 - loss: 0.3072
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9119 - false_negatives_3: 355.3548 - false_positives_3: 375.2097 - loss: 0.2520 + 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 427.6613 - false_positives_3: 507.7097 - loss: 0.3072
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9118 - false_negatives_3: 361.4286 - false_positives_3: 381.6190 - loss: 0.2521 + 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 434.7302 - false_positives_3: 515.6984 - loss: 0.3073
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9118 - false_negatives_3: 367.5469 - false_positives_3: 387.9375 - loss: 0.2522 + 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 441.6562 - false_positives_3: 523.8281 - loss: 0.3073
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9116 - false_negatives_3: 373.5231 - false_positives_3: 394.6154 - loss: 0.2524 + 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8841 - false_negatives_3: 448.6461 - false_positives_3: 531.8770 - loss: 0.3074
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9115 - false_negatives_3: 380.0000 - false_positives_3: 401.1364 - loss: 0.2525 + 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8840 - false_negatives_3: 455.5909 - false_positives_3: 540.0757 - loss: 0.3074
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9114 - false_negatives_3: 386.4030 - false_positives_3: 407.6418 - loss: 0.2527 + 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8840 - false_negatives_3: 462.7015 - false_positives_3: 548.1194 - loss: 0.3075
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9113 - false_negatives_3: 392.7353 - false_positives_3: 414.1618 - loss: 0.2528 + 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8840 - false_negatives_3: 469.7353 - false_positives_3: 556.3383 - loss: 0.3075
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9112 - false_negatives_3: 399.1304 - false_positives_3: 420.7246 - loss: 0.2530 + 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8840 - false_negatives_3: 476.9276 - false_positives_3: 564.5507 - loss: 0.3076
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9111 - false_negatives_3: 405.5428 - false_positives_3: 427.2714 - loss: 0.2531 + 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8839 - false_negatives_3: 484.1143 - false_positives_3: 572.8428 - loss: 0.3077
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9110 - false_negatives_3: 412.0000 - false_positives_3: 433.7324 - loss: 0.2533 + 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8839 - false_negatives_3: 491.2676 - false_positives_3: 581.2676 - loss: 0.3077
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9109 - false_negatives_3: 418.4167 - false_positives_3: 440.3611 - loss: 0.2534 + 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8839 - false_negatives_3: 498.4445 - false_positives_3: 589.5833 - loss: 0.3078
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 425.0274 - false_positives_3: 446.9041 - loss: 0.2536 + 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8838 - false_negatives_3: 505.5342 - false_positives_3: 597.9726 - loss: 0.3079
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 431.4865 - false_positives_3: 453.4595 - loss: 0.2537 + 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8838 - false_negatives_3: 512.6892 - false_positives_3: 606.3919 - loss: 0.3079
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 437.8267 - false_positives_3: 460.0267 - loss: 0.2539 + 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8838 - false_negatives_3: 519.7733 - false_positives_3: 614.7333 - loss: 0.3080
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9105 - false_negatives_3: 444.1974 - false_positives_3: 466.5789 - loss: 0.2540 + 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8837 - false_negatives_3: 526.8158 - false_positives_3: 623.0658 - loss: 0.3080
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9104 - false_negatives_3: 450.5195 - false_positives_3: 473.1688 - loss: 0.2541 + 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8837 - false_negatives_3: 533.8701 - false_positives_3: 631.3376 - loss: 0.3081
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9103 - false_negatives_3: 456.8462 - false_positives_3: 479.7308 - loss: 0.2542 + 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8837 - false_negatives_3: 540.8589 - false_positives_3: 639.5641 - loss: 0.3081
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9102 - false_negatives_3: 463.1013 - false_positives_3: 486.4430 - loss: 0.2543 + 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8837 - false_negatives_3: 547.7975 - false_positives_3: 647.8228 - loss: 0.3081
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9101 - false_negatives_3: 469.3625 - false_positives_3: 493.1000 - loss: 0.2544 + 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8836 - false_negatives_3: 554.9125 - false_positives_3: 655.9500 - loss: 0.3082
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9100 - false_negatives_3: 475.6173 - false_positives_3: 499.6913 - loss: 0.2546 + 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8836 - false_negatives_3: 561.8889 - false_positives_3: 664.1852 - loss: 0.3082
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9100 - false_negatives_3: 481.8293 - false_positives_3: 506.2317 - loss: 0.2546 + 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8836 - false_negatives_3: 569.1097 - false_positives_3: 672.3415 - loss: 0.3082
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 488.0602 - false_positives_3: 512.7831 - loss: 0.2547 + 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8836 - false_negatives_3: 576.2048 - false_positives_3: 680.8795 - loss: 0.3083
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9098 - false_negatives_3: 494.2738 - false_positives_3: 519.2976 - loss: 0.2548 + 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8835 - false_negatives_3: 583.5595 - false_positives_3: 689.2738 - loss: 0.3083
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9097 - false_negatives_3: 500.4706 - false_positives_3: 525.8118 - loss: 0.2549 + 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8835 - false_negatives_3: 590.8353 - false_positives_3: 697.6470 - loss: 0.3084
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9097 - false_negatives_3: 506.6628 - false_positives_3: 532.2675 - loss: 0.2550 + 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8834 - false_negatives_3: 598.0698 - false_positives_3: 706.0698 - loss: 0.3084
```  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 512.8161 - false_positives_3: 538.7701 - loss: 0.2551 + 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8834 - false_negatives_3: 605.2643 - false_positives_3: 714.5057 - loss: 0.3085
```  ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9095 - false_negatives_3: 519.0568 - false_positives_3: 545.2159 - loss: 0.2552 + 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8834 - false_negatives_3: 612.3864 - false_positives_3: 723.0227 - loss: 0.3085
```  ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9095 - false_negatives_3: 525.1910 - false_positives_3: 551.7079 - loss: 0.2553 + 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8833 - false_negatives_3: 619.5955 - false_positives_3: 731.4719 - loss: 0.3086
```  ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9094 - false_negatives_3: 531.3889 - false_positives_3: 558.1667 - loss: 0.2554 + 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8833 - false_negatives_3: 626.8000 - false_positives_3: 739.9667 - loss: 0.3086
```  ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9093 - false_negatives_3: 537.5494 - false_positives_3: 564.6484 - loss: 0.2555 + 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8833 - false_negatives_3: 634.0549 - false_positives_3: 748.4176 - loss: 0.3087
```  ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9093 - false_negatives_3: 543.6630 - false_positives_3: 571.0978 - loss: 0.2555 + 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8832 - false_negatives_3: 641.2283 - false_positives_3: 756.9783 - loss: 0.3087
```  ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9092 - false_negatives_3: 549.8065 - false_positives_3: 577.5054 - loss: 0.2556 + 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8832 - false_negatives_3: 648.3978 - false_positives_3: 765.5699 - loss: 0.3088
```  ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9092 - false_negatives_3: 555.8936 - false_positives_3: 583.9042 - loss: 0.2557 + 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8832 - false_negatives_3: 655.5958 - false_positives_3: 774.0958 - loss: 0.3088
```  ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9091 - false_negatives_3: 562.0632 - false_positives_3: 590.2526 - loss: 0.2558 + 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8831 - false_negatives_3: 662.7579 - false_positives_3: 782.5263 - loss: 0.3089
```  ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9091 - false_negatives_3: 568.1562 - false_positives_3: 596.6250 - loss: 0.2558 + 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8831 - false_negatives_3: 669.8333 - false_positives_3: 791.0000 - loss: 0.3089
```  ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9090 - false_negatives_3: 574.2062 - false_positives_3: 602.9587 - loss: 0.2559 + 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8831 - false_negatives_3: 677.0516 - false_positives_3: 799.3815 - loss: 0.3089
```  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9090 - false_negatives_3: 580.2449 - false_positives_3: 609.2245 - loss: 0.2560 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8830 - false_negatives_3: 684.1326 - false_positives_3: 807.8878 - loss: 0.3090
``` -Epoch 4: val_loss did not improve from 0.34519 +Epoch 3: val_loss did not improve from 0.36196  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.9089 - false_negatives_3: 586.1616 - false_positives_3: 615.3636 - loss: 0.2560 - val_binary_accuracy: 0.8496 - val_false_negatives_3: 226.0000 - val_false_positives_3: 526.0000 - val_loss: 0.3813 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8830 - false_negatives_3: 691.0707 - false_positives_3: 816.2222 - loss: 0.3090 - val_binary_accuracy: 0.8118 - val_false_negatives_3: 738.0000 - val_false_positives_3: 203.0000 - val_loss: 0.4112
``` -Epoch 5/20 +Epoch 4/20 ```
- 1/98 ━━━━━━━━━━━━━━━━━━━━ 9s 95ms/step - binary_accuracy: 0.8594 - false_negatives_3: 2.0000 - false_positives_3: 34.0000 - loss: 0.3404 + 1/98 ━━━━━━━━━━━━━━━━━━━━ 8s 89ms/step - binary_accuracy: 0.8750 - false_negatives_3: 22.0000 - false_positives_3: 10.0000 - loss: 0.3122
``` - + ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.8594 - false_negatives_3: 18.5000 - false_positives_3: 35.5000 - loss: 0.3305 + 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8906 - false_negatives_3: 23.5000 - false_positives_3: 16.5000 - loss: 0.2944
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8689 - false_negatives_3: 24.6667 - false_positives_3: 40.0000 - loss: 0.3137 + 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8950 - false_negatives_3: 28.0000 - false_positives_3: 23.3333 - loss: 0.2906
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8773 - false_negatives_3: 29.7500 - false_positives_3: 43.7500 - loss: 0.3004 + 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8973 - false_negatives_3: 33.7500 - false_positives_3: 29.2500 - loss: 0.2864
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8826 - false_negatives_3: 34.4000 - false_positives_3: 49.0000 - loss: 0.2915 + 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 39.2000 - false_positives_3: 37.0000 - loss: 0.2843
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8870 - false_negatives_3: 38.6667 - false_positives_3: 54.1667 - loss: 0.2843 + 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8978 - false_negatives_3: 44.5000 - false_positives_3: 45.0000 - loss: 0.2831
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8904 - false_negatives_3: 43.2857 - false_positives_3: 59.0000 - loss: 0.2785 + 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8981 - false_negatives_3: 50.5714 - false_positives_3: 51.8571 - loss: 0.2817
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8930 - false_negatives_3: 47.1250 - false_positives_3: 65.1250 - loss: 0.2740 + 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 56.5000 - false_positives_3: 59.2500 - loss: 0.2814
```  ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8954 - false_negatives_3: 51.2222 - false_positives_3: 70.5556 - loss: 0.2703 + 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 63.6667 - false_positives_3: 65.6667 - loss: 0.2814
```  ```
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8974 - false_negatives_3: 55.2000 - false_positives_3: 75.9000 - loss: 0.2672 + 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8978 - false_negatives_3: 69.9000 - false_positives_3: 72.8000 - loss: 0.2813
```  ```
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.8991 - false_negatives_3: 59.6364 - false_positives_3: 81.0909 - loss: 0.2647 + 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8978 - false_negatives_3: 76.5455 - false_positives_3: 79.5455 - loss: 0.2814
```  ```
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9007 - false_negatives_3: 63.5000 - false_positives_3: 86.4167 - loss: 0.2624 + 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 82.6667 - false_positives_3: 86.9167 - loss: 0.2814
```  ```
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9019 - false_negatives_3: 68.0769 - false_positives_3: 91.7692 - loss: 0.2610 + 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 88.6923 - false_positives_3: 94.0000 - loss: 0.2814
```  ```
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9030 - false_negatives_3: 72.4286 - false_positives_3: 97.2143 - loss: 0.2597 + 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 94.8571 - false_positives_3: 100.9286 - loss: 0.2815
``` - + ```
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9039 - false_negatives_3: 76.9333 - false_positives_3: 102.5333 - loss: 0.2585 + 15/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8975 - false_negatives_3: 100.4667 - false_positives_3: 109.1333 - loss: 0.2820
``` - + ```
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9047 - false_negatives_3: 81.7500 - false_positives_3: 108.0000 - loss: 0.2576 + 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8972 - false_negatives_3: 107.3125 - false_positives_3: 116.7500 - loss: 0.2825
``` - + ```
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9054 - false_negatives_3: 86.3529 - false_positives_3: 113.4706 - loss: 0.2567 + 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8968 - false_negatives_3: 114.3529 - false_positives_3: 124.4118 - loss: 0.2830
``` - + ```
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9061 - false_negatives_3: 91.1111 - false_positives_3: 118.7222 - loss: 0.2558 + 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8966 - false_negatives_3: 120.8333 - false_positives_3: 132.0556 - loss: 0.2832
``` - + ```
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9067 - false_negatives_3: 95.7368 - false_positives_3: 124.0000 - loss: 0.2550 + 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8965 - false_negatives_3: 127.1579 - false_positives_3: 139.4211 - loss: 0.2834
``` - + ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9073 - false_negatives_3: 100.9000 - false_positives_3: 128.8500 - loss: 0.2543 + 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8964 - false_negatives_3: 133.0500 - false_positives_3: 147.3500 - loss: 0.2835
```  ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9078 - false_negatives_3: 105.7619 - false_positives_3: 134.3333 - loss: 0.2537 + 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8961 - false_negatives_3: 139.9524 - false_positives_3: 155.0476 - loss: 0.2839
```  ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9081 - false_negatives_3: 111.4091 - false_positives_3: 139.6364 - loss: 0.2533 + 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8958 - false_negatives_3: 146.4545 - false_positives_3: 163.3636 - loss: 0.2843
```  ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9083 - false_negatives_3: 116.8261 - false_positives_3: 145.4783 - loss: 0.2531 + 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8955 - false_negatives_3: 153.2174 - false_positives_3: 171.4783 - loss: 0.2845
```  ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9085 - false_negatives_3: 122.5000 - false_positives_3: 151.0833 - loss: 0.2528 + 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8952 - false_negatives_3: 159.7917 - false_positives_3: 179.8750 - loss: 0.2848
```  ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9087 - false_negatives_3: 128.1600 - false_positives_3: 156.9200 - loss: 0.2527 + 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8950 - false_negatives_3: 166.6400 - false_positives_3: 187.9600 - loss: 0.2851
```  ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9088 - false_negatives_3: 133.6923 - false_positives_3: 162.6538 - loss: 0.2526 + 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8947 - false_negatives_3: 173.3077 - false_positives_3: 196.3462 - loss: 0.2853
```  ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9090 - false_negatives_3: 139.2963 - false_positives_3: 168.2222 - loss: 0.2525 + 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8945 - false_negatives_3: 180.1481 - false_positives_3: 204.5185 - loss: 0.2856
```  ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9092 - false_negatives_3: 144.5714 - false_positives_3: 174.0000 - loss: 0.2523 + 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8942 - false_negatives_3: 186.7143 - false_positives_3: 212.8929 - loss: 0.2858
```  ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9093 - false_negatives_3: 150.2069 - false_positives_3: 179.7586 - loss: 0.2522 + 29/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8940 - false_negatives_3: 193.1379 - false_positives_3: 221.1379 - loss: 0.2861
```  ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9094 - false_negatives_3: 155.7333 - false_positives_3: 185.8333 - loss: 0.2522 + 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8938 - false_negatives_3: 199.6667 - false_positives_3: 229.5667 - loss: 0.2863
```  ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9094 - false_negatives_3: 161.4839 - false_positives_3: 191.7097 - loss: 0.2521 + 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8936 - false_negatives_3: 206.3871 - false_positives_3: 237.6452 - loss: 0.2865
```  ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9095 - false_negatives_3: 166.8750 - false_positives_3: 197.7188 - loss: 0.2521 + 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8935 - false_negatives_3: 213.0625 - false_positives_3: 245.5000 - loss: 0.2867
```  ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 172.8788 - false_positives_3: 203.5758 - loss: 0.2521 + 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8934 - false_negatives_3: 219.6061 - false_positives_3: 253.1515 - loss: 0.2868
```  ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 178.7647 - false_positives_3: 209.8529 - loss: 0.2522 + 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8933 - false_negatives_3: 226.1471 - false_positives_3: 260.9706 - loss: 0.2869
```  ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 184.7714 - false_positives_3: 215.8000 - loss: 0.2522 + 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8932 - false_negatives_3: 233.1429 - false_positives_3: 268.5143 - loss: 0.2871
```  ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 190.7222 - false_positives_3: 221.7222 - loss: 0.2522 + 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8930 - false_negatives_3: 239.8611 - false_positives_3: 276.5278 - loss: 0.2872
```  ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 196.5946 - false_positives_3: 227.5676 - loss: 0.2522 + 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8929 - false_negatives_3: 246.8649 - false_positives_3: 284.3784 - loss: 0.2874
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9096 - false_negatives_3: 202.5000 - false_positives_3: 233.2895 - loss: 0.2521 + 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8927 - false_negatives_3: 253.5526 - false_positives_3: 292.4737 - loss: 0.2875
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9097 - false_negatives_3: 208.1795 - false_positives_3: 238.9231 - loss: 0.2520 + 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8926 - false_negatives_3: 260.2564 - false_positives_3: 300.3846 - loss: 0.2877
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9098 - false_negatives_3: 213.6250 - false_positives_3: 244.7500 - loss: 0.2520 + 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8925 - false_negatives_3: 266.8000 - false_positives_3: 308.4500 - loss: 0.2879
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9098 - false_negatives_3: 219.5366 - false_positives_3: 250.5610 - loss: 0.2519 + 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8924 - false_negatives_3: 273.2683 - false_positives_3: 316.4634 - loss: 0.2880
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9098 - false_negatives_3: 225.2619 - false_positives_3: 256.5000 - loss: 0.2519 + 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8923 - false_negatives_3: 279.7857 - false_positives_3: 324.3810 - loss: 0.2881
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9098 - false_negatives_3: 231.0698 - false_positives_3: 262.3721 - loss: 0.2519 + 43/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8922 - false_negatives_3: 286.2558 - false_positives_3: 332.3721 - loss: 0.2882
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 236.7500 - false_positives_3: 268.3636 - loss: 0.2518 + 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8922 - false_negatives_3: 292.7273 - false_positives_3: 340.3409 - loss: 0.2884
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 242.6444 - false_positives_3: 274.1333 - loss: 0.2518 + 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8921 - false_negatives_3: 299.0889 - false_positives_3: 348.2222 - loss: 0.2885
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 248.4565 - false_positives_3: 280.0869 - loss: 0.2518 + 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8920 - false_negatives_3: 305.5217 - false_positives_3: 355.9565 - loss: 0.2885
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 254.3830 - false_positives_3: 285.8936 - loss: 0.2518 + 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8920 - false_negatives_3: 311.8085 - false_positives_3: 363.8936 - loss: 0.2886
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 260.1458 - false_positives_3: 291.7500 - loss: 0.2517 + 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8919 - false_negatives_3: 318.5000 - false_positives_3: 371.7292 - loss: 0.2888
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 265.9592 - false_positives_3: 297.4898 - loss: 0.2516 + 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8918 - false_negatives_3: 325.1429 - false_positives_3: 379.7143 - loss: 0.2890
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9099 - false_negatives_3: 271.6800 - false_positives_3: 303.3000 - loss: 0.2516 + 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8917 - false_negatives_3: 331.8400 - false_positives_3: 387.6400 - loss: 0.2891
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9100 - false_negatives_3: 277.3529 - false_positives_3: 309.0588 - loss: 0.2516 + 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8917 - false_negatives_3: 338.3726 - false_positives_3: 395.7647 - loss: 0.2892
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9100 - false_negatives_3: 282.9038 - false_positives_3: 314.7500 - loss: 0.2515 + 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8916 - false_negatives_3: 345.0385 - false_positives_3: 403.7115 - loss: 0.2894
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9101 - false_negatives_3: 288.3773 - false_positives_3: 320.4528 - loss: 0.2514 + 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8915 - false_negatives_3: 351.5472 - false_positives_3: 411.8491 - loss: 0.2895
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9101 - false_negatives_3: 293.8518 - false_positives_3: 326.1296 - loss: 0.2514 + 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8914 - false_negatives_3: 358.2222 - false_positives_3: 419.7963 - loss: 0.2896
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9101 - false_negatives_3: 299.2545 - false_positives_3: 331.8000 - loss: 0.2513 + 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8914 - false_negatives_3: 364.8546 - false_positives_3: 427.7636 - loss: 0.2897
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9102 - false_negatives_3: 304.7143 - false_positives_3: 337.3393 - loss: 0.2512 + 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8913 - false_negatives_3: 371.3214 - false_positives_3: 435.7321 - loss: 0.2898
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9102 - false_negatives_3: 310.0877 - false_positives_3: 342.9825 - loss: 0.2512 + 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8913 - false_negatives_3: 377.9474 - false_positives_3: 443.7544 - loss: 0.2899
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9103 - false_negatives_3: 315.3965 - false_positives_3: 348.5862 - loss: 0.2511 + 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8912 - false_negatives_3: 384.4483 - false_positives_3: 451.7586 - loss: 0.2900
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9103 - false_negatives_3: 320.6780 - false_positives_3: 354.2203 - loss: 0.2510 + 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8911 - false_negatives_3: 391.2373 - false_positives_3: 459.6102 - loss: 0.2901
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9104 - false_negatives_3: 325.9333 - false_positives_3: 359.8333 - loss: 0.2509 + 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8911 - false_negatives_3: 397.8500 - false_positives_3: 467.7667 - loss: 0.2902
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9105 - false_negatives_3: 331.1639 - false_positives_3: 365.4099 - loss: 0.2509 + 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8910 - false_negatives_3: 404.5082 - false_positives_3: 475.7377 - loss: 0.2903
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9105 - false_negatives_3: 336.3387 - false_positives_3: 371.0807 - loss: 0.2508 + 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8909 - false_negatives_3: 411.0968 - false_positives_3: 483.7581 - loss: 0.2904
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9105 - false_negatives_3: 341.7778 - false_positives_3: 376.7460 - loss: 0.2507 + 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8909 - false_negatives_3: 417.6349 - false_positives_3: 491.7778 - loss: 0.2905
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 347.2812 - false_positives_3: 382.5312 - loss: 0.2507 + 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8908 - false_negatives_3: 424.2188 - false_positives_3: 499.7500 - loss: 0.2906
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 352.8308 - false_positives_3: 388.2308 - loss: 0.2506 + 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8908 - false_negatives_3: 430.9077 - false_positives_3: 507.6461 - loss: 0.2906
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 358.3333 - false_positives_3: 394.0151 - loss: 0.2506 + 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8908 - false_negatives_3: 437.4546 - false_positives_3: 515.5606 - loss: 0.2907
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 364.0000 - false_positives_3: 399.7314 - loss: 0.2506 + 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8907 - false_negatives_3: 444.1045 - false_positives_3: 523.4329 - loss: 0.2908
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9106 - false_negatives_3: 369.5441 - false_positives_3: 405.6176 - loss: 0.2505 + 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8907 - false_negatives_3: 450.7206 - false_positives_3: 531.4265 - loss: 0.2908
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 375.1739 - false_positives_3: 411.4493 - loss: 0.2505 + 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8906 - false_negatives_3: 457.4203 - false_positives_3: 539.3333 - loss: 0.2909
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 380.7857 - false_positives_3: 417.3000 - loss: 0.2505 + 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8905 - false_negatives_3: 464.0571 - false_positives_3: 547.5857 - loss: 0.2910
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 386.3944 - false_positives_3: 423.1268 - loss: 0.2505 + 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8905 - false_negatives_3: 470.9155 - false_positives_3: 555.6901 - loss: 0.2911
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 392.0278 - false_positives_3: 428.8750 - loss: 0.2504 + 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8904 - false_negatives_3: 477.6111 - false_positives_3: 564.0000 - loss: 0.2912
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 397.6301 - false_positives_3: 434.5891 - loss: 0.2504 + 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8903 - false_negatives_3: 484.4795 - false_positives_3: 572.1918 - loss: 0.2913
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 403.1757 - false_positives_3: 440.3513 - loss: 0.2504 + 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8903 - false_negatives_3: 491.2433 - false_positives_3: 580.4324 - loss: 0.2913
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 408.8533 - false_positives_3: 446.1600 - loss: 0.2503 + 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8902 - false_negatives_3: 498.0133 - false_positives_3: 588.6800 - loss: 0.2914
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 414.5789 - false_positives_3: 451.9342 - loss: 0.2503 + 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8902 - false_negatives_3: 504.7895 - false_positives_3: 596.9211 - loss: 0.2915
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 420.2078 - false_positives_3: 457.7143 - loss: 0.2502 + 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8901 - false_negatives_3: 511.4935 - false_positives_3: 605.1299 - loss: 0.2916
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 425.9615 - false_positives_3: 463.3974 - loss: 0.2502 + 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8901 - false_negatives_3: 518.1282 - false_positives_3: 613.2820 - loss: 0.2916
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 431.6076 - false_positives_3: 469.2532 - loss: 0.2502 + 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8900 - false_negatives_3: 524.6709 - false_positives_3: 621.4431 - loss: 0.2917
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 437.3625 - false_positives_3: 474.9750 - loss: 0.2501 + 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8900 - false_negatives_3: 531.3750 - false_positives_3: 629.4625 - loss: 0.2917
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 443.0000 - false_positives_3: 480.8642 - loss: 0.2501 + 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8899 - false_negatives_3: 537.9506 - false_positives_3: 637.8395 - loss: 0.2918
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 448.7805 - false_positives_3: 486.6707 - loss: 0.2501 + 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8899 - false_negatives_3: 544.7561 - false_positives_3: 646.0732 - loss: 0.2919
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 454.5422 - false_positives_3: 492.5783 - loss: 0.2501 + 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8898 - false_negatives_3: 551.5060 - false_positives_3: 654.3132 - loss: 0.2919
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 460.3095 - false_positives_3: 498.4762 - loss: 0.2500 + 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8897 - false_negatives_3: 558.2738 - false_positives_3: 662.4881 - loss: 0.2920
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9108 - false_negatives_3: 466.0941 - false_positives_3: 504.3294 - loss: 0.2500 + 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8897 - false_negatives_3: 564.9882 - false_positives_3: 670.7177 - loss: 0.2921
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 471.8837 - false_positives_3: 510.1512 - loss: 0.2500 + 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8897 - false_negatives_3: 571.6860 - false_positives_3: 678.8837 - loss: 0.2921
```  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 477.6782 - false_positives_3: 516.0000 - loss: 0.2500 + 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8896 - false_negatives_3: 578.4253 - false_positives_3: 687.0575 - loss: 0.2922
```  ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 483.5000 - false_positives_3: 521.8068 - loss: 0.2500 + 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8896 - false_negatives_3: 585.1591 - false_positives_3: 695.1818 - loss: 0.2922
```  ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 489.2921 - false_positives_3: 527.6741 - loss: 0.2500 + 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8895 - false_negatives_3: 591.9101 - false_positives_3: 703.2921 - loss: 0.2923
```  ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 495.0889 - false_positives_3: 533.5000 - loss: 0.2500 + 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8895 - false_negatives_3: 598.6000 - false_positives_3: 711.3444 - loss: 0.2923
```  ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 500.8462 - false_positives_3: 539.2527 - loss: 0.2500 + 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8894 - false_negatives_3: 605.3297 - false_positives_3: 719.4066 - loss: 0.2924
```  ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 506.5544 - false_positives_3: 545.0435 - loss: 0.2500 + 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8894 - false_negatives_3: 612.0326 - false_positives_3: 727.5761 - loss: 0.2924
```  ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 512.3226 - false_positives_3: 550.8602 - loss: 0.2500 + 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8894 - false_negatives_3: 618.7957 - false_positives_3: 735.6667 - loss: 0.2925
```  ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 518.0638 - false_positives_3: 556.6383 - loss: 0.2499 + 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8893 - false_negatives_3: 625.4468 - false_positives_3: 743.8298 - loss: 0.2925
```  ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 523.8000 - false_positives_3: 562.3895 - loss: 0.2499 + 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8893 - false_negatives_3: 632.1473 - false_positives_3: 751.9158 - loss: 0.2926
```  ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 529.5312 - false_positives_3: 568.1562 - loss: 0.2499 + 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8893 - false_negatives_3: 638.7812 - false_positives_3: 760.1562 - loss: 0.2927
```  ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 535.2062 - false_positives_3: 573.9691 - loss: 0.2499 + 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8892 - false_negatives_3: 645.4433 - false_positives_3: 768.3299 - loss: 0.2927
```  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9107 - false_negatives_3: 540.8062 - false_positives_3: 579.7347 - loss: 0.2499 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8892 - false_negatives_3: 651.9898 - false_positives_3: 776.4388 - loss: 0.2928
``` -Epoch 5: val_loss did not improve from 0.34519 +Epoch 4: val_loss did not improve from 0.36196  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.9107 - false_negatives_3: 546.2929 - false_positives_3: 585.3839 - loss: 0.2498 - val_binary_accuracy: 0.8434 - val_false_negatives_3: 510.0000 - val_false_positives_3: 273.0000 - val_loss: 0.3798 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8892 - false_negatives_3: 658.4041 - false_positives_3: 784.3839 - loss: 0.2928 - val_binary_accuracy: 0.8344 - val_false_negatives_3: 557.0000 - val_false_positives_3: 271.0000 - val_loss: 0.3734
``` -Epoch 6/20 +Epoch 5/20 ```
- 1/98 ━━━━━━━━━━━━━━━━━━━━ 9s 93ms/step - binary_accuracy: 0.9336 - false_negatives_3: 13.0000 - false_positives_3: 4.0000 - loss: 0.1881 + 1/98 ━━━━━━━━━━━━━━━━━━━━ 8s 87ms/step - binary_accuracy: 0.8906 - false_negatives_3: 23.0000 - false_positives_3: 5.0000 - loss: 0.3190
```  ```
- 2/98 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9297 - false_negatives_3: 15.5000 - false_positives_3: 12.0000 - loss: 0.1901 + 2/98 ━━━━━━━━━━━━━━━━━━━━ 6s 71ms/step - binary_accuracy: 0.8828 - false_negatives_3: 24.0000 - false_positives_3: 22.0000 - loss: 0.3187
```  ```
- 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9284 - false_negatives_3: 21.3333 - false_positives_3: 16.0000 - loss: 0.1904 + 3/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8824 - false_negatives_3: 30.6667 - false_positives_3: 30.3333 - loss: 0.3117
```  ```
- 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9258 - false_negatives_3: 26.7500 - false_positives_3: 22.2500 - loss: 0.1951 + 4/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8844 - false_negatives_3: 35.7500 - false_positives_3: 38.0000 - loss: 0.3076
```  ```
- 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9245 - false_negatives_3: 32.2000 - false_positives_3: 27.6000 - loss: 0.1979 + 5/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8868 - false_negatives_3: 40.2000 - false_positives_3: 45.4000 - loss: 0.3036
```  ```
- 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9239 - false_negatives_3: 36.3333 - false_positives_3: 33.8333 - loss: 0.1999 + 6/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8881 - false_negatives_3: 46.0000 - false_positives_3: 52.3333 - loss: 0.3014
```  ```
- 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9232 - false_negatives_3: 41.4286 - false_positives_3: 39.4286 - loss: 0.2016 + 7/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8891 - false_negatives_3: 51.7143 - false_positives_3: 59.4286 - loss: 0.2999
```  ```
- 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9227 - false_negatives_3: 46.2500 - false_positives_3: 45.1250 - loss: 0.2034 + 8/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8904 - false_negatives_3: 57.2500 - false_positives_3: 65.6250 - loss: 0.2979
```  ```
- 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9228 - false_negatives_3: 50.7778 - false_positives_3: 50.0000 - loss: 0.2039 + 9/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8916 - false_negatives_3: 61.8889 - false_positives_3: 72.7778 - loss: 0.2962
```  ```
- 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9229 - false_negatives_3: 55.3000 - false_positives_3: 54.9000 - loss: 0.2041 + 10/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8923 - false_negatives_3: 67.7000 - false_positives_3: 79.3000 - loss: 0.2949
```  ```
- 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9230 - false_negatives_3: 59.0909 - false_positives_3: 60.4545 - loss: 0.2042 + 11/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8930 - false_negatives_3: 72.9091 - false_positives_3: 86.3636 - loss: 0.2936
```  ```
- 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9227 - false_negatives_3: 65.2500 - false_positives_3: 65.2500 - loss: 0.2051 + 12/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8933 - false_negatives_3: 79.6667 - false_positives_3: 92.9167 - loss: 0.2930
```  ```
- 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9218 - false_negatives_3: 70.8462 - false_positives_3: 72.2308 - loss: 0.2068 + 13/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.8935 - false_negatives_3: 85.7692 - false_positives_3: 100.1538 - loss: 0.2925
``` - + ```
- 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9212 - false_negatives_3: 76.5714 - false_positives_3: 78.6429 - loss: 0.2081 + 14/98 ━━━━━━━━━━━━━━━━━━━━ 6s 72ms/step - binary_accuracy: 0.8937 - false_negatives_3: 91.8571 - false_positives_3: 107.2143 - loss: 0.2921
``` - + ```
- 15/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9206 - false_negatives_3: 82.4667 - false_positives_3: 84.7333 - loss: 0.2093 + 15/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8940 - false_negatives_3: 97.6667 - false_positives_3: 114.4000 - loss: 0.2916
``` - + ```
- 16/98 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9202 - false_negatives_3: 87.9375 - false_positives_3: 90.6875 - loss: 0.2103 + 16/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8941 - false_negatives_3: 103.8750 - false_positives_3: 121.4375 - loss: 0.2912
``` - + ```
- 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9198 - false_negatives_3: 93.7647 - false_positives_3: 96.4706 - loss: 0.2115 + 17/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8943 - false_negatives_3: 110.1765 - false_positives_3: 128.2353 - loss: 0.2908
``` - + ```
- 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9196 - false_negatives_3: 99.3889 - false_positives_3: 101.9444 - loss: 0.2124 + 18/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8946 - false_negatives_3: 116.2778 - false_positives_3: 134.7222 - loss: 0.2901
``` - + ```
- 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9193 - false_negatives_3: 105.1053 - false_positives_3: 107.3684 - loss: 0.2132 + 19/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8948 - false_negatives_3: 122.3684 - false_positives_3: 141.0000 - loss: 0.2895
```  ```
- 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9191 - false_negatives_3: 110.4000 - false_positives_3: 113.4000 - loss: 0.2140 + 20/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8951 - false_negatives_3: 128.0500 - false_positives_3: 147.6000 - loss: 0.2888
```  ```
- 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9187 - false_negatives_3: 116.7619 - false_positives_3: 119.0476 - loss: 0.2148 + 21/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8954 - false_negatives_3: 134.0952 - false_positives_3: 153.9048 - loss: 0.2881
```  ```
- 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9184 - false_negatives_3: 122.7273 - false_positives_3: 125.1818 - loss: 0.2156 + 22/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8956 - false_negatives_3: 139.8182 - false_positives_3: 160.8182 - loss: 0.2876
```  ```
- 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9181 - false_negatives_3: 128.5652 - false_positives_3: 131.2609 - loss: 0.2164 + 23/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8957 - false_negatives_3: 145.9130 - false_positives_3: 167.3913 - loss: 0.2872
```  ```
- 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9178 - false_negatives_3: 134.4167 - false_positives_3: 137.1667 - loss: 0.2171 + 24/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8959 - false_negatives_3: 151.6250 - false_positives_3: 174.1250 - loss: 0.2867
```  ```
- 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9175 - false_negatives_3: 140.2800 - false_positives_3: 143.1600 - loss: 0.2177 + 25/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8961 - false_negatives_3: 157.6000 - false_positives_3: 180.7200 - loss: 0.2863
```  ```
- 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9173 - false_negatives_3: 146.3077 - false_positives_3: 148.7308 - loss: 0.2182 + 26/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8963 - false_negatives_3: 163.4231 - false_positives_3: 187.3077 - loss: 0.2858
```  ```
- 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9171 - false_negatives_3: 152.2222 - false_positives_3: 154.5926 - loss: 0.2187 + 27/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8964 - false_negatives_3: 169.3704 - false_positives_3: 193.9630 - loss: 0.2854
```  ```
- 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9169 - false_negatives_3: 158.2857 - false_positives_3: 160.1786 - loss: 0.2191 + 28/98 ━━━━━━━━━━━━━━━━━━━━ 5s 72ms/step - binary_accuracy: 0.8966 - false_negatives_3: 175.3214 - false_positives_3: 200.5000 - loss: 0.2850
```  ```
- 29/98 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9168 - false_negatives_3: 164.0000 - false_positives_3: 165.9310 - loss: 0.2195 + 29/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8967 - false_negatives_3: 181.0345 - false_positives_3: 207.4483 - loss: 0.2848
```  ```
- 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9166 - false_negatives_3: 169.7333 - false_positives_3: 171.4333 - loss: 0.2198 + 30/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8968 - false_negatives_3: 187.3667 - false_positives_3: 214.0000 - loss: 0.2845
```  ```
- 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9165 - false_negatives_3: 175.2581 - false_positives_3: 176.9355 - loss: 0.2200 + 31/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8969 - false_negatives_3: 193.3871 - false_positives_3: 220.6452 - loss: 0.2841
```  ```
- 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9165 - false_negatives_3: 180.8125 - false_positives_3: 182.5000 - loss: 0.2203 + 32/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8970 - false_negatives_3: 199.5000 - false_positives_3: 227.2812 - loss: 0.2839
```  ```
- 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9164 - false_negatives_3: 186.3333 - false_positives_3: 187.9697 - loss: 0.2205 + 33/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8970 - false_negatives_3: 205.6364 - false_positives_3: 233.9091 - loss: 0.2836
```  ```
- 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9163 - false_negatives_3: 191.7353 - false_positives_3: 193.3824 - loss: 0.2207 + 34/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8971 - false_negatives_3: 211.6176 - false_positives_3: 240.6471 - loss: 0.2833
```  ```
- 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9163 - false_negatives_3: 197.2000 - false_positives_3: 198.7143 - loss: 0.2208 + 35/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8972 - false_negatives_3: 217.7143 - false_positives_3: 247.1429 - loss: 0.2831
```  ```
- 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 202.6111 - false_positives_3: 204.1389 - loss: 0.2210 + 36/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8973 - false_negatives_3: 223.7500 - false_positives_3: 253.7222 - loss: 0.2829
```  ```
- 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 208.1081 - false_positives_3: 209.5135 - loss: 0.2212 + 37/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8974 - false_negatives_3: 229.6487 - false_positives_3: 260.3243 - loss: 0.2826
```  ```
- 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 213.5000 - false_positives_3: 214.9211 - loss: 0.2214 + 38/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8975 - false_negatives_3: 235.5263 - false_positives_3: 266.8158 - loss: 0.2824
```  ```
- 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 218.9744 - false_positives_3: 220.1795 - loss: 0.2215 + 39/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8976 - false_negatives_3: 241.5385 - false_positives_3: 273.3590 - loss: 0.2821
```  ```
- 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 224.3000 - false_positives_3: 225.7000 - loss: 0.2217 + 40/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 247.3750 - false_positives_3: 279.9500 - loss: 0.2819
```  ```
- 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 229.9512 - false_positives_3: 231.0976 - loss: 0.2218 + 41/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 253.5610 - false_positives_3: 286.4634 - loss: 0.2817
```  ```
- 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 235.4048 - false_positives_3: 236.5238 - loss: 0.2220 + 42/98 ━━━━━━━━━━━━━━━━━━━━ 4s 72ms/step - binary_accuracy: 0.8978 - false_negatives_3: 259.6905 - false_positives_3: 293.0000 - loss: 0.2815
```  ```
- 43/98 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 240.9070 - false_positives_3: 241.7907 - loss: 0.2222 + 43/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8978 - false_negatives_3: 265.7675 - false_positives_3: 299.6977 - loss: 0.2813
```  ```
- 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 246.3182 - false_positives_3: 247.0909 - loss: 0.2223 + 44/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 272.0682 - false_positives_3: 306.2273 - loss: 0.2812
```  ```
- 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 251.8000 - false_positives_3: 252.3556 - loss: 0.2225 + 45/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 278.2889 - false_positives_3: 312.7778 - loss: 0.2811
```  ```
- 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 257.1522 - false_positives_3: 257.7391 - loss: 0.2226 + 46/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 284.4348 - false_positives_3: 319.1522 - loss: 0.2809
```  ```
- 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 262.7660 - false_positives_3: 263.0000 - loss: 0.2227 + 47/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 290.4681 - false_positives_3: 325.8085 - loss: 0.2807
```  ```
- 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 268.2292 - false_positives_3: 268.1875 - loss: 0.2229 + 48/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 296.7917 - false_positives_3: 332.3125 - loss: 0.2806
```  ```
- 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 273.7755 - false_positives_3: 273.2449 - loss: 0.2230 + 49/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8981 - false_negatives_3: 302.9184 - false_positives_3: 339.2449 - loss: 0.2805
```  ```
- 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 279.1400 - false_positives_3: 278.5200 - loss: 0.2231 + 50/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 309.2000 - false_positives_3: 346.1000 - loss: 0.2804
```  ```
- 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 284.5882 - false_positives_3: 283.6471 - loss: 0.2231 + 51/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 315.4510 - false_positives_3: 352.9216 - loss: 0.2803
```  ```
- 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 290.0192 - false_positives_3: 288.7885 - loss: 0.2232 + 52/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 321.8269 - false_positives_3: 359.7115 - loss: 0.2803
```  ```
- 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 295.3962 - false_positives_3: 293.8868 - loss: 0.2233 + 53/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 328.1509 - false_positives_3: 366.5094 - loss: 0.2802
```  ```
- 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 300.6296 - false_positives_3: 299.0000 - loss: 0.2234 + 54/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 334.4630 - false_positives_3: 373.2408 - loss: 0.2801
```  ```
- 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 306.0364 - false_positives_3: 304.0364 - loss: 0.2234 + 55/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 340.6909 - false_positives_3: 379.9455 - loss: 0.2800
```  ```
- 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 311.3571 - false_positives_3: 309.4821 - loss: 0.2235 + 56/98 ━━━━━━━━━━━━━━━━━━━━ 3s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 346.8214 - false_positives_3: 386.7321 - loss: 0.2799
```  ```
- 57/98 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 316.8246 - false_positives_3: 314.8596 - loss: 0.2236 + 57/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 352.9649 - false_positives_3: 393.3684 - loss: 0.2798
```  ```
- 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 322.2586 - false_positives_3: 320.2242 - loss: 0.2237 + 58/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 358.9828 - false_positives_3: 400.1897 - loss: 0.2797
```  ```
- 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 327.6610 - false_positives_3: 325.5932 - loss: 0.2239 + 59/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 365.2373 - false_positives_3: 406.7966 - loss: 0.2797
```  ```
- 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 333.0000 - false_positives_3: 330.9500 - loss: 0.2240 + 60/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 371.3333 - false_positives_3: 413.8333 - loss: 0.2797
```  ```
- 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 338.2623 - false_positives_3: 336.3279 - loss: 0.2241 + 61/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 377.5901 - false_positives_3: 420.8524 - loss: 0.2796
```  ```
- 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 343.5161 - false_positives_3: 341.6774 - loss: 0.2242 + 62/98 ━━━━━━━━━━━━━━━━━━━━ 2s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 383.7742 - false_positives_3: 427.9032 - loss: 0.2796
```  ```
- 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 348.7460 - false_positives_3: 346.9841 - loss: 0.2243 + 63/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 389.9206 - false_positives_3: 434.8889 - loss: 0.2796
```  ```
- 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 353.8906 - false_positives_3: 352.2969 - loss: 0.2243 + 64/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 395.9844 - false_positives_3: 441.8594 - loss: 0.2796
```  ```
- 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9159 - false_negatives_3: 358.9539 - false_positives_3: 357.5846 - loss: 0.2244 + 65/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 402.0923 - false_positives_3: 448.8154 - loss: 0.2796
```  ```
- 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 364.0454 - false_positives_3: 362.8485 - loss: 0.2245 + 66/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 408.0757 - false_positives_3: 455.7727 - loss: 0.2795
```  ```
- 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 369.1194 - false_positives_3: 368.1194 - loss: 0.2245 + 67/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 414.1791 - false_positives_3: 462.6119 - loss: 0.2795
```  ```
- 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 374.2059 - false_positives_3: 373.3529 - loss: 0.2246 + 68/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 420.1765 - false_positives_3: 469.5882 - loss: 0.2794
```  ```
- 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 379.3044 - false_positives_3: 378.5652 - loss: 0.2246 + 69/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 426.4058 - false_positives_3: 476.4638 - loss: 0.2794
```  ```
- 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 384.4286 - false_positives_3: 383.7000 - loss: 0.2247 + 70/98 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 432.5286 - false_positives_3: 483.5857 - loss: 0.2794
```  ```
- 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 389.5211 - false_positives_3: 388.8169 - loss: 0.2248 + 71/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 438.8451 - false_positives_3: 490.6620 - loss: 0.2795
```  ```
- 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 394.6528 - false_positives_3: 393.9167 - loss: 0.2248 + 72/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8983 - false_negatives_3: 445.1111 - false_positives_3: 497.7917 - loss: 0.2795
```  ```
- 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 399.6849 - false_positives_3: 399.1918 - loss: 0.2249 + 73/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 451.3151 - false_positives_3: 504.9863 - loss: 0.2795
```  ```
- 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 404.9595 - false_positives_3: 404.3649 - loss: 0.2249 + 74/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 457.6351 - false_positives_3: 512.0946 - loss: 0.2795
```  ```
- 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 410.1200 - false_positives_3: 409.7867 - loss: 0.2250 + 75/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 463.9067 - false_positives_3: 519.2667 - loss: 0.2796
```  ```
- 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 415.2500 - false_positives_3: 415.1711 - loss: 0.2251 + 76/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8982 - false_negatives_3: 470.1842 - false_positives_3: 526.4474 - loss: 0.2796
```  ```
- 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 420.3506 - false_positives_3: 420.5714 - loss: 0.2252 + 77/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 476.3377 - false_positives_3: 533.7792 - loss: 0.2796
```  ```
- 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 425.5641 - false_positives_3: 425.8974 - loss: 0.2252 + 78/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8982 - false_negatives_3: 482.5385 - false_positives_3: 541.0513 - loss: 0.2797
```  ```
- 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 430.7089 - false_positives_3: 431.3544 - loss: 0.2253 + 79/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8981 - false_negatives_3: 488.6709 - false_positives_3: 548.3671 - loss: 0.2797
```  ```
- 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 435.9875 - false_positives_3: 436.7625 - loss: 0.2254 + 80/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.8981 - false_negatives_3: 495.0250 - false_positives_3: 555.5875 - loss: 0.2797
```  ```
- 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 441.2469 - false_positives_3: 442.2469 - loss: 0.2255 + 81/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8981 - false_negatives_3: 501.3951 - false_positives_3: 562.9383 - loss: 0.2798
```  ```
- 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9162 - false_negatives_3: 446.5976 - false_positives_3: 447.6951 - loss: 0.2256 + 82/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8981 - false_negatives_3: 507.8171 - false_positives_3: 570.3049 - loss: 0.2798
```  ```
- 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 451.9518 - false_positives_3: 453.1446 - loss: 0.2257 + 83/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 514.2530 - false_positives_3: 577.6627 - loss: 0.2799
```  ```
- 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 457.2738 - false_positives_3: 458.5833 - loss: 0.2258 + 84/98 ━━━━━━━━━━━━━━━━━━━━ 1s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 520.5952 - false_positives_3: 585.0476 - loss: 0.2799
```  ```
- 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 462.6118 - false_positives_3: 464.0235 - loss: 0.2258 + 85/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8980 - false_negatives_3: 526.9882 - false_positives_3: 592.3765 - loss: 0.2799
```  ```
- 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 467.8954 - false_positives_3: 469.4186 - loss: 0.2259 + 86/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 533.3372 - false_positives_3: 599.6977 - loss: 0.2800
```  ```
- 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 473.2989 - false_positives_3: 474.7701 - loss: 0.2260 + 87/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 539.8046 - false_positives_3: 606.9770 - loss: 0.2800
```  ```
- 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 478.6136 - false_positives_3: 480.3182 - loss: 0.2261 + 88/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8979 - false_negatives_3: 546.1932 - false_positives_3: 614.3750 - loss: 0.2801
```  ```
- 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 484.0786 - false_positives_3: 485.7753 - loss: 0.2262 + 89/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8978 - false_negatives_3: 552.6517 - false_positives_3: 621.7528 - loss: 0.2801
```  ```
- 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 489.4667 - false_positives_3: 491.3333 - loss: 0.2263 + 90/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8978 - false_negatives_3: 559.0778 - false_positives_3: 629.2111 - loss: 0.2801
```  ```
- 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 494.8352 - false_positives_3: 496.8901 - loss: 0.2263 + 91/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8978 - false_negatives_3: 565.7033 - false_positives_3: 636.5934 - loss: 0.2802
```  ```
- 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 500.2391 - false_positives_3: 502.4456 - loss: 0.2264 + 92/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8977 - false_negatives_3: 572.2609 - false_positives_3: 644.0978 - loss: 0.2803
```  ```
- 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 505.6344 - false_positives_3: 508.0215 - loss: 0.2265 + 93/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8977 - false_negatives_3: 579.0323 - false_positives_3: 651.5377 - loss: 0.2803
```  ```
- 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 511.0532 - false_positives_3: 513.5532 - loss: 0.2266 + 94/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8976 - false_negatives_3: 585.7341 - false_positives_3: 659.1277 - loss: 0.2804
```  ```
- 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9161 - false_negatives_3: 516.4737 - false_positives_3: 519.2000 - loss: 0.2267 + 95/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8976 - false_negatives_3: 592.4000 - false_positives_3: 666.6421 - loss: 0.2805
```  ```
- 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 521.9792 - false_positives_3: 524.7708 - loss: 0.2268 + 96/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8976 - false_negatives_3: 598.9792 - false_positives_3: 674.1146 - loss: 0.2805
```  ```
- 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 527.4020 - false_positives_3: 530.4124 - loss: 0.2269 + 97/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.8975 - false_negatives_3: 605.5773 - false_positives_3: 681.5567 - loss: 0.2806
```  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9160 - false_negatives_3: 532.8674 - false_positives_3: 535.9592 - loss: 0.2270 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 0s 72ms/step - binary_accuracy: 0.8975 - false_negatives_3: 612.0714 - false_positives_3: 688.9184 - loss: 0.2806
``` -Epoch 6: val_loss did not improve from 0.34519 +Epoch 5: val_loss did not improve from 0.36196  ```
- 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 80ms/step - binary_accuracy: 0.9160 - false_negatives_3: 538.2222 - false_positives_3: 541.3939 - loss: 0.2270 - val_binary_accuracy: 0.8432 - val_false_negatives_3: 215.0000 - val_false_positives_3: 569.0000 - val_loss: 0.3991 + 98/98 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8974 - false_negatives_3: 618.4343 - false_positives_3: 696.1313 - loss: 0.2807 - val_binary_accuracy: 0.8456 - val_false_negatives_3: 446.0000 - val_false_positives_3: 326.0000 - val_loss: 0.3658
``` -Epoch 6: early stopping +Epoch 5: early stopping ```
- 1/20 ━━━━━━━━━━━━━━━━━━━━ 4s 263ms/step + 1/20 ━━━━━━━━━━━━━━━━━━━━ 9s 489ms/step
``` @@ -27762,28 +26811,28 @@ Epoch 6: early stopping  ```
- 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 7/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
```  ```
- 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 9/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
```  ```
- 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 11/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
```  ```
- 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 30ms/step + 13/20 ━━━━━━━━━━━━━━━━━━━━ 0s 31ms/step
``` @@ -27811,21 +26860,21 @@ Epoch 6: early stopping  ```
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 39ms/step + 20/20 ━━━━━━━━━━━━━━━━━━━━ 0s 40ms/step
```  ```
- 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 39ms/step + 20/20 ━━━━━━━━━━━━━━━━━━━━ 1s 40ms/step
``` ---------------------------------------------------------------------------------------------------- -Number of zeros incorrectly classified: 349.0, Number of ones incorrectly classified: 393.0 -Sample ratio for positives: 0.5296495956873315, Sample ratio for negatives:0.47035040431266845 +Number of zeros incorrectly classified: 407.0, Number of ones incorrectly classified: 410.0 +Sample ratio for positives: 0.5018359853121175, Sample ratio for negatives:0.4981640146878825 Starting training with 29997 samples ---------------------------------------------------------------------------------------------------- Epoch 1/20 @@ -27833,829 +26882,829 @@ Epoch 1/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 5:53 3s/step - binary_accuracy: 0.9414 - false_negatives_4: 9.0000 - false_positives_4: 6.0000 - loss: 0.2306 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 5:36 3s/step - binary_accuracy: 0.9297 - false_negatives_4: 5.0000 - false_positives_4: 13.0000 - loss: 0.2644
``` - + ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9326 - false_negatives_4: 19.0000 - false_positives_4: 8.0000 - loss: 0.2360 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9238 - false_negatives_4: 13.0000 - false_positives_4: 17.0000 - loss: 0.2729
``` - + ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.8939 - false_negatives_4: 22.3333 - false_positives_4: 42.6667 - loss: 0.3502 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9036 - false_negatives_4: 16.0000 - false_positives_4: 39.0000 - loss: 0.3096
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8706 - false_negatives_4: 38.7500 - false_positives_4: 61.0000 - loss: 0.4030 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.8818 - false_negatives_4: 37.7500 - false_positives_4: 50.5000 - loss: 0.3489
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8605 - false_negatives_4: 53.0000 - false_positives_4: 72.8000 - loss: 0.4232 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.8691 - false_negatives_4: 51.6000 - false_positives_4: 65.6000 - loss: 0.3693
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8562 - false_negatives_4: 65.1667 - false_positives_4: 82.0000 - loss: 0.4306 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8616 - false_negatives_4: 62.6667 - false_positives_4: 80.0000 - loss: 0.3793
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8542 - false_negatives_4: 75.2857 - false_positives_4: 91.2857 - loss: 0.4323 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 9s 82ms/step - binary_accuracy: 0.8566 - false_negatives_4: 72.8571 - false_positives_4: 93.7143 - loss: 0.3864
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8535 - false_negatives_4: 84.6250 - false_positives_4: 99.8750 - loss: 0.4318 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 81ms/step - binary_accuracy: 0.8533 - false_negatives_4: 82.7500 - false_positives_4: 106.5000 - loss: 0.3904
``` - + ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 78ms/step - binary_accuracy: 0.8536 - false_negatives_4: 93.2222 - false_positives_4: 108.0000 - loss: 0.4299 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 81ms/step - binary_accuracy: 0.8514 - false_negatives_4: 91.8889 - false_positives_4: 118.3333 - loss: 0.3924
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 78ms/step - binary_accuracy: 0.8544 - false_negatives_4: 101.0000 - false_positives_4: 115.5000 - loss: 0.4266 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 80ms/step - binary_accuracy: 0.8506 - false_negatives_4: 100.0000 - false_positives_4: 129.3000 - loss: 0.3923
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 8s 78ms/step - binary_accuracy: 0.8554 - false_negatives_4: 108.6364 - false_positives_4: 122.6364 - loss: 0.4227 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8499 - false_negatives_4: 108.5455 - false_positives_4: 140.0909 - loss: 0.3919
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 8s 78ms/step - binary_accuracy: 0.8561 - false_negatives_4: 116.2500 - false_positives_4: 130.5833 - loss: 0.4191 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8494 - false_negatives_4: 117.0833 - false_positives_4: 150.7500 - loss: 0.3913
```  ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.8569 - false_negatives_4: 124.2308 - false_positives_4: 137.9231 - loss: 0.4154 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8493 - false_negatives_4: 125.3846 - false_positives_4: 160.9231 - loss: 0.3902
```  ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.8577 - false_negatives_4: 131.9286 - false_positives_4: 145.3571 - loss: 0.4118 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8492 - false_negatives_4: 133.7143 - false_positives_4: 170.7857 - loss: 0.3892
```  ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.8584 - false_negatives_4: 139.7333 - false_positives_4: 152.7333 - loss: 0.4084 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 8s 79ms/step - binary_accuracy: 0.8493 - false_negatives_4: 141.8000 - false_positives_4: 180.6000 - loss: 0.3880
```  ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.8592 - false_negatives_4: 147.2500 - false_positives_4: 159.7500 - loss: 0.4049 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 78ms/step - binary_accuracy: 0.8496 - false_negatives_4: 149.3750 - false_positives_4: 190.5625 - loss: 0.3868
```  ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.8601 - false_negatives_4: 154.4706 - false_positives_4: 166.5882 - loss: 0.4014 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 78ms/step - binary_accuracy: 0.8498 - false_negatives_4: 157.2353 - false_positives_4: 200.1765 - loss: 0.3856
```  ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.8610 - false_negatives_4: 161.6111 - false_positives_4: 173.2222 - loss: 0.3983 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 78ms/step - binary_accuracy: 0.8500 - false_negatives_4: 165.1111 - false_positives_4: 209.9444 - loss: 0.3845
```  ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.8620 - false_negatives_4: 168.3158 - false_positives_4: 180.0000 - loss: 0.3951 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8503 - false_negatives_4: 172.7895 - false_positives_4: 219.5789 - loss: 0.3833
```  ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8629 - false_negatives_4: 174.9000 - false_positives_4: 186.7500 - loss: 0.3920 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8506 - false_negatives_4: 180.4000 - false_positives_4: 229.0000 - loss: 0.3821
```  ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8637 - false_negatives_4: 181.4762 - false_positives_4: 193.6190 - loss: 0.3892 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8510 - false_negatives_4: 188.0952 - false_positives_4: 238.1905 - loss: 0.3809
```  ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8645 - false_negatives_4: 187.8182 - false_positives_4: 200.2727 - loss: 0.3865 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8512 - false_negatives_4: 196.1364 - false_positives_4: 247.3182 - loss: 0.3799
```  ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8654 - false_negatives_4: 194.1304 - false_positives_4: 207.0000 - loss: 0.3839 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8515 - false_negatives_4: 203.7826 - false_positives_4: 256.8261 - loss: 0.3788
```  ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8661 - false_negatives_4: 200.2083 - false_positives_4: 213.8750 - loss: 0.3814 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8518 - false_negatives_4: 211.4167 - false_positives_4: 266.0833 - loss: 0.3778
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8669 - false_negatives_4: 206.4000 - false_positives_4: 220.6000 - loss: 0.3789 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 7s 79ms/step - binary_accuracy: 0.8522 - false_negatives_4: 218.7200 - false_positives_4: 275.5200 - loss: 0.3768
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8676 - false_negatives_4: 212.5385 - false_positives_4: 227.4615 - loss: 0.3766 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8525 - false_negatives_4: 226.3077 - false_positives_4: 284.8462 - loss: 0.3759
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8683 - false_negatives_4: 218.6667 - false_positives_4: 234.2593 - loss: 0.3744 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8527 - false_negatives_4: 233.7037 - false_positives_4: 294.5555 - loss: 0.3750
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8688 - false_negatives_4: 224.9643 - false_positives_4: 241.5357 - loss: 0.3725 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 7s 81ms/step - binary_accuracy: 0.8530 - false_negatives_4: 241.2500 - false_positives_4: 303.8214 - loss: 0.3742
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8693 - false_negatives_4: 231.2759 - false_positives_4: 248.8276 - loss: 0.3708 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 7s 81ms/step - binary_accuracy: 0.8533 - false_negatives_4: 248.6897 - false_positives_4: 313.0000 - loss: 0.3734
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8698 - false_negatives_4: 237.9000 - false_positives_4: 255.9000 - loss: 0.3691 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 7s 80ms/step - binary_accuracy: 0.8536 - false_negatives_4: 256.3333 - false_positives_4: 322.0333 - loss: 0.3727
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8703 - false_negatives_4: 244.2581 - false_positives_4: 263.3226 - loss: 0.3675 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8539 - false_negatives_4: 263.8710 - false_positives_4: 331.0645 - loss: 0.3720
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8707 - false_negatives_4: 251.0938 - false_positives_4: 270.4375 - loss: 0.3661 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8541 - false_negatives_4: 271.5000 - false_positives_4: 339.8438 - loss: 0.3713
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8711 - false_negatives_4: 257.6970 - false_positives_4: 277.8788 - loss: 0.3648 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8545 - false_negatives_4: 279.0000 - false_positives_4: 348.5151 - loss: 0.3706
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8714 - false_negatives_4: 264.3235 - false_positives_4: 285.3529 - loss: 0.3634 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8547 - false_negatives_4: 286.4118 - false_positives_4: 357.4118 - loss: 0.3700
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8718 - false_negatives_4: 270.8857 - false_positives_4: 292.8000 - loss: 0.3622 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 80ms/step - binary_accuracy: 0.8550 - false_negatives_4: 294.2857 - false_positives_4: 366.0286 - loss: 0.3695
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8721 - false_negatives_4: 277.6111 - false_positives_4: 300.1389 - loss: 0.3610 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8552 - false_negatives_4: 301.9445 - false_positives_4: 374.8889 - loss: 0.3689
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8724 - false_negatives_4: 284.1081 - false_positives_4: 307.8919 - loss: 0.3599 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8555 - false_negatives_4: 309.8919 - false_positives_4: 383.6757 - loss: 0.3684
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8728 - false_negatives_4: 290.6579 - false_positives_4: 315.3947 - loss: 0.3589 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8557 - false_negatives_4: 317.7895 - false_positives_4: 392.5789 - loss: 0.3679
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8730 - false_negatives_4: 297.2051 - false_positives_4: 323.0513 - loss: 0.3579 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8559 - false_negatives_4: 325.8462 - false_positives_4: 401.3590 - loss: 0.3675
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8733 - false_negatives_4: 303.6750 - false_positives_4: 330.7250 - loss: 0.3569 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8560 - false_negatives_4: 333.8000 - false_positives_4: 410.1500 - loss: 0.3670
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 6s 78ms/step - binary_accuracy: 0.8736 - false_negatives_4: 310.0244 - false_positives_4: 338.2927 - loss: 0.3559 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 6s 79ms/step - binary_accuracy: 0.8562 - false_negatives_4: 341.6342 - false_positives_4: 419.0488 - loss: 0.3666
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8739 - false_negatives_4: 316.4524 - false_positives_4: 345.6429 - loss: 0.3549 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 79ms/step - binary_accuracy: 0.8564 - false_negatives_4: 349.4048 - false_positives_4: 427.8095 - loss: 0.3662
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8742 - false_negatives_4: 322.7209 - false_positives_4: 353.2093 - loss: 0.3540 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 79ms/step - binary_accuracy: 0.8566 - false_negatives_4: 357.0698 - false_positives_4: 436.4651 - loss: 0.3657
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8744 - false_negatives_4: 329.2273 - false_positives_4: 360.7273 - loss: 0.3532 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 79ms/step - binary_accuracy: 0.8569 - false_negatives_4: 364.6136 - false_positives_4: 445.2046 - loss: 0.3653
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8747 - false_negatives_4: 335.6222 - false_positives_4: 368.3333 - loss: 0.3524 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 79ms/step - binary_accuracy: 0.8571 - false_negatives_4: 372.1111 - false_positives_4: 453.8222 - loss: 0.3648
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8749 - false_negatives_4: 342.1956 - false_positives_4: 375.8913 - loss: 0.3516 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 79ms/step - binary_accuracy: 0.8573 - false_negatives_4: 379.4565 - false_positives_4: 462.5652 - loss: 0.3643
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8751 - false_negatives_4: 348.7660 - false_positives_4: 383.4681 - loss: 0.3509 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8575 - false_negatives_4: 386.9787 - false_positives_4: 471.2128 - loss: 0.3639
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8753 - false_negatives_4: 355.5417 - false_positives_4: 390.8333 - loss: 0.3502 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8577 - false_negatives_4: 394.2917 - false_positives_4: 480.2917 - loss: 0.3635
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8755 - false_negatives_4: 362.2041 - false_positives_4: 398.4694 - loss: 0.3495 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8578 - false_negatives_4: 402.4286 - false_positives_4: 489.0612 - loss: 0.3632
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8757 - false_negatives_4: 369.0000 - false_positives_4: 406.0200 - loss: 0.3488 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8579 - false_negatives_4: 410.3000 - false_positives_4: 498.1400 - loss: 0.3629
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8759 - false_negatives_4: 375.6863 - false_positives_4: 413.6667 - loss: 0.3482 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8581 - false_negatives_4: 418.1373 - false_positives_4: 507.2549 - loss: 0.3626
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8760 - false_negatives_4: 382.4038 - false_positives_4: 421.1923 - loss: 0.3476 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8582 - false_negatives_4: 425.9038 - false_positives_4: 516.3846 - loss: 0.3622
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 5s 77ms/step - binary_accuracy: 0.8762 - false_negatives_4: 389.0943 - false_positives_4: 428.8868 - loss: 0.3470 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 5s 78ms/step - binary_accuracy: 0.8583 - false_negatives_4: 433.6415 - false_positives_4: 525.2830 - loss: 0.3619
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8763 - false_negatives_4: 395.9259 - false_positives_4: 436.6111 - loss: 0.3465 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8585 - false_negatives_4: 441.2963 - false_positives_4: 534.2778 - loss: 0.3616
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8765 - false_negatives_4: 402.8546 - false_positives_4: 444.3273 - loss: 0.3459 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8586 - false_negatives_4: 449.1636 - false_positives_4: 543.1454 - loss: 0.3613
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8766 - false_negatives_4: 409.8214 - false_positives_4: 451.9821 - loss: 0.3454 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8587 - false_negatives_4: 457.0357 - false_positives_4: 552.3393 - loss: 0.3610
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8767 - false_negatives_4: 416.6842 - false_positives_4: 459.7368 - loss: 0.3449 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8588 - false_negatives_4: 464.8596 - false_positives_4: 561.6140 - loss: 0.3608
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8769 - false_negatives_4: 423.6897 - false_positives_4: 467.4828 - loss: 0.3444 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8589 - false_negatives_4: 472.5862 - false_positives_4: 570.9655 - loss: 0.3605
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8770 - false_negatives_4: 430.6102 - false_positives_4: 475.2712 - loss: 0.3439 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 78ms/step - binary_accuracy: 0.8590 - false_negatives_4: 480.1526 - false_positives_4: 580.3220 - loss: 0.3603
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8771 - false_negatives_4: 437.5000 - false_positives_4: 483.2000 - loss: 0.3435 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8591 - false_negatives_4: 487.7167 - false_positives_4: 589.6833 - loss: 0.3600
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8772 - false_negatives_4: 444.5574 - false_positives_4: 491.0164 - loss: 0.3431 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8592 - false_negatives_4: 495.2459 - false_positives_4: 599.0328 - loss: 0.3598
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.8773 - false_negatives_4: 451.5161 - false_positives_4: 498.9355 - loss: 0.3427 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8593 - false_negatives_4: 502.8548 - false_positives_4: 608.3710 - loss: 0.3595
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.8773 - false_negatives_4: 458.6032 - false_positives_4: 506.8889 - loss: 0.3423 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8594 - false_negatives_4: 510.4445 - false_positives_4: 617.6667 - loss: 0.3593
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.8774 - false_negatives_4: 465.6719 - false_positives_4: 514.8281 - loss: 0.3419 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8594 - false_negatives_4: 517.9219 - false_positives_4: 627.0938 - loss: 0.3591
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.8775 - false_negatives_4: 472.6923 - false_positives_4: 522.7385 - loss: 0.3416 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8595 - false_negatives_4: 525.5846 - false_positives_4: 636.3538 - loss: 0.3588
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8776 - false_negatives_4: 479.6515 - false_positives_4: 530.5606 - loss: 0.3412 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 4s 77ms/step - binary_accuracy: 0.8596 - false_negatives_4: 533.0151 - false_positives_4: 646.0000 - loss: 0.3587
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8777 - false_negatives_4: 486.4776 - false_positives_4: 538.4478 - loss: 0.3408 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8597 - false_negatives_4: 540.7612 - false_positives_4: 655.4329 - loss: 0.3585
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8778 - false_negatives_4: 493.4118 - false_positives_4: 546.3823 - loss: 0.3404 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8597 - false_negatives_4: 548.3970 - false_positives_4: 664.8970 - loss: 0.3583
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8778 - false_negatives_4: 500.4638 - false_positives_4: 554.2899 - loss: 0.3401 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8598 - false_negatives_4: 556.0145 - false_positives_4: 674.3913 - loss: 0.3582
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8779 - false_negatives_4: 507.4286 - false_positives_4: 562.3571 - loss: 0.3398 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8599 - false_negatives_4: 563.5714 - false_positives_4: 683.9000 - loss: 0.3580
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8779 - false_negatives_4: 514.6620 - false_positives_4: 570.3662 - loss: 0.3394 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8599 - false_negatives_4: 571.1972 - false_positives_4: 693.3803 - loss: 0.3579
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8780 - false_negatives_4: 521.7778 - false_positives_4: 578.5417 - loss: 0.3391 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8600 - false_negatives_4: 578.6528 - false_positives_4: 703.0278 - loss: 0.3577
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8780 - false_negatives_4: 528.9178 - false_positives_4: 586.6712 - loss: 0.3389 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8601 - false_negatives_4: 586.1781 - false_positives_4: 712.4794 - loss: 0.3575
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8781 - false_negatives_4: 536.0676 - false_positives_4: 594.8243 - loss: 0.3386 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8602 - false_negatives_4: 593.6757 - false_positives_4: 721.9054 - loss: 0.3574
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8781 - false_negatives_4: 543.0933 - false_positives_4: 602.9467 - loss: 0.3383 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8602 - false_negatives_4: 601.1733 - false_positives_4: 731.3867 - loss: 0.3572
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8782 - false_negatives_4: 550.0921 - false_positives_4: 611.0526 - loss: 0.3380 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8603 - false_negatives_4: 608.6579 - false_positives_4: 740.7895 - loss: 0.3570
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8782 - false_negatives_4: 557.0389 - false_positives_4: 619.2078 - loss: 0.3377 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8604 - false_negatives_4: 616.0909 - false_positives_4: 750.3117 - loss: 0.3569
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8783 - false_negatives_4: 564.1667 - false_positives_4: 627.2564 - loss: 0.3374 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 77ms/step - binary_accuracy: 0.8604 - false_negatives_4: 623.7051 - false_positives_4: 759.7051 - loss: 0.3567
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8783 - false_negatives_4: 571.2405 - false_positives_4: 635.4937 - loss: 0.3372 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8605 - false_negatives_4: 631.2658 - false_positives_4: 769.2658 - loss: 0.3566
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8784 - false_negatives_4: 578.4000 - false_positives_4: 643.6125 - loss: 0.3369 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8605 - false_negatives_4: 638.7500 - false_positives_4: 778.8125 - loss: 0.3565
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8784 - false_negatives_4: 585.5309 - false_positives_4: 651.7161 - loss: 0.3367 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8606 - false_negatives_4: 646.2839 - false_positives_4: 788.3087 - loss: 0.3563
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8784 - false_negatives_4: 592.5854 - false_positives_4: 659.7195 - loss: 0.3364 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8606 - false_negatives_4: 653.6951 - false_positives_4: 797.9025 - loss: 0.3562
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8785 - false_negatives_4: 599.5903 - false_positives_4: 667.7952 - loss: 0.3361 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8607 - false_negatives_4: 661.2651 - false_positives_4: 807.4337 - loss: 0.3560
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8785 - false_negatives_4: 606.6667 - false_positives_4: 675.8095 - loss: 0.3359 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8607 - false_negatives_4: 668.7738 - false_positives_4: 817.0119 - loss: 0.3559
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8786 - false_negatives_4: 613.7411 - false_positives_4: 683.8353 - loss: 0.3357 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8608 - false_negatives_4: 676.3176 - false_positives_4: 826.5176 - loss: 0.3558
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8786 - false_negatives_4: 620.8488 - false_positives_4: 691.8605 - loss: 0.3354 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8608 - false_negatives_4: 683.8488 - false_positives_4: 835.9883 - loss: 0.3556
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8787 - false_negatives_4: 627.9196 - false_positives_4: 699.9885 - loss: 0.3352 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8609 - false_negatives_4: 691.2988 - false_positives_4: 845.5632 - loss: 0.3555
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8787 - false_negatives_4: 635.1705 - false_positives_4: 708.0568 - loss: 0.3350 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8609 - false_negatives_4: 698.8182 - false_positives_4: 855.0227 - loss: 0.3554
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8787 - false_negatives_4: 642.3371 - false_positives_4: 716.0899 - loss: 0.3347 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8610 - false_negatives_4: 706.3371 - false_positives_4: 864.6068 - loss: 0.3553
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8788 - false_negatives_4: 649.4333 - false_positives_4: 724.1667 - loss: 0.3345 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8610 - false_negatives_4: 713.8222 - false_positives_4: 874.2111 - loss: 0.3552
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8788 - false_negatives_4: 656.4945 - false_positives_4: 732.2308 - loss: 0.3343 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 77ms/step - binary_accuracy: 0.8611 - false_negatives_4: 721.3077 - false_positives_4: 883.7582 - loss: 0.3551
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8788 - false_negatives_4: 663.5435 - false_positives_4: 740.3587 - loss: 0.3341 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8611 - false_negatives_4: 728.7609 - false_positives_4: 893.3043 - loss: 0.3550
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 670.5806 - false_positives_4: 748.4301 - loss: 0.3339 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8612 - false_negatives_4: 736.2258 - false_positives_4: 902.8387 - loss: 0.3549
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 677.6064 - false_positives_4: 756.5532 - loss: 0.3337 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8612 - false_negatives_4: 743.6489 - false_positives_4: 912.3085 - loss: 0.3547
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 684.6421 - false_positives_4: 764.6526 - loss: 0.3334 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8613 - false_negatives_4: 751.0737 - false_positives_4: 921.8527 - loss: 0.3546
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 691.6458 - false_positives_4: 772.7500 - loss: 0.3332 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8613 - false_negatives_4: 758.5625 - false_positives_4: 931.2917 - loss: 0.3545
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8790 - false_negatives_4: 698.6907 - false_positives_4: 780.7938 - loss: 0.3330 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8614 - false_negatives_4: 766.0206 - false_positives_4: 940.7938 - loss: 0.3544
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8790 - false_negatives_4: 705.6837 - false_positives_4: 788.8571 - loss: 0.3328 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 77ms/step - binary_accuracy: 0.8614 - false_negatives_4: 773.5000 - false_positives_4: 950.2857 - loss: 0.3543
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8790 - false_negatives_4: 712.6869 - false_positives_4: 796.8384 - loss: 0.3326 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8615 - false_negatives_4: 780.9495 - false_positives_4: 959.8485 - loss: 0.3542
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8791 - false_negatives_4: 719.6200 - false_positives_4: 804.8900 - loss: 0.3324 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8615 - false_negatives_4: 788.4500 - false_positives_4: 969.3300 - loss: 0.3541
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8791 - false_negatives_4: 726.6337 - false_positives_4: 812.8317 - loss: 0.3322 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8615 - false_negatives_4: 795.8614 - false_positives_4: 978.9109 - loss: 0.3540
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8792 - false_negatives_4: 733.5686 - false_positives_4: 820.8333 - loss: 0.3320 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8616 - false_negatives_4: 803.4706 - false_positives_4: 988.3530 - loss: 0.3539
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8792 - false_negatives_4: 740.5534 - false_positives_4: 828.7961 - loss: 0.3318 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8616 - false_negatives_4: 811.0097 - false_positives_4: 997.8738 - loss: 0.3539
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8792 - false_negatives_4: 747.4808 - false_positives_4: 836.8558 - loss: 0.3316 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8617 - false_negatives_4: 818.5192 - false_positives_4: 1007.3846 - loss: 0.3538
``` - + ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8793 - false_negatives_4: 754.3619 - false_positives_4: 844.8666 - loss: 0.3314 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8617 - false_negatives_4: 826.0571 - false_positives_4: 1016.9048 - loss: 0.3537
``` - + ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8793 - false_negatives_4: 761.2453 - false_positives_4: 852.8868 - loss: 0.3312 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8617 - false_negatives_4: 833.5472 - false_positives_4: 1026.4623 - loss: 0.3536
``` - + ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8793 - false_negatives_4: 768.1963 - false_positives_4: 860.8411 - loss: 0.3310 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8618 - false_negatives_4: 841.0468 - false_positives_4: 1036.0374 - loss: 0.3535
``` - + ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8794 - false_negatives_4: 775.0833 - false_positives_4: 868.7870 - loss: 0.3308 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8618 - false_negatives_4: 848.5278 - false_positives_4: 1045.5927 - loss: 0.3534
``` - + ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8794 - false_negatives_4: 781.9908 - false_positives_4: 876.6789 - loss: 0.3306 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8618 - false_negatives_4: 856.0000 - false_positives_4: 1055.0918 - loss: 0.3533
``` - + ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8794 - false_negatives_4: 788.8000 - false_positives_4: 884.6454 - loss: 0.3304 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8619 - false_negatives_4: 863.4636 - false_positives_4: 1064.5364 - loss: 0.3532
``` - + ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8795 - false_negatives_4: 795.7207 - false_positives_4: 892.5135 - loss: 0.3303 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8619 - false_negatives_4: 870.9009 - false_positives_4: 1073.9369 - loss: 0.3532
``` - + ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8795 - false_negatives_4: 802.5714 - false_positives_4: 900.5089 - loss: 0.3301 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8619 - false_negatives_4: 878.2768 - false_positives_4: 1083.4108 - loss: 0.3531
``` - + ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8795 - false_negatives_4: 809.4248 - false_positives_4: 908.5044 - loss: 0.3299 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8620 - false_negatives_4: 885.8141 - false_positives_4: 1092.7699 - loss: 0.3530
``` - + ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8796 - false_negatives_4: 816.2544 - false_positives_4: 916.5175 - loss: 0.3297 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8620 - false_negatives_4: 893.3246 - false_positives_4: 1102.2982 - loss: 0.3529
``` - + ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8796 - false_negatives_4: 823.0435 - false_positives_4: 924.4869 - loss: 0.3295 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8620 - false_negatives_4: 900.9826 - false_positives_4: 1111.8608 - loss: 0.3528
``` - + ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8796 - false_negatives_4: 829.8707 - false_positives_4: 932.4396 - loss: 0.3294 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8621 - false_negatives_4: 908.6207 - false_positives_4: 1121.3966 - loss: 0.3527
``` - + ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 75ms/step - binary_accuracy: 0.8797 - false_negatives_4: 836.6496 - false_positives_4: 940.4188 - loss: 0.3292 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8621 - false_negatives_4: 916.2393 - false_positives_4: 1130.9744 - loss: 0.3527
``` -Epoch 1: val_loss did not improve from 0.34519 +Epoch 1: val_loss did not improve from 0.36196 - + ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 13s 83ms/step - binary_accuracy: 0.8797 - false_negatives_4: 849.9664 - false_positives_4: 955.9916 - loss: 0.3288 - val_binary_accuracy: 0.8452 - val_false_negatives_4: 181.0000 - val_false_positives_4: 593.0000 - val_loss: 0.3705 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 13s 85ms/step - binary_accuracy: 0.8621 - false_negatives_4: 931.0924 - false_positives_4: 1149.7479 - loss: 0.3525 - val_binary_accuracy: 0.8266 - val_false_negatives_4: 627.0000 - val_false_positives_4: 240.0000 - val_loss: 0.3802
@@ -28665,829 +27714,829 @@ Epoch 2/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 94ms/step - binary_accuracy: 0.8750 - false_negatives_4: 4.0000 - false_positives_4: 28.0000 - loss: 0.2734 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 96ms/step - binary_accuracy: 0.8789 - false_negatives_4: 25.0000 - false_positives_4: 6.0000 - loss: 0.3237
```  ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8779 - false_negatives_4: 15.0000 - false_positives_4: 31.5000 - loss: 0.2874 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8779 - false_negatives_4: 30.0000 - false_positives_4: 17.0000 - loss: 0.3221
```  ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8852 - false_negatives_4: 20.6667 - false_positives_4: 36.0000 - loss: 0.2827 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8826 - false_negatives_4: 35.3333 - false_positives_4: 23.6667 - loss: 0.3148
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8907 - false_negatives_4: 25.5000 - false_positives_4: 40.7500 - loss: 0.2804 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8831 - false_negatives_4: 40.2500 - false_positives_4: 33.5000 - loss: 0.3142
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8944 - false_negatives_4: 29.8000 - false_positives_4: 46.4000 - loss: 0.2769 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8820 - false_negatives_4: 50.0000 - false_positives_4: 40.4000 - loss: 0.3143
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8971 - false_negatives_4: 35.5000 - false_positives_4: 51.0000 - loss: 0.2745 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8797 - false_negatives_4: 57.5000 - false_positives_4: 51.5000 - loss: 0.3174
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8991 - false_negatives_4: 40.8571 - false_positives_4: 56.0000 - loss: 0.2725 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 65.4286 - false_positives_4: 60.2857 - loss: 0.3184
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9000 - false_negatives_4: 47.3750 - false_positives_4: 61.2500 - loss: 0.2720 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8788 - false_negatives_4: 72.3750 - false_positives_4: 68.8750 - loss: 0.3183
```  ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9008 - false_negatives_4: 53.0000 - false_positives_4: 67.4444 - loss: 0.2716 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8789 - false_negatives_4: 79.5556 - false_positives_4: 76.6667 - loss: 0.3175
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9014 - false_negatives_4: 59.4000 - false_positives_4: 72.9000 - loss: 0.2711 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8787 - false_negatives_4: 86.6000 - false_positives_4: 85.7000 - loss: 0.3176
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9020 - false_negatives_4: 65.2727 - false_positives_4: 78.4545 - loss: 0.2704 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8784 - false_negatives_4: 94.8182 - false_positives_4: 93.6364 - loss: 0.3176
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9023 - false_negatives_4: 71.8333 - false_positives_4: 84.0833 - loss: 0.2701 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8782 - false_negatives_4: 102.1667 - false_positives_4: 102.3333 - loss: 0.3176
``` - + ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9026 - false_negatives_4: 77.8462 - false_positives_4: 90.0769 - loss: 0.2699 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8782 - false_negatives_4: 109.6923 - false_positives_4: 110.2308 - loss: 0.3175
``` - + ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9030 - false_negatives_4: 83.7143 - false_positives_4: 95.7857 - loss: 0.2695 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8781 - false_negatives_4: 116.5714 - false_positives_4: 119.0000 - loss: 0.3177
``` - + ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9034 - false_negatives_4: 89.2667 - false_positives_4: 101.4000 - loss: 0.2691 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8780 - false_negatives_4: 124.4667 - false_positives_4: 127.0667 - loss: 0.3178
``` - + ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9039 - false_negatives_4: 94.6250 - false_positives_4: 106.9375 - loss: 0.2685 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 132.1250 - false_positives_4: 136.0625 - loss: 0.3181
``` - + ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9043 - false_negatives_4: 100.1176 - false_positives_4: 112.4118 - loss: 0.2680 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8776 - false_negatives_4: 139.6471 - false_positives_4: 144.7059 - loss: 0.3183
```  ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9046 - false_negatives_4: 105.1111 - false_positives_4: 118.9444 - loss: 0.2677 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8776 - false_negatives_4: 147.0000 - false_positives_4: 152.9444 - loss: 0.3183
```  ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9046 - false_negatives_4: 111.2632 - false_positives_4: 125.0000 - loss: 0.2677 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8776 - false_negatives_4: 154.1053 - false_positives_4: 161.1053 - loss: 0.3183
```  ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9047 - false_negatives_4: 117.1000 - false_positives_4: 131.2500 - loss: 0.2678 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 161.4500 - false_positives_4: 169.2500 - loss: 0.3184
```  ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9049 - false_negatives_4: 122.7619 - false_positives_4: 137.2381 - loss: 0.2677 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 168.4762 - false_positives_4: 177.6190 - loss: 0.3184
```  ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9051 - false_negatives_4: 128.1818 - false_positives_4: 143.2273 - loss: 0.2675 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 175.7273 - false_positives_4: 185.7727 - loss: 0.3185
```  ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9052 - false_negatives_4: 134.0870 - false_positives_4: 149.0435 - loss: 0.2675 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 182.9130 - false_positives_4: 194.1304 - loss: 0.3186
```  ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 6s 74ms/step - binary_accuracy: 0.9053 - false_negatives_4: 139.6667 - false_positives_4: 155.2917 - loss: 0.2674 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 189.9583 - false_positives_4: 202.6667 - loss: 0.3187
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9054 - false_negatives_4: 145.6800 - false_positives_4: 161.2800 - loss: 0.2674 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 197.0400 - false_positives_4: 211.1200 - loss: 0.3187
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 151.4615 - false_positives_4: 167.6154 - loss: 0.2675 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 203.9615 - false_positives_4: 219.7692 - loss: 0.3187
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 157.4074 - false_positives_4: 173.7037 - loss: 0.2676 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8778 - false_negatives_4: 211.1852 - false_positives_4: 228.1111 - loss: 0.3187
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 163.2143 - false_positives_4: 179.9286 - loss: 0.2676 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 218.0714 - false_positives_4: 236.9286 - loss: 0.3187
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 169.0000 - false_positives_4: 186.3793 - loss: 0.2676 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8777 - false_negatives_4: 225.7931 - false_positives_4: 245.3448 - loss: 0.3188
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 175.1000 - false_positives_4: 192.7333 - loss: 0.2676 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8776 - false_negatives_4: 233.2000 - false_positives_4: 254.1000 - loss: 0.3189
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 180.9355 - false_positives_4: 199.1613 - loss: 0.2676 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8776 - false_negatives_4: 240.5484 - false_positives_4: 262.5807 - loss: 0.3189
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 186.7500 - false_positives_4: 205.5625 - loss: 0.2675 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8775 - false_negatives_4: 247.8750 - false_positives_4: 271.0938 - loss: 0.3190
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9056 - false_negatives_4: 192.5152 - false_positives_4: 212.1212 - loss: 0.2675 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8775 - false_negatives_4: 255.7879 - false_positives_4: 279.3030 - loss: 0.3190
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 198.4118 - false_positives_4: 218.6471 - loss: 0.2674 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8774 - false_negatives_4: 263.3529 - false_positives_4: 288.0588 - loss: 0.3191
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 204.1714 - false_positives_4: 225.2000 - loss: 0.2674 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8773 - false_negatives_4: 270.8286 - false_positives_4: 296.7714 - loss: 0.3191
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 210.0000 - false_positives_4: 231.7500 - loss: 0.2674 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8773 - false_negatives_4: 278.3889 - false_positives_4: 305.3611 - loss: 0.3192
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 215.8919 - false_positives_4: 238.2162 - loss: 0.2674 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8772 - false_negatives_4: 285.7567 - false_positives_4: 314.1351 - loss: 0.3192
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 221.7368 - false_positives_4: 244.8421 - loss: 0.2674 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8772 - false_negatives_4: 293.1842 - false_positives_4: 322.7632 - loss: 0.3192
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9055 - false_negatives_4: 227.6923 - false_positives_4: 251.4359 - loss: 0.2674 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8771 - false_negatives_4: 300.6410 - false_positives_4: 331.4102 - loss: 0.3192
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9054 - false_negatives_4: 233.6500 - false_positives_4: 258.1500 - loss: 0.2674 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8771 - false_negatives_4: 308.0000 - false_positives_4: 340.0750 - loss: 0.3192
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9054 - false_negatives_4: 239.9756 - false_positives_4: 264.5610 - loss: 0.2674 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8771 - false_negatives_4: 315.4390 - false_positives_4: 348.6829 - loss: 0.3191
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9053 - false_negatives_4: 246.0238 - false_positives_4: 271.5952 - loss: 0.2675 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 322.7619 - false_positives_4: 357.3095 - loss: 0.3191
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9052 - false_negatives_4: 252.5349 - false_positives_4: 278.5581 - loss: 0.2676 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 330.0465 - false_positives_4: 365.7907 - loss: 0.3190
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9051 - false_negatives_4: 258.9318 - false_positives_4: 285.6364 - loss: 0.2677 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 337.2500 - false_positives_4: 374.2954 - loss: 0.3189
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9050 - false_negatives_4: 265.4889 - false_positives_4: 292.5333 - loss: 0.2679 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 344.6444 - false_positives_4: 382.7333 - loss: 0.3189
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9048 - false_negatives_4: 271.9131 - false_positives_4: 299.5435 - loss: 0.2680 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 351.9565 - false_positives_4: 391.2391 - loss: 0.3188
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9047 - false_negatives_4: 278.2766 - false_positives_4: 306.6383 - loss: 0.2681 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 359.2128 - false_positives_4: 399.8085 - loss: 0.3188
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9046 - false_negatives_4: 284.6458 - false_positives_4: 313.6875 - loss: 0.2682 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 366.4583 - false_positives_4: 408.3542 - loss: 0.3188
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9045 - false_negatives_4: 290.8979 - false_positives_4: 321.0612 - loss: 0.2683 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 373.4898 - false_positives_4: 416.8571 - loss: 0.3187
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9044 - false_negatives_4: 297.2200 - false_positives_4: 328.4200 - loss: 0.2685 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 380.7200 - false_positives_4: 425.2200 - loss: 0.3187
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9043 - false_negatives_4: 303.7647 - false_positives_4: 335.6274 - loss: 0.2686 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 387.7647 - false_positives_4: 433.6471 - loss: 0.3187
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9042 - false_negatives_4: 310.1538 - false_positives_4: 343.0000 - loss: 0.2688 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 395.1731 - false_positives_4: 441.8654 - loss: 0.3187
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9041 - false_negatives_4: 316.5472 - false_positives_4: 350.3019 - loss: 0.2689 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 402.4340 - false_positives_4: 450.3396 - loss: 0.3187
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9040 - false_negatives_4: 322.8704 - false_positives_4: 357.5926 - loss: 0.2690 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 410.0000 - false_positives_4: 458.6296 - loss: 0.3187
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9039 - false_negatives_4: 329.2364 - false_positives_4: 364.7818 - loss: 0.2691 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 417.3818 - false_positives_4: 467.2727 - loss: 0.3187
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9038 - false_negatives_4: 335.6429 - false_positives_4: 371.9464 - loss: 0.2693 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8770 - false_negatives_4: 424.9464 - false_positives_4: 475.7321 - loss: 0.3187
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9037 - false_negatives_4: 342.1053 - false_positives_4: 379.1754 - loss: 0.2694 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 432.2807 - false_positives_4: 484.3333 - loss: 0.3188
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9036 - false_negatives_4: 348.4828 - false_positives_4: 386.5345 - loss: 0.2695 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 439.7931 - false_positives_4: 492.7931 - loss: 0.3188
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9035 - false_negatives_4: 355.0508 - false_positives_4: 393.7288 - loss: 0.2696 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 447.2373 - false_positives_4: 501.2034 - loss: 0.3188
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9034 - false_negatives_4: 361.5333 - false_positives_4: 401.1333 - loss: 0.2698 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 454.6500 - false_positives_4: 509.6833 - loss: 0.3188
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9033 - false_negatives_4: 368.1803 - false_positives_4: 408.3279 - loss: 0.2699 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 462.0492 - false_positives_4: 518.1312 - loss: 0.3188
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9032 - false_negatives_4: 374.7742 - false_positives_4: 415.6613 - loss: 0.2701 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 469.3548 - false_positives_4: 526.5968 - loss: 0.3188
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9031 - false_negatives_4: 381.4445 - false_positives_4: 422.8254 - loss: 0.2702 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 476.7460 - false_positives_4: 535.1111 - loss: 0.3188
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9030 - false_negatives_4: 387.9688 - false_positives_4: 430.0469 - loss: 0.2703 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 484.1562 - false_positives_4: 543.5156 - loss: 0.3188
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9029 - false_negatives_4: 394.5538 - false_positives_4: 437.2308 - loss: 0.2704 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 491.4308 - false_positives_4: 552.0000 - loss: 0.3188
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9028 - false_negatives_4: 401.1060 - false_positives_4: 444.4394 - loss: 0.2705 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 498.7879 - false_positives_4: 560.4243 - loss: 0.3188
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9027 - false_negatives_4: 407.7015 - false_positives_4: 451.5672 - loss: 0.2706 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 506.1045 - false_positives_4: 568.8806 - loss: 0.3188
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9026 - false_negatives_4: 414.1912 - false_positives_4: 458.8382 - loss: 0.2708 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 513.3235 - false_positives_4: 577.3677 - loss: 0.3187
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9025 - false_negatives_4: 420.7971 - false_positives_4: 465.9276 - loss: 0.2709 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 520.6667 - false_positives_4: 585.7246 - loss: 0.3187
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9025 - false_negatives_4: 427.3000 - false_positives_4: 473.1000 - loss: 0.2710 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8769 - false_negatives_4: 527.9000 - false_positives_4: 594.3143 - loss: 0.3187
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9024 - false_negatives_4: 433.9296 - false_positives_4: 480.2253 - loss: 0.2711 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 535.3239 - false_positives_4: 602.7888 - loss: 0.3187
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9023 - false_negatives_4: 440.3889 - false_positives_4: 487.4861 - loss: 0.2712 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 542.7083 - false_positives_4: 611.3055 - loss: 0.3187
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9022 - false_negatives_4: 446.9452 - false_positives_4: 494.6849 - loss: 0.2713 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 550.0822 - false_positives_4: 619.8219 - loss: 0.3186
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9021 - false_negatives_4: 453.4460 - false_positives_4: 501.8919 - loss: 0.2714 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 557.4595 - false_positives_4: 628.3784 - loss: 0.3186
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9021 - false_negatives_4: 459.9067 - false_positives_4: 509.1333 - loss: 0.2715 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 564.7867 - false_positives_4: 637.0000 - loss: 0.3186
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9020 - false_negatives_4: 466.3421 - false_positives_4: 516.2500 - loss: 0.2716 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 572.1974 - false_positives_4: 645.5921 - loss: 0.3186
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9020 - false_negatives_4: 472.6753 - false_positives_4: 523.3506 - loss: 0.2717 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 579.5065 - false_positives_4: 654.2857 - loss: 0.3186
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9019 - false_negatives_4: 479.0641 - false_positives_4: 530.3718 - loss: 0.2717 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 586.8975 - false_positives_4: 662.8718 - loss: 0.3186
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9019 - false_negatives_4: 485.3671 - false_positives_4: 537.4177 - loss: 0.2718 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8768 - false_negatives_4: 594.1519 - false_positives_4: 671.5823 - loss: 0.3187
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9018 - false_negatives_4: 491.6750 - false_positives_4: 544.4500 - loss: 0.2719 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 601.5000 - false_positives_4: 680.2000 - loss: 0.3187
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9018 - false_negatives_4: 497.9506 - false_positives_4: 551.5432 - loss: 0.2719 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 608.8395 - false_positives_4: 688.9259 - loss: 0.3187
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9017 - false_negatives_4: 504.3171 - false_positives_4: 558.5975 - loss: 0.2720 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 616.2195 - false_positives_4: 697.6097 - loss: 0.3187
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9017 - false_negatives_4: 510.6145 - false_positives_4: 565.7711 - loss: 0.2721 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 623.5542 - false_positives_4: 706.3735 - loss: 0.3187
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9016 - false_negatives_4: 516.9524 - false_positives_4: 572.8690 - loss: 0.2721 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 631.0000 - false_positives_4: 715.0833 - loss: 0.3187
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9016 - false_negatives_4: 523.2353 - false_positives_4: 580.0000 - loss: 0.2722 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8767 - false_negatives_4: 638.4353 - false_positives_4: 723.8118 - loss: 0.3188
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9015 - false_negatives_4: 529.6512 - false_positives_4: 587.0814 - loss: 0.2722 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 645.8023 - false_positives_4: 732.5698 - loss: 0.3188
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9015 - false_negatives_4: 536.0000 - false_positives_4: 594.2069 - loss: 0.2723 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 653.1494 - false_positives_4: 741.2988 - loss: 0.3188
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9014 - false_negatives_4: 542.4659 - false_positives_4: 601.3068 - loss: 0.2724 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 660.4659 - false_positives_4: 750.0114 - loss: 0.3188
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9013 - false_negatives_4: 548.8427 - false_positives_4: 608.5843 - loss: 0.2724 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 667.7977 - false_positives_4: 758.6180 - loss: 0.3188
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9013 - false_negatives_4: 555.3000 - false_positives_4: 615.8222 - loss: 0.2725 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 675.0000 - false_positives_4: 767.2444 - loss: 0.3188
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9012 - false_negatives_4: 561.7143 - false_positives_4: 623.0879 - loss: 0.2726 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 682.3736 - false_positives_4: 775.8132 - loss: 0.3188
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9012 - false_negatives_4: 568.1522 - false_positives_4: 630.2935 - loss: 0.2727 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 689.6630 - false_positives_4: 784.4674 - loss: 0.3188
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9011 - false_negatives_4: 574.6022 - false_positives_4: 637.5054 - loss: 0.2727 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 697.0860 - false_positives_4: 793.0538 - loss: 0.3188
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9011 - false_negatives_4: 581.0319 - false_positives_4: 644.7021 - loss: 0.2728 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8766 - false_negatives_4: 704.4575 - false_positives_4: 801.7021 - loss: 0.3188
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9010 - false_negatives_4: 587.4631 - false_positives_4: 651.8105 - loss: 0.2729 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8765 - false_negatives_4: 711.8632 - false_positives_4: 810.2842 - loss: 0.3188
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9010 - false_negatives_4: 593.8646 - false_positives_4: 659.0521 - loss: 0.2730 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8765 - false_negatives_4: 719.2188 - false_positives_4: 819.1042 - loss: 0.3189
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9009 - false_negatives_4: 600.3712 - false_positives_4: 666.2681 - loss: 0.2730 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8765 - false_negatives_4: 726.8248 - false_positives_4: 827.8453 - loss: 0.3189
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9009 - false_negatives_4: 606.9184 - false_positives_4: 673.5102 - loss: 0.2731 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8765 - false_negatives_4: 734.3469 - false_positives_4: 836.7449 - loss: 0.3189
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9008 - false_negatives_4: 613.4243 - false_positives_4: 680.8182 - loss: 0.2732 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8764 - false_negatives_4: 741.9293 - false_positives_4: 845.6061 - loss: 0.3190
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9008 - false_negatives_4: 619.8900 - false_positives_4: 688.1300 - loss: 0.2732 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8764 - false_negatives_4: 749.5300 - false_positives_4: 854.5300 - loss: 0.3190
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9007 - false_negatives_4: 626.3466 - false_positives_4: 695.4554 - loss: 0.2733 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8764 - false_negatives_4: 757.0990 - false_positives_4: 863.4554 - loss: 0.3191
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9007 - false_negatives_4: 632.7451 - false_positives_4: 702.7549 - loss: 0.2734 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8764 - false_negatives_4: 764.6373 - false_positives_4: 872.3922 - loss: 0.3191
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9006 - false_negatives_4: 639.1068 - false_positives_4: 710.0000 - loss: 0.2735 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8763 - false_negatives_4: 772.1262 - false_positives_4: 881.2816 - loss: 0.3191
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9006 - false_negatives_4: 645.4808 - false_positives_4: 717.2885 - loss: 0.2735 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8763 - false_negatives_4: 779.5865 - false_positives_4: 890.1539 - loss: 0.3192
```  ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9005 - false_negatives_4: 651.8476 - false_positives_4: 724.5143 - loss: 0.2736 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8763 - false_negatives_4: 787.1047 - false_positives_4: 898.9714 - loss: 0.3192
```  ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9005 - false_negatives_4: 658.1981 - false_positives_4: 731.7264 - loss: 0.2736 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8763 - false_negatives_4: 794.5755 - false_positives_4: 907.8868 - loss: 0.3192
```  ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9005 - false_negatives_4: 664.5701 - false_positives_4: 738.9813 - loss: 0.2737 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 802.0934 - false_positives_4: 916.7850 - loss: 0.3193
```  ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9004 - false_negatives_4: 670.9352 - false_positives_4: 746.2685 - loss: 0.2738 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 809.5093 - false_positives_4: 925.6667 - loss: 0.3193
```  ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9004 - false_negatives_4: 677.3027 - false_positives_4: 753.5229 - loss: 0.2738 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 816.9541 - false_positives_4: 934.5596 - loss: 0.3193
```  ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9003 - false_negatives_4: 683.6909 - false_positives_4: 760.7909 - loss: 0.2739 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 824.4091 - false_positives_4: 943.3818 - loss: 0.3194
```  ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9003 - false_negatives_4: 690.1081 - false_positives_4: 768.0901 - loss: 0.2740 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 831.8108 - false_positives_4: 952.2883 - loss: 0.3194
```  ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9002 - false_negatives_4: 696.6607 - false_positives_4: 775.3125 - loss: 0.2740 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8762 - false_negatives_4: 839.3214 - false_positives_4: 961.1161 - loss: 0.3194
```  ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9002 - false_negatives_4: 703.1416 - false_positives_4: 782.7522 - loss: 0.2741 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8761 - false_negatives_4: 846.7610 - false_positives_4: 970.0266 - loss: 0.3194
```  ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9001 - false_negatives_4: 709.8333 - false_positives_4: 790.1667 - loss: 0.2742 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8761 - false_negatives_4: 854.2018 - false_positives_4: 978.8860 - loss: 0.3194
```  ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9001 - false_negatives_4: 716.4261 - false_positives_4: 797.7043 - loss: 0.2742 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8761 - false_negatives_4: 861.6087 - false_positives_4: 987.8000 - loss: 0.3195
```  ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9000 - false_negatives_4: 723.0431 - false_positives_4: 805.2241 - loss: 0.2743 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8761 - false_negatives_4: 869.0431 - false_positives_4: 996.7069 - loss: 0.3195
```  ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9000 - false_negatives_4: 729.7265 - false_positives_4: 812.7692 - loss: 0.2744 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8761 - false_negatives_4: 876.4872 - false_positives_4: 1005.5726 - loss: 0.3195
``` -Epoch 2: val_loss improved from 0.34519 to 0.33508, saving model to AL_Model.keras +Epoch 2: val_loss improved from 0.36196 to 0.35707, saving model to AL_Model.keras - + ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 78ms/step - binary_accuracy: 0.8999 - false_negatives_4: 742.8067 - false_positives_4: 827.5294 - loss: 0.2745 - val_binary_accuracy: 0.8586 - val_false_negatives_4: 300.0000 - val_false_positives_4: 407.0000 - val_loss: 0.3351 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 10s 82ms/step - binary_accuracy: 0.8760 - false_negatives_4: 891.0504 - false_positives_4: 1022.9412 - loss: 0.3196 - val_binary_accuracy: 0.8404 - val_false_negatives_4: 479.0000 - val_false_positives_4: 319.0000 - val_loss: 0.3571
@@ -29497,829 +28546,829 @@ Epoch 3/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 95ms/step - binary_accuracy: 0.9258 - false_negatives_4: 8.0000 - false_positives_4: 11.0000 - loss: 0.2452 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 94ms/step - binary_accuracy: 0.9062 - false_negatives_4: 17.0000 - false_positives_4: 7.0000 - loss: 0.3179
```  ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9277 - false_negatives_4: 12.0000 - false_positives_4: 15.5000 - loss: 0.2369 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8965 - false_negatives_4: 21.5000 - false_positives_4: 19.5000 - loss: 0.3115
```  ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 16.0000 - false_positives_4: 21.6667 - loss: 0.2385 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8941 - false_negatives_4: 26.6667 - false_positives_4: 29.0000 - loss: 0.3111
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 72ms/step - binary_accuracy: 0.9272 - false_negatives_4: 20.0000 - false_positives_4: 26.5000 - loss: 0.2367 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8957 - false_negatives_4: 31.2500 - false_positives_4: 36.0000 - loss: 0.3049
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9269 - false_negatives_4: 24.6000 - false_positives_4: 31.6000 - loss: 0.2347 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8967 - false_negatives_4: 36.8000 - false_positives_4: 42.4000 - loss: 0.2992
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 29.3333 - false_positives_4: 36.6667 - loss: 0.2341 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8963 - false_negatives_4: 42.3333 - false_positives_4: 50.6667 - loss: 0.2959
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 33.8571 - false_positives_4: 41.2857 - loss: 0.2328 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8958 - false_negatives_4: 50.0000 - false_positives_4: 57.2857 - loss: 0.2937
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9272 - false_negatives_4: 38.1250 - false_positives_4: 45.5000 - loss: 0.2314 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8954 - false_negatives_4: 57.0000 - false_positives_4: 64.3750 - loss: 0.2914
```  ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9270 - false_negatives_4: 43.3333 - false_positives_4: 50.0000 - loss: 0.2308 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8954 - false_negatives_4: 63.8889 - false_positives_4: 70.6667 - loss: 0.2892
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9267 - false_negatives_4: 47.9000 - false_positives_4: 55.5000 - loss: 0.2307 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.8955 - false_negatives_4: 70.1000 - false_positives_4: 77.6000 - loss: 0.2877
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9264 - false_negatives_4: 53.3636 - false_positives_4: 60.2727 - loss: 0.2308 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8956 - false_negatives_4: 76.1818 - false_positives_4: 84.4545 - loss: 0.2861
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9261 - false_negatives_4: 58.3333 - false_positives_4: 65.6667 - loss: 0.2312 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8957 - false_negatives_4: 82.5833 - false_positives_4: 91.1667 - loss: 0.2848
```  ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9257 - false_negatives_4: 63.8462 - false_positives_4: 70.8462 - loss: 0.2318 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8960 - false_negatives_4: 88.5385 - false_positives_4: 97.5385 - loss: 0.2835
```  ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9252 - false_negatives_4: 69.1429 - false_positives_4: 76.6429 - loss: 0.2325 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8963 - false_negatives_4: 94.0714 - false_positives_4: 104.1429 - loss: 0.2824
``` - + ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9249 - false_negatives_4: 74.4000 - false_positives_4: 82.2000 - loss: 0.2329 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8964 - false_negatives_4: 100.9333 - false_positives_4: 110.4000 - loss: 0.2821
``` - + ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9245 - false_negatives_4: 79.3750 - false_positives_4: 88.1250 - loss: 0.2335 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8964 - false_negatives_4: 107.2500 - false_positives_4: 117.3750 - loss: 0.2820
``` - + ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9241 - false_negatives_4: 85.0000 - false_positives_4: 93.8235 - loss: 0.2341 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8963 - false_negatives_4: 114.4118 - false_positives_4: 123.8824 - loss: 0.2821
``` - + ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9238 - false_negatives_4: 90.2222 - false_positives_4: 99.5556 - loss: 0.2346 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8962 - false_negatives_4: 121.0556 - false_positives_4: 131.1667 - loss: 0.2824
``` - + ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9235 - false_negatives_4: 95.4737 - false_positives_4: 105.2105 - loss: 0.2349 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8960 - false_negatives_4: 127.7895 - false_positives_4: 138.3684 - loss: 0.2827
``` - + ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9233 - false_negatives_4: 100.7000 - false_positives_4: 110.7000 - loss: 0.2351 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8959 - false_negatives_4: 134.1500 - false_positives_4: 145.8000 - loss: 0.2829
```  ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9231 - false_negatives_4: 105.7143 - false_positives_4: 116.0952 - loss: 0.2353 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8959 - false_negatives_4: 140.4762 - false_positives_4: 153.1905 - loss: 0.2831
```  ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9230 - false_negatives_4: 110.4545 - false_positives_4: 121.5455 - loss: 0.2353 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8958 - false_negatives_4: 146.7273 - false_positives_4: 160.6364 - loss: 0.2833
```  ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9228 - false_negatives_4: 115.4783 - false_positives_4: 127.1739 - loss: 0.2353 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8957 - false_negatives_4: 152.9565 - false_positives_4: 168.0870 - loss: 0.2834
```  ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9226 - false_negatives_4: 120.2500 - false_positives_4: 133.3333 - loss: 0.2354 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.8957 - false_negatives_4: 159.1250 - false_positives_4: 175.7500 - loss: 0.2834
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9224 - false_negatives_4: 125.3600 - false_positives_4: 139.3600 - loss: 0.2354 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8956 - false_negatives_4: 165.5200 - false_positives_4: 183.2800 - loss: 0.2836
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9222 - false_negatives_4: 130.2692 - false_positives_4: 145.4615 - loss: 0.2355 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8955 - false_negatives_4: 171.7308 - false_positives_4: 190.9615 - loss: 0.2837
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9220 - false_negatives_4: 135.4444 - false_positives_4: 151.5556 - loss: 0.2355 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8954 - false_negatives_4: 178.0000 - false_positives_4: 198.5556 - loss: 0.2838
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9218 - false_negatives_4: 140.4643 - false_positives_4: 157.5357 - loss: 0.2355 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8953 - false_negatives_4: 184.2143 - false_positives_4: 206.3929 - loss: 0.2839
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9216 - false_negatives_4: 145.7241 - false_positives_4: 163.4828 - loss: 0.2355 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8952 - false_negatives_4: 190.5862 - false_positives_4: 214.0000 - loss: 0.2840
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9214 - false_negatives_4: 150.8667 - false_positives_4: 169.6333 - loss: 0.2355 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8952 - false_negatives_4: 196.7333 - false_positives_4: 221.6333 - loss: 0.2841
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9212 - false_negatives_4: 156.2258 - false_positives_4: 175.5484 - loss: 0.2355 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8951 - false_negatives_4: 203.1613 - false_positives_4: 229.0968 - loss: 0.2841
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9210 - false_negatives_4: 161.5312 - false_positives_4: 181.7500 - loss: 0.2356 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8950 - false_negatives_4: 209.4688 - false_positives_4: 236.7188 - loss: 0.2842
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9208 - false_negatives_4: 166.9091 - false_positives_4: 187.8182 - loss: 0.2358 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8949 - false_negatives_4: 216.3030 - false_positives_4: 244.0909 - loss: 0.2843
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9206 - false_negatives_4: 172.3529 - false_positives_4: 193.7353 - loss: 0.2359 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8948 - false_negatives_4: 222.9118 - false_positives_4: 251.7647 - loss: 0.2844
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9205 - false_negatives_4: 177.6857 - false_positives_4: 199.6857 - loss: 0.2360 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8947 - false_negatives_4: 229.8857 - false_positives_4: 259.2857 - loss: 0.2845
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9203 - false_negatives_4: 183.0278 - false_positives_4: 205.5556 - loss: 0.2361 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8946 - false_negatives_4: 236.6944 - false_positives_4: 266.9445 - loss: 0.2846
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9202 - false_negatives_4: 188.3513 - false_positives_4: 211.3784 - loss: 0.2362 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.8944 - false_negatives_4: 243.6757 - false_positives_4: 274.6757 - loss: 0.2848
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9201 - false_negatives_4: 193.5526 - false_positives_4: 217.3947 - loss: 0.2363 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8943 - false_negatives_4: 250.7632 - false_positives_4: 282.2368 - loss: 0.2850
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9199 - false_negatives_4: 199.2051 - false_positives_4: 223.3077 - loss: 0.2364 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8941 - false_negatives_4: 257.7436 - false_positives_4: 290.1795 - loss: 0.2852
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9197 - false_negatives_4: 204.6750 - false_positives_4: 229.7500 - loss: 0.2366 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8940 - false_negatives_4: 264.8250 - false_positives_4: 298.0500 - loss: 0.2854
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9195 - false_negatives_4: 210.4878 - false_positives_4: 236.1219 - loss: 0.2368 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8939 - false_negatives_4: 271.8537 - false_positives_4: 305.8537 - loss: 0.2856
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9193 - false_negatives_4: 216.2381 - false_positives_4: 242.7381 - loss: 0.2371 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8937 - false_negatives_4: 278.7857 - false_positives_4: 313.8333 - loss: 0.2859
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9190 - false_negatives_4: 222.0465 - false_positives_4: 249.3954 - loss: 0.2373 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8936 - false_negatives_4: 285.9767 - false_positives_4: 321.6744 - loss: 0.2861
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9188 - false_negatives_4: 227.8864 - false_positives_4: 255.8864 - loss: 0.2376 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8934 - false_negatives_4: 292.9318 - false_positives_4: 329.8636 - loss: 0.2864
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9186 - false_negatives_4: 233.7111 - false_positives_4: 262.5111 - loss: 0.2378 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8933 - false_negatives_4: 300.0000 - false_positives_4: 337.8445 - loss: 0.2866
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9184 - false_negatives_4: 239.5870 - false_positives_4: 269.0652 - loss: 0.2381 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8932 - false_negatives_4: 307.0217 - false_positives_4: 345.7174 - loss: 0.2869
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9182 - false_negatives_4: 245.3404 - false_positives_4: 275.8298 - loss: 0.2384 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8930 - false_negatives_4: 313.8298 - false_positives_4: 353.7872 - loss: 0.2871
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9180 - false_negatives_4: 251.1875 - false_positives_4: 282.5417 - loss: 0.2386 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8929 - false_negatives_4: 320.9375 - false_positives_4: 361.7083 - loss: 0.2873
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9178 - false_negatives_4: 257.0612 - false_positives_4: 289.1633 - loss: 0.2388 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8928 - false_negatives_4: 327.8979 - false_positives_4: 369.8163 - loss: 0.2875
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9176 - false_negatives_4: 263.0000 - false_positives_4: 295.7200 - loss: 0.2391 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.8927 - false_negatives_4: 335.1400 - false_positives_4: 377.6800 - loss: 0.2877
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9174 - false_negatives_4: 268.9804 - false_positives_4: 302.3333 - loss: 0.2393 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8925 - false_negatives_4: 342.1373 - false_positives_4: 386.0000 - loss: 0.2879
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9173 - false_negatives_4: 274.8654 - false_positives_4: 308.8846 - loss: 0.2395 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8924 - false_negatives_4: 349.2885 - false_positives_4: 394.1346 - loss: 0.2881
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9171 - false_negatives_4: 280.6981 - false_positives_4: 315.4717 - loss: 0.2397 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.8923 - false_negatives_4: 356.3019 - false_positives_4: 402.2830 - loss: 0.2884
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9169 - false_negatives_4: 286.6296 - false_positives_4: 321.9815 - loss: 0.2399 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8922 - false_negatives_4: 363.2592 - false_positives_4: 410.4074 - loss: 0.2885
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9168 - false_negatives_4: 292.5273 - false_positives_4: 328.4727 - loss: 0.2401 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8920 - false_negatives_4: 370.1091 - false_positives_4: 418.6909 - loss: 0.2887
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9166 - false_negatives_4: 298.4107 - false_positives_4: 335.1429 - loss: 0.2404 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8919 - false_negatives_4: 377.0000 - false_positives_4: 426.8571 - loss: 0.2889
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9165 - false_negatives_4: 304.4737 - false_positives_4: 341.8246 - loss: 0.2406 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8918 - false_negatives_4: 383.8421 - false_positives_4: 435.1053 - loss: 0.2890
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9163 - false_negatives_4: 310.5345 - false_positives_4: 348.5862 - loss: 0.2408 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8917 - false_negatives_4: 390.6897 - false_positives_4: 443.3793 - loss: 0.2892
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9161 - false_negatives_4: 316.5932 - false_positives_4: 355.2373 - loss: 0.2410 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8916 - false_negatives_4: 397.6610 - false_positives_4: 451.5763 - loss: 0.2894
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9160 - false_negatives_4: 322.5667 - false_positives_4: 361.9000 - loss: 0.2412 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8915 - false_negatives_4: 404.5167 - false_positives_4: 459.9500 - loss: 0.2895
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9158 - false_negatives_4: 328.6885 - false_positives_4: 368.5901 - loss: 0.2414 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8914 - false_negatives_4: 411.7705 - false_positives_4: 468.1147 - loss: 0.2897
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9156 - false_negatives_4: 334.7258 - false_positives_4: 375.3710 - loss: 0.2416 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8913 - false_negatives_4: 418.8387 - false_positives_4: 476.6613 - loss: 0.2899
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9155 - false_negatives_4: 340.9365 - false_positives_4: 382.0476 - loss: 0.2419 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8911 - false_negatives_4: 426.0317 - false_positives_4: 485.1111 - loss: 0.2901
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9153 - false_negatives_4: 346.9844 - false_positives_4: 388.9844 - loss: 0.2421 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.8910 - false_negatives_4: 433.0938 - false_positives_4: 493.6719 - loss: 0.2903
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9152 - false_negatives_4: 353.1385 - false_positives_4: 395.8154 - loss: 0.2423 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8909 - false_negatives_4: 440.2308 - false_positives_4: 502.0923 - loss: 0.2904
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9150 - false_negatives_4: 359.2424 - false_positives_4: 402.6667 - loss: 0.2425 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8908 - false_negatives_4: 447.3030 - false_positives_4: 510.6970 - loss: 0.2906
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9149 - false_negatives_4: 365.2836 - false_positives_4: 409.4328 - loss: 0.2427 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8907 - false_negatives_4: 454.2537 - false_positives_4: 519.2537 - loss: 0.2908
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9147 - false_negatives_4: 371.2500 - false_positives_4: 416.2500 - loss: 0.2430 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8906 - false_negatives_4: 461.1471 - false_positives_4: 527.7500 - loss: 0.2909
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9146 - false_negatives_4: 377.2029 - false_positives_4: 422.9710 - loss: 0.2432 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8905 - false_negatives_4: 468.0145 - false_positives_4: 536.2319 - loss: 0.2911
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9145 - false_negatives_4: 383.1000 - false_positives_4: 429.7000 - loss: 0.2433 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8904 - false_negatives_4: 474.9143 - false_positives_4: 544.6572 - loss: 0.2912
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9144 - false_negatives_4: 389.0000 - false_positives_4: 436.4225 - loss: 0.2435 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8903 - false_negatives_4: 481.7042 - false_positives_4: 553.1972 - loss: 0.2914
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9142 - false_negatives_4: 394.9722 - false_positives_4: 443.0833 - loss: 0.2437 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8902 - false_negatives_4: 488.5972 - false_positives_4: 561.6528 - loss: 0.2915
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9141 - false_negatives_4: 400.8493 - false_positives_4: 449.7671 - loss: 0.2439 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8901 - false_negatives_4: 495.4795 - false_positives_4: 570.2328 - loss: 0.2917
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9140 - false_negatives_4: 406.8243 - false_positives_4: 456.3513 - loss: 0.2441 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8900 - false_negatives_4: 502.5000 - false_positives_4: 578.7703 - loss: 0.2918
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9139 - false_negatives_4: 412.6933 - false_positives_4: 463.1067 - loss: 0.2443 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8899 - false_negatives_4: 509.4800 - false_positives_4: 587.4400 - loss: 0.2920
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9138 - false_negatives_4: 418.6316 - false_positives_4: 469.7895 - loss: 0.2445 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8898 - false_negatives_4: 516.6053 - false_positives_4: 596.0395 - loss: 0.2922
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9137 - false_negatives_4: 424.7013 - false_positives_4: 476.4156 - loss: 0.2446 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.8897 - false_negatives_4: 523.6364 - false_positives_4: 604.5974 - loss: 0.2923
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9136 - false_negatives_4: 430.7051 - false_positives_4: 483.1795 - loss: 0.2448 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8896 - false_negatives_4: 530.6025 - false_positives_4: 613.1539 - loss: 0.2925
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9135 - false_negatives_4: 436.8228 - false_positives_4: 489.8228 - loss: 0.2450 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8896 - false_negatives_4: 537.4684 - false_positives_4: 621.7089 - loss: 0.2926
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9134 - false_negatives_4: 442.9250 - false_positives_4: 496.5000 - loss: 0.2452 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8895 - false_negatives_4: 544.3250 - false_positives_4: 630.1875 - loss: 0.2927
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9133 - false_negatives_4: 448.9753 - false_positives_4: 503.1852 - loss: 0.2454 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8894 - false_negatives_4: 551.2222 - false_positives_4: 638.5926 - loss: 0.2929
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9132 - false_negatives_4: 455.0610 - false_positives_4: 509.8171 - loss: 0.2456 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8893 - false_negatives_4: 558.0854 - false_positives_4: 647.1464 - loss: 0.2930
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9131 - false_negatives_4: 461.1325 - false_positives_4: 516.5060 - loss: 0.2458 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8893 - false_negatives_4: 565.1325 - false_positives_4: 655.5542 - loss: 0.2932
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9130 - false_negatives_4: 467.1786 - false_positives_4: 523.1310 - loss: 0.2459 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8892 - false_negatives_4: 572.0952 - false_positives_4: 664.2024 - loss: 0.2933
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9129 - false_negatives_4: 473.2471 - false_positives_4: 529.7529 - loss: 0.2461 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8891 - false_negatives_4: 579.1765 - false_positives_4: 672.7177 - loss: 0.2935
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9128 - false_negatives_4: 479.2907 - false_positives_4: 536.4070 - loss: 0.2463 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8890 - false_negatives_4: 586.1395 - false_positives_4: 681.3488 - loss: 0.2936
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9127 - false_negatives_4: 485.3333 - false_positives_4: 542.9770 - loss: 0.2464 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8889 - false_negatives_4: 593.1149 - false_positives_4: 689.9425 - loss: 0.2937
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9126 - false_negatives_4: 491.3296 - false_positives_4: 549.5909 - loss: 0.2466 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8889 - false_negatives_4: 600.1591 - false_positives_4: 698.5000 - loss: 0.2939
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9125 - false_negatives_4: 497.3258 - false_positives_4: 556.2023 - loss: 0.2468 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8888 - false_negatives_4: 607.1573 - false_positives_4: 707.0449 - loss: 0.2940
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.9124 - false_negatives_4: 503.2667 - false_positives_4: 562.8333 - loss: 0.2469 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8887 - false_negatives_4: 614.1222 - false_positives_4: 715.5667 - loss: 0.2942
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9124 - false_negatives_4: 509.2308 - false_positives_4: 569.4176 - loss: 0.2470 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 74ms/step - binary_accuracy: 0.8887 - false_negatives_4: 621.0769 - false_positives_4: 723.9451 - loss: 0.2943
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9123 - false_negatives_4: 515.2283 - false_positives_4: 575.9674 - loss: 0.2472 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8886 - false_negatives_4: 627.9457 - false_positives_4: 732.3152 - loss: 0.2944
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9122 - false_negatives_4: 521.2043 - false_positives_4: 582.5377 - loss: 0.2473 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8885 - false_negatives_4: 634.8387 - false_positives_4: 740.6451 - loss: 0.2945
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9121 - false_negatives_4: 527.2341 - false_positives_4: 589.0851 - loss: 0.2475 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8885 - false_negatives_4: 641.6702 - false_positives_4: 749.0532 - loss: 0.2946
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9121 - false_negatives_4: 533.1895 - false_positives_4: 595.6842 - loss: 0.2476 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8884 - false_negatives_4: 648.5895 - false_positives_4: 757.4000 - loss: 0.2947
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9120 - false_negatives_4: 539.2083 - false_positives_4: 602.2292 - loss: 0.2478 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8884 - false_negatives_4: 655.4896 - false_positives_4: 765.6979 - loss: 0.2948
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9119 - false_negatives_4: 545.2165 - false_positives_4: 608.8248 - loss: 0.2479 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8883 - false_negatives_4: 662.3917 - false_positives_4: 774.0413 - loss: 0.2949
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9118 - false_negatives_4: 551.2245 - false_positives_4: 615.3979 - loss: 0.2480 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8883 - false_negatives_4: 669.2857 - false_positives_4: 782.3776 - loss: 0.2950
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9118 - false_negatives_4: 557.2121 - false_positives_4: 621.9697 - loss: 0.2482 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8882 - false_negatives_4: 676.2222 - false_positives_4: 790.6768 - loss: 0.2951
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9117 - false_negatives_4: 563.2200 - false_positives_4: 628.4900 - loss: 0.2483 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8882 - false_negatives_4: 683.1000 - false_positives_4: 798.9600 - loss: 0.2952
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9116 - false_negatives_4: 569.1881 - false_positives_4: 635.0594 - loss: 0.2484 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8881 - false_negatives_4: 689.9703 - false_positives_4: 807.2871 - loss: 0.2952
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9116 - false_negatives_4: 575.1569 - false_positives_4: 641.5980 - loss: 0.2485 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8881 - false_negatives_4: 696.8333 - false_positives_4: 815.6078 - loss: 0.2953
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9115 - false_negatives_4: 581.0777 - false_positives_4: 648.1359 - loss: 0.2486 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8880 - false_negatives_4: 703.6990 - false_positives_4: 823.8738 - loss: 0.2954
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.9114 - false_negatives_4: 586.9711 - false_positives_4: 654.6635 - loss: 0.2488 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 74ms/step - binary_accuracy: 0.8880 - false_negatives_4: 710.5289 - false_positives_4: 832.2596 - loss: 0.2955
```  ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9114 - false_negatives_4: 592.8190 - false_positives_4: 661.2571 - loss: 0.2489 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8879 - false_negatives_4: 717.4952 - false_positives_4: 840.5143 - loss: 0.2956
```  ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9113 - false_negatives_4: 598.7736 - false_positives_4: 667.8019 - loss: 0.2490 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8879 - false_negatives_4: 724.3962 - false_positives_4: 848.8868 - loss: 0.2956
```  ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9113 - false_negatives_4: 604.6729 - false_positives_4: 674.3925 - loss: 0.2491 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8878 - false_negatives_4: 731.4393 - false_positives_4: 857.2150 - loss: 0.2957
```  ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9112 - false_negatives_4: 610.5926 - false_positives_4: 680.9815 - loss: 0.2492 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8878 - false_negatives_4: 738.4352 - false_positives_4: 865.5926 - loss: 0.2958
```  ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9111 - false_negatives_4: 616.4771 - false_positives_4: 687.5413 - loss: 0.2493 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8877 - false_negatives_4: 745.3578 - false_positives_4: 874.0367 - loss: 0.2959
```  ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9111 - false_negatives_4: 622.3364 - false_positives_4: 694.0818 - loss: 0.2494 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8877 - false_negatives_4: 752.3273 - false_positives_4: 882.4272 - loss: 0.2960
```  ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9110 - false_negatives_4: 628.1982 - false_positives_4: 700.6577 - loss: 0.2495 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8877 - false_negatives_4: 759.2613 - false_positives_4: 890.8739 - loss: 0.2960
```  ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9110 - false_negatives_4: 634.1339 - false_positives_4: 707.1875 - loss: 0.2496 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8876 - false_negatives_4: 766.2411 - false_positives_4: 899.3125 - loss: 0.2961
```  ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9109 - false_negatives_4: 640.0266 - false_positives_4: 713.8495 - loss: 0.2498 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8876 - false_negatives_4: 773.2213 - false_positives_4: 907.7699 - loss: 0.2962
```  ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9109 - false_negatives_4: 646.1228 - false_positives_4: 720.4386 - loss: 0.2499 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8875 - false_negatives_4: 780.1754 - false_positives_4: 916.2368 - loss: 0.2963
```  ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9108 - false_negatives_4: 652.1739 - false_positives_4: 727.1218 - loss: 0.2500 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8875 - false_negatives_4: 787.1913 - false_positives_4: 924.6348 - loss: 0.2963
```  ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9107 - false_negatives_4: 658.2500 - false_positives_4: 733.8104 - loss: 0.2501 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8874 - false_negatives_4: 794.1638 - false_positives_4: 933.1035 - loss: 0.2964
```  ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.9107 - false_negatives_4: 664.3846 - false_positives_4: 740.5043 - loss: 0.2502 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 74ms/step - binary_accuracy: 0.8874 - false_negatives_4: 801.1710 - false_positives_4: 941.4786 - loss: 0.2965
``` -Epoch 3: val_loss did not improve from 0.33508 +Epoch 3: val_loss did not improve from 0.35707  ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 79ms/step - binary_accuracy: 0.9106 - false_negatives_4: 676.4117 - false_positives_4: 753.6050 - loss: 0.2505 - val_binary_accuracy: 0.8488 - val_false_negatives_4: 203.0000 - val_false_positives_4: 553.0000 - val_loss: 0.3587 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 79ms/step - binary_accuracy: 0.8873 - false_negatives_4: 814.8319 - false_positives_4: 957.8571 - loss: 0.2966 - val_binary_accuracy: 0.8226 - val_false_negatives_4: 677.0000 - val_false_positives_4: 210.0000 - val_loss: 0.3948
@@ -30329,829 +29378,829 @@ Epoch 4/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 10s 92ms/step - binary_accuracy: 0.9102 - false_negatives_4: 6.0000 - false_positives_4: 17.0000 - loss: 0.2605 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 95ms/step - binary_accuracy: 0.8711 - false_negatives_4: 28.0000 - false_positives_4: 5.0000 - loss: 0.3450
```  ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9189 - false_negatives_4: 7.5000 - false_positives_4: 22.5000 - loss: 0.2452 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8828 - false_negatives_4: 30.5000 - false_positives_4: 13.0000 - loss: 0.3192
``` - + ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9217 - false_negatives_4: 13.0000 - false_positives_4: 25.6667 - loss: 0.2392 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8898 - false_negatives_4: 34.6667 - false_positives_4: 19.0000 - loss: 0.3054
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9222 - false_negatives_4: 17.2500 - false_positives_4: 31.2500 - loss: 0.2360 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8946 - false_negatives_4: 38.5000 - false_positives_4: 25.0000 - loss: 0.2962
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9210 - false_negatives_4: 24.2000 - false_positives_4: 36.0000 - loss: 0.2380 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.8977 - false_negatives_4: 43.2000 - false_positives_4: 30.6000 - loss: 0.2887
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9193 - false_negatives_4: 29.6667 - false_positives_4: 43.3333 - loss: 0.2398 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.8989 - false_negatives_4: 48.5000 - false_positives_4: 37.3333 - loss: 0.2838
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 75ms/step - binary_accuracy: 0.9181 - false_negatives_4: 35.5714 - false_positives_4: 49.8571 - loss: 0.2409 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9000 - false_negatives_4: 54.0000 - false_positives_4: 43.5714 - loss: 0.2798
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9178 - false_negatives_4: 40.3750 - false_positives_4: 56.0000 - loss: 0.2405 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9008 - false_negatives_4: 59.3750 - false_positives_4: 49.8750 - loss: 0.2766
```  ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9175 - false_negatives_4: 45.6667 - false_positives_4: 61.6667 - loss: 0.2403 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9019 - false_negatives_4: 64.4444 - false_positives_4: 55.5556 - loss: 0.2733
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9173 - false_negatives_4: 50.4000 - false_positives_4: 67.9000 - loss: 0.2398 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9024 - false_negatives_4: 70.9000 - false_positives_4: 61.0000 - loss: 0.2715
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9170 - false_negatives_4: 55.7273 - false_positives_4: 73.8182 - loss: 0.2395 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9027 - false_negatives_4: 76.6364 - false_positives_4: 67.4545 - loss: 0.2705
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9167 - false_negatives_4: 60.7500 - false_positives_4: 80.1667 - loss: 0.2394 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9029 - false_negatives_4: 82.4167 - false_positives_4: 73.8333 - loss: 0.2694
```  ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9163 - false_negatives_4: 66.3077 - false_positives_4: 86.4615 - loss: 0.2393 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9031 - false_negatives_4: 87.8462 - false_positives_4: 80.6154 - loss: 0.2686
```  ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9161 - false_negatives_4: 71.2143 - false_positives_4: 92.6429 - loss: 0.2389 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 93.5000 - false_positives_4: 87.0714 - loss: 0.2680
```  ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9157 - false_negatives_4: 77.2000 - false_positives_4: 98.8000 - loss: 0.2391 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9034 - false_negatives_4: 99.0667 - false_positives_4: 93.8000 - loss: 0.2678
```  ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9154 - false_negatives_4: 82.5625 - false_positives_4: 105.1250 - loss: 0.2391 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9035 - false_negatives_4: 104.9375 - false_positives_4: 100.0000 - loss: 0.2676
``` - + ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9152 - false_negatives_4: 88.2941 - false_positives_4: 110.9412 - loss: 0.2390 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9036 - false_negatives_4: 110.7647 - false_positives_4: 106.7647 - loss: 0.2675
``` - + ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9151 - false_negatives_4: 93.5556 - false_positives_4: 116.8889 - loss: 0.2388 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9035 - false_negatives_4: 116.8889 - false_positives_4: 113.3889 - loss: 0.2674
``` - + ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9149 - false_negatives_4: 99.4211 - false_positives_4: 122.4211 - loss: 0.2387 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9034 - false_negatives_4: 122.7895 - false_positives_4: 120.4211 - loss: 0.2672
``` - + ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 74ms/step - binary_accuracy: 0.9148 - false_negatives_4: 104.9500 - false_positives_4: 128.2500 - loss: 0.2386 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9034 - false_negatives_4: 128.9500 - false_positives_4: 127.0500 - loss: 0.2672
```  ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9147 - false_negatives_4: 110.5714 - false_positives_4: 133.7619 - loss: 0.2385 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9034 - false_negatives_4: 134.5714 - false_positives_4: 134.2381 - loss: 0.2672
```  ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9146 - false_negatives_4: 116.0000 - false_positives_4: 139.5455 - loss: 0.2383 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 140.4545 - false_positives_4: 141.0909 - loss: 0.2672
```  ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9145 - false_negatives_4: 121.8261 - false_positives_4: 145.0435 - loss: 0.2383 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 146.2174 - false_positives_4: 148.0870 - loss: 0.2672
```  ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9144 - false_negatives_4: 127.4583 - false_positives_4: 151.0833 - loss: 0.2384 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 151.7500 - false_positives_4: 154.7500 - loss: 0.2670
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9143 - false_negatives_4: 133.4000 - false_positives_4: 156.8400 - loss: 0.2385 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 157.2800 - false_positives_4: 161.5600 - loss: 0.2669
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9142 - false_negatives_4: 139.0000 - false_positives_4: 162.6923 - loss: 0.2385 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 163.1538 - false_positives_4: 168.2308 - loss: 0.2668
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9140 - false_negatives_4: 144.9259 - false_positives_4: 168.4444 - loss: 0.2386 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9033 - false_negatives_4: 169.1481 - false_positives_4: 175.1852 - loss: 0.2669
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9139 - false_negatives_4: 150.8214 - false_positives_4: 174.2143 - loss: 0.2387 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9032 - false_negatives_4: 175.6071 - false_positives_4: 182.0000 - loss: 0.2669
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9138 - false_negatives_4: 156.6552 - false_positives_4: 180.0345 - loss: 0.2387 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9030 - false_negatives_4: 181.8965 - false_positives_4: 189.1035 - loss: 0.2670
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9137 - false_negatives_4: 162.5000 - false_positives_4: 185.8333 - loss: 0.2388 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9029 - false_negatives_4: 188.1000 - false_positives_4: 196.1000 - loss: 0.2671
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9136 - false_negatives_4: 168.2903 - false_positives_4: 191.4839 - loss: 0.2389 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9028 - false_negatives_4: 194.1613 - false_positives_4: 203.1613 - loss: 0.2672
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9136 - false_negatives_4: 174.0312 - false_positives_4: 197.1875 - loss: 0.2389 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9028 - false_negatives_4: 200.2500 - false_positives_4: 210.1250 - loss: 0.2672
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9135 - false_negatives_4: 179.6667 - false_positives_4: 202.9697 - loss: 0.2390 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9027 - false_negatives_4: 206.3636 - false_positives_4: 217.0909 - loss: 0.2673
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9134 - false_negatives_4: 185.3235 - false_positives_4: 208.6176 - loss: 0.2391 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9026 - false_negatives_4: 212.5882 - false_positives_4: 224.0882 - loss: 0.2674
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9134 - false_negatives_4: 190.8571 - false_positives_4: 214.2857 - loss: 0.2391 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9025 - false_negatives_4: 218.6572 - false_positives_4: 231.2286 - loss: 0.2675
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9134 - false_negatives_4: 196.3611 - false_positives_4: 219.7222 - loss: 0.2391 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9024 - false_negatives_4: 224.8611 - false_positives_4: 238.3333 - loss: 0.2676
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9134 - false_negatives_4: 201.8108 - false_positives_4: 225.1351 - loss: 0.2390 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9023 - false_negatives_4: 231.0000 - false_positives_4: 245.4865 - loss: 0.2677
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9134 - false_negatives_4: 207.2368 - false_positives_4: 230.6579 - loss: 0.2391 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 6s 75ms/step - binary_accuracy: 0.9023 - false_negatives_4: 237.2368 - false_positives_4: 252.5526 - loss: 0.2678
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9134 - false_negatives_4: 212.9744 - false_positives_4: 236.1795 - loss: 0.2391 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9022 - false_negatives_4: 243.3077 - false_positives_4: 259.7692 - loss: 0.2680
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9133 - false_negatives_4: 218.6000 - false_positives_4: 241.9000 - loss: 0.2393 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9021 - false_negatives_4: 249.3500 - false_positives_4: 266.8500 - loss: 0.2681
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 74ms/step - binary_accuracy: 0.9133 - false_negatives_4: 224.4390 - false_positives_4: 247.6098 - loss: 0.2394 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9021 - false_negatives_4: 255.3659 - false_positives_4: 273.8781 - loss: 0.2682
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9132 - false_negatives_4: 230.1667 - false_positives_4: 253.5476 - loss: 0.2395 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9020 - false_negatives_4: 261.3810 - false_positives_4: 280.8333 - loss: 0.2683
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9132 - false_negatives_4: 236.0465 - false_positives_4: 259.3023 - loss: 0.2397 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9020 - false_negatives_4: 267.4651 - false_positives_4: 287.7442 - loss: 0.2683
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9131 - false_negatives_4: 241.7955 - false_positives_4: 265.1364 - loss: 0.2398 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9019 - false_negatives_4: 273.5682 - false_positives_4: 294.6818 - loss: 0.2684
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9130 - false_negatives_4: 247.4889 - false_positives_4: 271.0667 - loss: 0.2399 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9019 - false_negatives_4: 279.4889 - false_positives_4: 301.6667 - loss: 0.2685
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9130 - false_negatives_4: 253.3696 - false_positives_4: 276.9565 - loss: 0.2401 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9018 - false_negatives_4: 285.5000 - false_positives_4: 308.5217 - loss: 0.2686
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9129 - false_negatives_4: 259.1489 - false_positives_4: 282.9362 - loss: 0.2403 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9018 - false_negatives_4: 291.4255 - false_positives_4: 315.7021 - loss: 0.2687
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9129 - false_negatives_4: 265.0208 - false_positives_4: 288.7917 - loss: 0.2404 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9017 - false_negatives_4: 297.7708 - false_positives_4: 322.6667 - loss: 0.2688
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9128 - false_negatives_4: 270.8163 - false_positives_4: 294.5918 - loss: 0.2406 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9017 - false_negatives_4: 303.8979 - false_positives_4: 330.0000 - loss: 0.2690
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9128 - false_negatives_4: 276.6600 - false_positives_4: 300.4000 - loss: 0.2407 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9016 - false_negatives_4: 309.9600 - false_positives_4: 337.2600 - loss: 0.2691
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9127 - false_negatives_4: 282.4314 - false_positives_4: 306.1961 - loss: 0.2409 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 75ms/step - binary_accuracy: 0.9015 - false_negatives_4: 315.9608 - false_positives_4: 344.4510 - loss: 0.2692
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9127 - false_negatives_4: 288.0192 - false_positives_4: 312.0000 - loss: 0.2410 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9015 - false_negatives_4: 321.8654 - false_positives_4: 351.6923 - loss: 0.2693
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9127 - false_negatives_4: 293.7170 - false_positives_4: 317.8113 - loss: 0.2412 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9014 - false_negatives_4: 327.8679 - false_positives_4: 358.9245 - loss: 0.2694
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9126 - false_negatives_4: 299.2592 - false_positives_4: 323.6852 - loss: 0.2413 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9014 - false_negatives_4: 334.0000 - false_positives_4: 366.0185 - loss: 0.2695
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9126 - false_negatives_4: 305.0000 - false_positives_4: 329.4182 - loss: 0.2415 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9013 - false_negatives_4: 340.0000 - false_positives_4: 373.4546 - loss: 0.2697
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9126 - false_negatives_4: 310.5893 - false_positives_4: 335.3929 - loss: 0.2417 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9012 - false_negatives_4: 346.3393 - false_positives_4: 380.6964 - loss: 0.2698
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9125 - false_negatives_4: 316.3333 - false_positives_4: 341.2281 - loss: 0.2418 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9012 - false_negatives_4: 352.5263 - false_positives_4: 388.0526 - loss: 0.2700
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9125 - false_negatives_4: 321.9655 - false_positives_4: 347.1379 - loss: 0.2420 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9011 - false_negatives_4: 358.8448 - false_positives_4: 395.3621 - loss: 0.2701
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9125 - false_negatives_4: 327.6949 - false_positives_4: 352.9322 - loss: 0.2421 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9010 - false_negatives_4: 365.0339 - false_positives_4: 402.7627 - loss: 0.2703
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9124 - false_negatives_4: 333.3000 - false_positives_4: 358.8833 - loss: 0.2423 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9010 - false_negatives_4: 371.2833 - false_positives_4: 410.1833 - loss: 0.2704
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9124 - false_negatives_4: 338.9344 - false_positives_4: 364.7705 - loss: 0.2424 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9009 - false_negatives_4: 377.5738 - false_positives_4: 417.5246 - loss: 0.2706
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9124 - false_negatives_4: 344.5645 - false_positives_4: 370.7258 - loss: 0.2425 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9008 - false_negatives_4: 383.9032 - false_positives_4: 424.9193 - loss: 0.2708
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9123 - false_negatives_4: 350.2222 - false_positives_4: 376.6508 - loss: 0.2426 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9007 - false_negatives_4: 390.2698 - false_positives_4: 432.3175 - loss: 0.2709
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9123 - false_negatives_4: 355.8594 - false_positives_4: 382.5312 - loss: 0.2427 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 75ms/step - binary_accuracy: 0.9007 - false_negatives_4: 396.7188 - false_positives_4: 439.6875 - loss: 0.2711
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9123 - false_negatives_4: 361.5385 - false_positives_4: 388.3539 - loss: 0.2428 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9006 - false_negatives_4: 403.0615 - false_positives_4: 447.0923 - loss: 0.2712
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9123 - false_negatives_4: 367.0909 - false_positives_4: 394.2879 - loss: 0.2429 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9005 - false_negatives_4: 409.4849 - false_positives_4: 454.4243 - loss: 0.2714
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 372.7164 - false_positives_4: 400.1791 - loss: 0.2430 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9005 - false_negatives_4: 415.8358 - false_positives_4: 461.7910 - loss: 0.2715
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 378.2647 - false_positives_4: 406.0147 - loss: 0.2431 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9004 - false_negatives_4: 422.2059 - false_positives_4: 469.1176 - loss: 0.2716
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 383.7971 - false_positives_4: 411.9276 - loss: 0.2432 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9003 - false_negatives_4: 428.6232 - false_positives_4: 476.4348 - loss: 0.2718
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 389.2714 - false_positives_4: 417.8429 - loss: 0.2432 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9003 - false_negatives_4: 435.1286 - false_positives_4: 483.7143 - loss: 0.2719
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 394.7324 - false_positives_4: 423.7887 - loss: 0.2433 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9002 - false_negatives_4: 441.5916 - false_positives_4: 490.9577 - loss: 0.2720
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9122 - false_negatives_4: 400.1667 - false_positives_4: 429.6805 - loss: 0.2433 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9001 - false_negatives_4: 447.9583 - false_positives_4: 498.2500 - loss: 0.2721
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 405.6575 - false_positives_4: 435.5205 - loss: 0.2434 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9001 - false_negatives_4: 454.4247 - false_positives_4: 505.4932 - loss: 0.2722
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 411.1351 - false_positives_4: 441.3649 - loss: 0.2434 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9000 - false_negatives_4: 460.8243 - false_positives_4: 512.7973 - loss: 0.2723
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 416.5467 - false_positives_4: 447.2400 - loss: 0.2435 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.9000 - false_negatives_4: 467.2000 - false_positives_4: 520.1067 - loss: 0.2725
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 421.9737 - false_positives_4: 453.0132 - loss: 0.2435 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8999 - false_negatives_4: 473.5000 - false_positives_4: 527.5526 - loss: 0.2726
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 427.3896 - false_positives_4: 458.8312 - loss: 0.2436 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8998 - false_negatives_4: 480.0260 - false_positives_4: 534.8831 - loss: 0.2727
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 432.8462 - false_positives_4: 464.6667 - loss: 0.2436 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 75ms/step - binary_accuracy: 0.8998 - false_negatives_4: 486.4744 - false_positives_4: 542.2949 - loss: 0.2728
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 438.2785 - false_positives_4: 470.4937 - loss: 0.2437 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8997 - false_negatives_4: 492.9620 - false_positives_4: 549.6709 - loss: 0.2729
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 443.6500 - false_positives_4: 476.2750 - loss: 0.2437 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8997 - false_negatives_4: 499.3875 - false_positives_4: 557.1375 - loss: 0.2730
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 449.0617 - false_positives_4: 481.9753 - loss: 0.2437 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8996 - false_negatives_4: 505.9259 - false_positives_4: 564.5555 - loss: 0.2732
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 454.3781 - false_positives_4: 487.9268 - loss: 0.2438 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8995 - false_negatives_4: 512.4390 - false_positives_4: 571.9756 - loss: 0.2733
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 459.8675 - false_positives_4: 493.7711 - loss: 0.2438 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8995 - false_negatives_4: 518.9518 - false_positives_4: 579.4097 - loss: 0.2734
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 465.3095 - false_positives_4: 499.7619 - loss: 0.2439 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8994 - false_negatives_4: 525.4762 - false_positives_4: 586.8452 - loss: 0.2735
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9121 - false_negatives_4: 470.8235 - false_positives_4: 505.7177 - loss: 0.2440 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8993 - false_negatives_4: 532.0236 - false_positives_4: 594.3765 - loss: 0.2737
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 476.3721 - false_positives_4: 511.6628 - loss: 0.2440 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8993 - false_negatives_4: 538.4767 - false_positives_4: 601.8721 - loss: 0.2738
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 481.8965 - false_positives_4: 517.6437 - loss: 0.2441 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8992 - false_negatives_4: 544.8735 - false_positives_4: 609.3563 - loss: 0.2739
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 487.4546 - false_positives_4: 523.6136 - loss: 0.2441 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8992 - false_negatives_4: 551.2955 - false_positives_4: 616.7841 - loss: 0.2740
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 492.9438 - false_positives_4: 529.6068 - loss: 0.2442 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 75ms/step - binary_accuracy: 0.8991 - false_negatives_4: 557.6517 - false_positives_4: 624.2697 - loss: 0.2741
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 498.4667 - false_positives_4: 535.5667 - loss: 0.2442 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8991 - false_negatives_4: 563.9889 - false_positives_4: 631.7333 - loss: 0.2742
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 504.0000 - false_positives_4: 541.5385 - loss: 0.2443 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.8990 - false_negatives_4: 570.3077 - false_positives_4: 639.1978 - loss: 0.2743
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9120 - false_negatives_4: 509.4891 - false_positives_4: 547.5543 - loss: 0.2443 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8990 - false_negatives_4: 576.7500 - false_positives_4: 646.5652 - loss: 0.2744
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 515.0107 - false_positives_4: 553.5377 - loss: 0.2444 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8989 - false_negatives_4: 583.2258 - false_positives_4: 654.0645 - loss: 0.2745
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 520.4681 - false_positives_4: 559.5638 - loss: 0.2444 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8989 - false_negatives_4: 589.6808 - false_positives_4: 661.5532 - loss: 0.2746
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 526.0947 - false_positives_4: 565.5474 - loss: 0.2445 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8988 - false_negatives_4: 596.1158 - false_positives_4: 669.0421 - loss: 0.2747
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 531.6458 - false_positives_4: 571.7292 - loss: 0.2445 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8988 - false_negatives_4: 602.5000 - false_positives_4: 676.6042 - loss: 0.2748
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 537.2886 - false_positives_4: 577.8350 - loss: 0.2446 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8987 - false_negatives_4: 608.9691 - false_positives_4: 684.1547 - loss: 0.2749
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9119 - false_negatives_4: 542.8674 - false_positives_4: 583.9592 - loss: 0.2446 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8987 - false_negatives_4: 615.4081 - false_positives_4: 691.7449 - loss: 0.2750
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 548.3939 - false_positives_4: 590.0505 - loss: 0.2447 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8986 - false_negatives_4: 621.8889 - false_positives_4: 699.3232 - loss: 0.2751
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 553.8800 - false_positives_4: 596.1300 - loss: 0.2447 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8986 - false_negatives_4: 628.3500 - false_positives_4: 706.9000 - loss: 0.2752
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 559.3366 - false_positives_4: 602.1881 - loss: 0.2448 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8985 - false_negatives_4: 634.8317 - false_positives_4: 714.4852 - loss: 0.2753
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 564.8627 - false_positives_4: 608.1667 - loss: 0.2448 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 75ms/step - binary_accuracy: 0.8985 - false_negatives_4: 641.4412 - false_positives_4: 722.0588 - loss: 0.2754
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 570.3301 - false_positives_4: 614.1747 - loss: 0.2448 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8984 - false_negatives_4: 648.0097 - false_positives_4: 729.6796 - loss: 0.2754
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 575.7885 - false_positives_4: 620.1731 - loss: 0.2449 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.8984 - false_negatives_4: 654.6539 - false_positives_4: 737.2404 - loss: 0.2756
```  ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 581.2381 - false_positives_4: 626.2381 - loss: 0.2449 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8983 - false_negatives_4: 661.2095 - false_positives_4: 744.9143 - loss: 0.2757
```  ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9118 - false_negatives_4: 586.6981 - false_positives_4: 632.2264 - loss: 0.2449 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8983 - false_negatives_4: 667.8019 - false_positives_4: 752.5189 - loss: 0.2758
```  ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 592.1869 - false_positives_4: 638.2336 - loss: 0.2450 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8982 - false_negatives_4: 674.4019 - false_positives_4: 760.2056 - loss: 0.2759
```  ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 597.6574 - false_positives_4: 644.2500 - loss: 0.2450 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8982 - false_negatives_4: 680.9907 - false_positives_4: 767.8519 - loss: 0.2760
```  ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 603.0734 - false_positives_4: 650.4220 - loss: 0.2450 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8981 - false_negatives_4: 687.5596 - false_positives_4: 775.5505 - loss: 0.2761
```  ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 608.6091 - false_positives_4: 656.5000 - loss: 0.2451 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8980 - false_negatives_4: 694.0728 - false_positives_4: 783.3182 - loss: 0.2761
```  ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 614.0630 - false_positives_4: 662.6577 - loss: 0.2451 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8980 - false_negatives_4: 700.7928 - false_positives_4: 790.9820 - loss: 0.2762
```  ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 619.5357 - false_positives_4: 668.7500 - loss: 0.2451 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8979 - false_negatives_4: 707.4286 - false_positives_4: 798.6875 - loss: 0.2763
```  ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 624.9380 - false_positives_4: 674.8672 - loss: 0.2452 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8979 - false_negatives_4: 714.0531 - false_positives_4: 806.3363 - loss: 0.2764
```  ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9117 - false_negatives_4: 630.4561 - false_positives_4: 680.9298 - loss: 0.2452 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8978 - false_negatives_4: 720.6404 - false_positives_4: 814.0088 - loss: 0.2765
```  ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9116 - false_negatives_4: 635.8956 - false_positives_4: 687.1478 - loss: 0.2452 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8978 - false_negatives_4: 727.2869 - false_positives_4: 821.6609 - loss: 0.2766
```  ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9116 - false_negatives_4: 641.3879 - false_positives_4: 693.3707 - loss: 0.2453 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8977 - false_negatives_4: 733.8793 - false_positives_4: 829.4569 - loss: 0.2767
```  ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9116 - false_negatives_4: 646.8547 - false_positives_4: 699.6325 - loss: 0.2453 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.8977 - false_negatives_4: 740.5385 - false_positives_4: 837.1710 - loss: 0.2768
``` -Epoch 4: val_loss did not improve from 0.33508 +Epoch 4: val_loss did not improve from 0.35707  ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 78ms/step - binary_accuracy: 0.9116 - false_negatives_4: 657.5294 - false_positives_4: 711.8571 - loss: 0.2454 - val_binary_accuracy: 0.8502 - val_false_negatives_4: 488.0000 - val_false_positives_4: 261.0000 - val_loss: 0.3633 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 10s 81ms/step - binary_accuracy: 0.8976 - false_negatives_4: 753.5378 - false_positives_4: 852.2437 - loss: 0.2770 - val_binary_accuracy: 0.8406 - val_false_negatives_4: 530.0000 - val_false_positives_4: 267.0000 - val_loss: 0.3630
@@ -31161,829 +30210,829 @@ Epoch 5/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 10s 91ms/step - binary_accuracy: 0.9453 - false_negatives_4: 9.0000 - false_positives_4: 5.0000 - loss: 0.1607 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 10s 92ms/step - binary_accuracy: 0.9375 - false_negatives_4: 10.0000 - false_positives_4: 6.0000 - loss: 0.2054
``` - + ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9463 - false_negatives_4: 9.5000 - false_positives_4: 11.0000 - loss: 0.1656 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9336 - false_negatives_4: 13.5000 - false_positives_4: 12.5000 - loss: 0.2131
``` - + ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9447 - false_negatives_4: 13.6667 - false_positives_4: 15.0000 - loss: 0.1713 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9314 - false_negatives_4: 19.0000 - false_positives_4: 17.0000 - loss: 0.2215
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9419 - false_negatives_4: 19.0000 - false_positives_4: 19.5000 - loss: 0.1777 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9276 - false_negatives_4: 24.2500 - false_positives_4: 24.2500 - loss: 0.2299
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9399 - false_negatives_4: 23.2000 - false_positives_4: 25.0000 - loss: 0.1827 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9252 - false_negatives_4: 30.0000 - false_positives_4: 30.4000 - loss: 0.2355
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9377 - false_negatives_4: 29.1667 - false_positives_4: 29.8333 - loss: 0.1868 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9239 - false_negatives_4: 35.3333 - false_positives_4: 36.1667 - loss: 0.2378
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9357 - false_negatives_4: 35.0000 - false_positives_4: 35.0000 - loss: 0.1894 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9227 - false_negatives_4: 41.0000 - false_positives_4: 41.8571 - loss: 0.2394
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9342 - false_negatives_4: 39.8750 - false_positives_4: 40.8750 - loss: 0.1916 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9214 - false_negatives_4: 45.8750 - false_positives_4: 49.1250 - loss: 0.2413
```  ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9332 - false_negatives_4: 44.8889 - false_positives_4: 46.1111 - loss: 0.1936 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9203 - false_negatives_4: 51.7778 - false_positives_4: 55.3333 - loss: 0.2423
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9324 - false_negatives_4: 49.9000 - false_positives_4: 51.1000 - loss: 0.1953 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9193 - false_negatives_4: 57.3000 - false_positives_4: 61.9000 - loss: 0.2432
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9318 - false_negatives_4: 54.2727 - false_positives_4: 56.5455 - loss: 0.1967 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9185 - false_negatives_4: 62.9091 - false_positives_4: 68.5455 - loss: 0.2438
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9314 - false_negatives_4: 59.1667 - false_positives_4: 61.1667 - loss: 0.1977 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9178 - false_negatives_4: 68.1667 - false_positives_4: 75.3333 - loss: 0.2444
```  ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9309 - false_negatives_4: 63.8462 - false_positives_4: 66.3846 - loss: 0.1988 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9171 - false_negatives_4: 74.3846 - false_positives_4: 81.5385 - loss: 0.2453
```  ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9307 - false_negatives_4: 68.0000 - false_positives_4: 71.5714 - loss: 0.1995 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9163 - false_negatives_4: 80.2857 - false_positives_4: 88.5000 - loss: 0.2464
```  ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9305 - false_negatives_4: 72.2667 - false_positives_4: 76.5333 - loss: 0.2000 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9157 - false_negatives_4: 86.4667 - false_positives_4: 94.8000 - loss: 0.2473
```  ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9303 - false_negatives_4: 76.3750 - false_positives_4: 81.5000 - loss: 0.2003 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9153 - false_negatives_4: 92.0000 - false_positives_4: 101.2500 - loss: 0.2480
``` - + ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9303 - false_negatives_4: 80.1765 - false_positives_4: 86.2941 - loss: 0.2004 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9149 - false_negatives_4: 97.8235 - false_positives_4: 107.2353 - loss: 0.2486
``` - + ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9302 - false_negatives_4: 84.2778 - false_positives_4: 91.2222 - loss: 0.2007 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9146 - false_negatives_4: 103.3333 - false_positives_4: 113.8333 - loss: 0.2493
``` - + ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9301 - false_negatives_4: 88.4737 - false_positives_4: 96.2105 - loss: 0.2010 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9142 - false_negatives_4: 109.0000 - false_positives_4: 120.1579 - loss: 0.2498
``` - + ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9300 - false_negatives_4: 93.1000 - false_positives_4: 100.9500 - loss: 0.2013 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9139 - false_negatives_4: 114.9500 - false_positives_4: 126.2500 - loss: 0.2502
``` - + ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9298 - false_negatives_4: 97.3810 - false_positives_4: 106.2857 - loss: 0.2017 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9137 - false_negatives_4: 120.4762 - false_positives_4: 132.6667 - loss: 0.2505
``` - + ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9295 - false_negatives_4: 102.5000 - false_positives_4: 111.2727 - loss: 0.2021 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9134 - false_negatives_4: 126.3636 - false_positives_4: 138.6818 - loss: 0.2509
```  ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9293 - false_negatives_4: 107.3478 - false_positives_4: 116.5652 - loss: 0.2026 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9132 - false_negatives_4: 132.0870 - false_positives_4: 145.0870 - loss: 0.2512
```  ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9291 - false_negatives_4: 112.2083 - false_positives_4: 121.4583 - loss: 0.2029 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9130 - false_negatives_4: 138.1667 - false_positives_4: 151.0417 - loss: 0.2515
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9289 - false_negatives_4: 117.1600 - false_positives_4: 126.6000 - loss: 0.2033 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9127 - false_negatives_4: 143.9600 - false_positives_4: 157.4000 - loss: 0.2519
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9287 - false_negatives_4: 122.2308 - false_positives_4: 131.7308 - loss: 0.2037 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 7s 77ms/step - binary_accuracy: 0.9125 - false_negatives_4: 150.0000 - false_positives_4: 163.6154 - loss: 0.2523
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9286 - false_negatives_4: 127.1852 - false_positives_4: 136.6667 - loss: 0.2040 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.9123 - false_negatives_4: 155.8519 - false_positives_4: 170.1481 - loss: 0.2527
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9285 - false_negatives_4: 131.8571 - false_positives_4: 141.6429 - loss: 0.2043 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 77ms/step - binary_accuracy: 0.9121 - false_negatives_4: 162.0000 - false_positives_4: 176.4643 - loss: 0.2530
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9284 - false_negatives_4: 136.5172 - false_positives_4: 146.4138 - loss: 0.2045 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9118 - false_negatives_4: 167.8276 - false_positives_4: 183.1724 - loss: 0.2534
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9283 - false_negatives_4: 141.2667 - false_positives_4: 151.2333 - loss: 0.2047 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9116 - false_negatives_4: 173.9333 - false_positives_4: 189.7667 - loss: 0.2538
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9282 - false_negatives_4: 145.9355 - false_positives_4: 156.2258 - loss: 0.2049 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9114 - false_negatives_4: 179.8710 - false_positives_4: 196.5484 - loss: 0.2542
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9281 - false_negatives_4: 150.6562 - false_positives_4: 161.0938 - loss: 0.2050 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9111 - false_negatives_4: 185.6875 - false_positives_4: 203.4688 - loss: 0.2545
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9281 - false_negatives_4: 155.2424 - false_positives_4: 166.1515 - loss: 0.2053 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9109 - false_negatives_4: 191.7273 - false_positives_4: 210.1818 - loss: 0.2548
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9279 - false_negatives_4: 160.2353 - false_positives_4: 171.1765 - loss: 0.2056 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9107 - false_negatives_4: 197.5588 - false_positives_4: 217.2647 - loss: 0.2552
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9278 - false_negatives_4: 165.0000 - false_positives_4: 176.4286 - loss: 0.2059 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9105 - false_negatives_4: 203.4857 - false_positives_4: 224.2000 - loss: 0.2555
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9277 - false_negatives_4: 170.0278 - false_positives_4: 181.5556 - loss: 0.2062 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9103 - false_negatives_4: 209.5000 - false_positives_4: 231.0000 - loss: 0.2558
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9276 - false_negatives_4: 174.8378 - false_positives_4: 186.8919 - loss: 0.2065 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9101 - false_negatives_4: 215.2432 - false_positives_4: 237.9189 - loss: 0.2561
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9274 - false_negatives_4: 179.6842 - false_positives_4: 192.2368 - loss: 0.2068 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9100 - false_negatives_4: 221.1316 - false_positives_4: 244.7632 - loss: 0.2563
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9273 - false_negatives_4: 184.7692 - false_positives_4: 197.4872 - loss: 0.2071 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9098 - false_negatives_4: 227.2051 - false_positives_4: 251.4359 - loss: 0.2565
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9272 - false_negatives_4: 189.8250 - false_positives_4: 203.0000 - loss: 0.2074 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9096 - false_negatives_4: 233.1750 - false_positives_4: 258.1250 - loss: 0.2568
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9270 - false_negatives_4: 194.8049 - false_positives_4: 208.4878 - loss: 0.2077 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9095 - false_negatives_4: 239.1707 - false_positives_4: 264.6585 - loss: 0.2570
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9269 - false_negatives_4: 199.7619 - false_positives_4: 213.9048 - loss: 0.2079 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9094 - false_negatives_4: 245.0952 - false_positives_4: 271.1905 - loss: 0.2571
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9268 - false_negatives_4: 204.6977 - false_positives_4: 219.3256 - loss: 0.2082 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9093 - false_negatives_4: 251.1163 - false_positives_4: 277.7442 - loss: 0.2573
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 209.6364 - false_positives_4: 224.7045 - loss: 0.2085 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9091 - false_negatives_4: 257.2500 - false_positives_4: 284.2954 - loss: 0.2574
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 214.4222 - false_positives_4: 230.0222 - loss: 0.2088 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9090 - false_negatives_4: 263.3556 - false_positives_4: 290.9333 - loss: 0.2576
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9265 - false_negatives_4: 219.2826 - false_positives_4: 235.2609 - loss: 0.2090 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9089 - false_negatives_4: 269.4131 - false_positives_4: 297.5435 - loss: 0.2578
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9264 - false_negatives_4: 224.0638 - false_positives_4: 240.5745 - loss: 0.2093 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9088 - false_negatives_4: 275.4681 - false_positives_4: 304.0851 - loss: 0.2579
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9264 - false_negatives_4: 228.8750 - false_positives_4: 245.9167 - loss: 0.2096 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9087 - false_negatives_4: 281.5208 - false_positives_4: 310.8125 - loss: 0.2581
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9263 - false_negatives_4: 233.7143 - false_positives_4: 251.4694 - loss: 0.2098 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9085 - false_negatives_4: 287.8776 - false_positives_4: 317.4286 - loss: 0.2582
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9262 - false_negatives_4: 238.6000 - false_positives_4: 256.9800 - loss: 0.2101 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9084 - false_negatives_4: 294.0000 - false_positives_4: 324.6200 - loss: 0.2585
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9261 - false_negatives_4: 243.3725 - false_positives_4: 262.5490 - loss: 0.2103 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9082 - false_negatives_4: 300.7451 - false_positives_4: 331.6078 - loss: 0.2587
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9260 - false_negatives_4: 248.1731 - false_positives_4: 268.0000 - loss: 0.2106 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9080 - false_negatives_4: 307.3654 - false_positives_4: 338.8846 - loss: 0.2590
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9259 - false_negatives_4: 252.8491 - false_positives_4: 273.8113 - loss: 0.2108 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9078 - false_negatives_4: 314.0566 - false_positives_4: 346.1132 - loss: 0.2593
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9258 - false_negatives_4: 257.9815 - false_positives_4: 279.4445 - loss: 0.2111 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9076 - false_negatives_4: 320.6296 - false_positives_4: 353.3333 - loss: 0.2595
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9257 - false_negatives_4: 262.9818 - false_positives_4: 285.4364 - loss: 0.2113 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9075 - false_negatives_4: 327.3273 - false_positives_4: 360.4546 - loss: 0.2598
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9255 - false_negatives_4: 268.1429 - false_positives_4: 291.2857 - loss: 0.2116 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9073 - false_negatives_4: 333.9464 - false_positives_4: 367.5893 - loss: 0.2600
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9254 - false_negatives_4: 273.2281 - false_positives_4: 297.2632 - loss: 0.2119 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9071 - false_negatives_4: 340.7018 - false_positives_4: 374.6842 - loss: 0.2602
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9253 - false_negatives_4: 278.4138 - false_positives_4: 303.2414 - loss: 0.2122 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9070 - false_negatives_4: 347.4138 - false_positives_4: 381.8793 - loss: 0.2605
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9252 - false_negatives_4: 283.6610 - false_positives_4: 309.1356 - loss: 0.2125 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9068 - false_negatives_4: 354.1526 - false_positives_4: 388.9322 - loss: 0.2607
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9250 - false_negatives_4: 288.9333 - false_positives_4: 315.0167 - loss: 0.2128 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9066 - false_negatives_4: 360.8000 - false_positives_4: 396.1333 - loss: 0.2609
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9249 - false_negatives_4: 294.1803 - false_positives_4: 320.9344 - loss: 0.2131 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9065 - false_negatives_4: 367.4262 - false_positives_4: 403.3443 - loss: 0.2611
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9248 - false_negatives_4: 299.3387 - false_positives_4: 326.8710 - loss: 0.2134 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9064 - false_negatives_4: 374.0000 - false_positives_4: 410.5161 - loss: 0.2613
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9247 - false_negatives_4: 304.5079 - false_positives_4: 332.6825 - loss: 0.2136 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9062 - false_negatives_4: 380.5079 - false_positives_4: 417.6667 - loss: 0.2615
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9246 - false_negatives_4: 309.5312 - false_positives_4: 338.6406 - loss: 0.2139 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 387.0781 - false_positives_4: 424.7656 - loss: 0.2617
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9245 - false_negatives_4: 314.6154 - false_positives_4: 344.5385 - loss: 0.2142 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 393.5538 - false_positives_4: 431.9692 - loss: 0.2619
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9244 - false_negatives_4: 319.6212 - false_positives_4: 350.4849 - loss: 0.2144 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9058 - false_negatives_4: 400.0151 - false_positives_4: 439.0757 - loss: 0.2620
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9243 - false_negatives_4: 324.6866 - false_positives_4: 356.3881 - loss: 0.2147 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9057 - false_negatives_4: 406.4627 - false_positives_4: 446.1194 - loss: 0.2622
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9242 - false_negatives_4: 329.7353 - false_positives_4: 362.2941 - loss: 0.2149 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9056 - false_negatives_4: 412.8529 - false_positives_4: 453.2059 - loss: 0.2623
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9241 - false_negatives_4: 334.8696 - false_positives_4: 368.1304 - loss: 0.2151 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9055 - false_negatives_4: 419.2174 - false_positives_4: 460.3478 - loss: 0.2625
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9240 - false_negatives_4: 339.9714 - false_positives_4: 374.0714 - loss: 0.2154 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9054 - false_negatives_4: 425.5000 - false_positives_4: 467.4857 - loss: 0.2626
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9240 - false_negatives_4: 345.1549 - false_positives_4: 379.9577 - loss: 0.2156 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9053 - false_negatives_4: 431.9718 - false_positives_4: 474.5775 - loss: 0.2628
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9239 - false_negatives_4: 350.3055 - false_positives_4: 385.9305 - loss: 0.2159 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9052 - false_negatives_4: 438.3611 - false_positives_4: 481.7917 - loss: 0.2629
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9238 - false_negatives_4: 355.3972 - false_positives_4: 391.9041 - loss: 0.2161 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9051 - false_negatives_4: 444.8630 - false_positives_4: 488.9726 - loss: 0.2631
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9237 - false_negatives_4: 360.5135 - false_positives_4: 397.8649 - loss: 0.2163 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9050 - false_negatives_4: 451.2297 - false_positives_4: 496.2027 - loss: 0.2632
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9236 - false_negatives_4: 365.5467 - false_positives_4: 403.7333 - loss: 0.2165 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9049 - false_negatives_4: 457.5867 - false_positives_4: 503.4267 - loss: 0.2634
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9235 - false_negatives_4: 370.5921 - false_positives_4: 409.6711 - loss: 0.2167 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9048 - false_negatives_4: 463.8684 - false_positives_4: 510.6316 - loss: 0.2635
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9235 - false_negatives_4: 375.6494 - false_positives_4: 415.4935 - loss: 0.2169 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9047 - false_negatives_4: 470.1818 - false_positives_4: 517.7792 - loss: 0.2637
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9234 - false_negatives_4: 380.6538 - false_positives_4: 421.2436 - loss: 0.2171 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9046 - false_negatives_4: 476.4359 - false_positives_4: 525.0513 - loss: 0.2638
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9233 - false_negatives_4: 385.5949 - false_positives_4: 426.9747 - loss: 0.2173 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9045 - false_negatives_4: 482.7342 - false_positives_4: 532.2405 - loss: 0.2639
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9233 - false_negatives_4: 390.6875 - false_positives_4: 432.6250 - loss: 0.2174 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9045 - false_negatives_4: 488.8875 - false_positives_4: 539.5375 - loss: 0.2640
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9232 - false_negatives_4: 395.6790 - false_positives_4: 438.2963 - loss: 0.2176 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9044 - false_negatives_4: 495.2099 - false_positives_4: 546.7778 - loss: 0.2642
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9232 - false_negatives_4: 400.6829 - false_positives_4: 443.9390 - loss: 0.2178 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9043 - false_negatives_4: 501.4268 - false_positives_4: 554.1097 - loss: 0.2643
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9231 - false_negatives_4: 405.6506 - false_positives_4: 449.5663 - loss: 0.2179 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9042 - false_negatives_4: 507.6385 - false_positives_4: 561.4578 - loss: 0.2644
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9230 - false_negatives_4: 410.6429 - false_positives_4: 455.1786 - loss: 0.2181 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9041 - false_negatives_4: 513.7738 - false_positives_4: 568.7619 - loss: 0.2645
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9230 - false_negatives_4: 415.6353 - false_positives_4: 460.8118 - loss: 0.2182 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9040 - false_negatives_4: 519.9059 - false_positives_4: 576.1294 - loss: 0.2646
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9229 - false_negatives_4: 420.5698 - false_positives_4: 466.4884 - loss: 0.2184 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9040 - false_negatives_4: 526.0349 - false_positives_4: 583.4418 - loss: 0.2647
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9229 - false_negatives_4: 425.5402 - false_positives_4: 472.0575 - loss: 0.2185 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9039 - false_negatives_4: 532.1494 - false_positives_4: 590.7701 - loss: 0.2648
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9229 - false_negatives_4: 430.4432 - false_positives_4: 477.7159 - loss: 0.2187 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9038 - false_negatives_4: 538.2159 - false_positives_4: 598.1477 - loss: 0.2650
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9228 - false_negatives_4: 435.4944 - false_positives_4: 483.2921 - loss: 0.2188 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9038 - false_negatives_4: 544.5843 - false_positives_4: 605.4269 - loss: 0.2651
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9228 - false_negatives_4: 440.4778 - false_positives_4: 488.9222 - loss: 0.2189 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9037 - false_negatives_4: 550.8555 - false_positives_4: 612.8555 - loss: 0.2652
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9227 - false_negatives_4: 445.5604 - false_positives_4: 494.4945 - loss: 0.2191 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9036 - false_negatives_4: 557.2088 - false_positives_4: 620.2198 - loss: 0.2653
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9227 - false_negatives_4: 450.6087 - false_positives_4: 500.0761 - loss: 0.2192 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9035 - false_negatives_4: 563.5652 - false_positives_4: 627.6196 - loss: 0.2654
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9226 - false_negatives_4: 455.7097 - false_positives_4: 505.6559 - loss: 0.2193 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9034 - false_negatives_4: 569.8925 - false_positives_4: 634.9893 - loss: 0.2655
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9226 - false_negatives_4: 460.7766 - false_positives_4: 511.2553 - loss: 0.2195 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9034 - false_negatives_4: 576.2021 - false_positives_4: 642.3085 - loss: 0.2656
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9225 - false_negatives_4: 465.8947 - false_positives_4: 516.8632 - loss: 0.2196 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9033 - false_negatives_4: 582.5158 - false_positives_4: 649.5684 - loss: 0.2657
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9225 - false_negatives_4: 470.9062 - false_positives_4: 522.4583 - loss: 0.2197 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9032 - false_negatives_4: 588.8229 - false_positives_4: 656.8229 - loss: 0.2658
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9224 - false_negatives_4: 476.0000 - false_positives_4: 528.0309 - loss: 0.2198 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9032 - false_negatives_4: 595.1547 - false_positives_4: 664.0721 - loss: 0.2659
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9224 - false_negatives_4: 481.0918 - false_positives_4: 533.6021 - loss: 0.2199 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9031 - false_negatives_4: 601.5102 - false_positives_4: 671.3062 - loss: 0.2660
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9224 - false_negatives_4: 486.2020 - false_positives_4: 539.1616 - loss: 0.2201 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9030 - false_negatives_4: 607.9091 - false_positives_4: 678.4545 - loss: 0.2661
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9223 - false_negatives_4: 491.2600 - false_positives_4: 544.7900 - loss: 0.2202 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9030 - false_negatives_4: 614.2500 - false_positives_4: 685.6100 - loss: 0.2662
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9223 - false_negatives_4: 496.3564 - false_positives_4: 550.3861 - loss: 0.2203 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9029 - false_negatives_4: 620.6337 - false_positives_4: 692.7822 - loss: 0.2663
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9222 - false_negatives_4: 501.5196 - false_positives_4: 555.9020 - loss: 0.2204 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9029 - false_negatives_4: 627.0294 - false_positives_4: 699.8726 - loss: 0.2664
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9222 - false_negatives_4: 506.6117 - false_positives_4: 561.5437 - loss: 0.2206 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9028 - false_negatives_4: 633.3398 - false_positives_4: 707.1068 - loss: 0.2664
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9222 - false_negatives_4: 511.7212 - false_positives_4: 567.1827 - loss: 0.2207 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9027 - false_negatives_4: 639.8365 - false_positives_4: 714.2981 - loss: 0.2665
```  ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9221 - false_negatives_4: 516.8286 - false_positives_4: 572.8095 - loss: 0.2208 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9027 - false_negatives_4: 646.2476 - false_positives_4: 721.5143 - loss: 0.2666
```  ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9221 - false_negatives_4: 521.9151 - false_positives_4: 578.4056 - loss: 0.2209 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9026 - false_negatives_4: 652.6604 - false_positives_4: 728.6509 - loss: 0.2667
```  ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9220 - false_negatives_4: 527.0093 - false_positives_4: 584.0093 - loss: 0.2210 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9026 - false_negatives_4: 659.0468 - false_positives_4: 735.8691 - loss: 0.2667
```  ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9220 - false_negatives_4: 532.1759 - false_positives_4: 589.5741 - loss: 0.2212 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9025 - false_negatives_4: 665.4815 - false_positives_4: 743.0555 - loss: 0.2668
```  ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9220 - false_negatives_4: 537.3211 - false_positives_4: 595.1927 - loss: 0.2213 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9024 - false_negatives_4: 671.8532 - false_positives_4: 750.2844 - loss: 0.2669
```  ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9219 - false_negatives_4: 542.5364 - false_positives_4: 600.7273 - loss: 0.2214 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9024 - false_negatives_4: 678.2091 - false_positives_4: 757.4818 - loss: 0.2670
```  ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9219 - false_negatives_4: 547.7027 - false_positives_4: 606.3333 - loss: 0.2215 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9023 - false_negatives_4: 684.5676 - false_positives_4: 764.6396 - loss: 0.2670
```  ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9219 - false_negatives_4: 552.9196 - false_positives_4: 611.8750 - loss: 0.2216 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9023 - false_negatives_4: 690.8661 - false_positives_4: 771.9196 - loss: 0.2671
```  ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9218 - false_negatives_4: 558.1062 - false_positives_4: 617.5044 - loss: 0.2217 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9022 - false_negatives_4: 697.2390 - false_positives_4: 779.1859 - loss: 0.2672
```  ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9218 - false_negatives_4: 563.3421 - false_positives_4: 623.0965 - loss: 0.2218 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9022 - false_negatives_4: 703.5877 - false_positives_4: 786.4649 - loss: 0.2672
```  ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9217 - false_negatives_4: 568.5217 - false_positives_4: 628.7043 - loss: 0.2219 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9021 - false_negatives_4: 709.9130 - false_positives_4: 793.7304 - loss: 0.2673
```  ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9217 - false_negatives_4: 573.6810 - false_positives_4: 634.2759 - loss: 0.2220 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9021 - false_negatives_4: 716.1983 - false_positives_4: 801.0086 - loss: 0.2674
```  ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9217 - false_negatives_4: 578.7949 - false_positives_4: 639.8461 - loss: 0.2221 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9020 - false_negatives_4: 722.5214 - false_positives_4: 808.2308 - loss: 0.2674
``` -Epoch 5: val_loss did not improve from 0.33508 +Epoch 5: val_loss did not improve from 0.35707  ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 78ms/step - binary_accuracy: 0.9216 - false_negatives_4: 588.8151 - false_positives_4: 650.7227 - loss: 0.2223 - val_binary_accuracy: 0.8564 - val_false_negatives_4: 396.0000 - val_false_positives_4: 322.0000 - val_loss: 0.3762 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 10s 82ms/step - binary_accuracy: 0.9019 - false_negatives_4: 734.8655 - false_positives_4: 822.4117 - loss: 0.2676 - val_binary_accuracy: 0.8330 - val_false_negatives_4: 592.0000 - val_false_positives_4: 243.0000 - val_loss: 0.3805
@@ -31993,829 +31042,829 @@ Epoch 6/20 ```
- 1/118 ━━━━━━━━━━━━━━━━━━━━ 10s 92ms/step - binary_accuracy: 0.9219 - false_negatives_4: 10.0000 - false_positives_4: 10.0000 - loss: 0.1936 + 1/118 ━━━━━━━━━━━━━━━━━━━━ 11s 95ms/step - binary_accuracy: 0.8906 - false_negatives_4: 20.0000 - false_positives_4: 8.0000 - loss: 0.2467
``` - + ```
- 2/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9287 - false_negatives_4: 12.5000 - false_positives_4: 14.0000 - loss: 0.1945 + 2/118 ━━━━━━━━━━━━━━━━━━━━ 9s 78ms/step - binary_accuracy: 0.9004 - false_negatives_4: 22.0000 - false_positives_4: 15.0000 - loss: 0.2441
```  ```
- 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9303 - false_negatives_4: 15.0000 - false_positives_4: 19.6667 - loss: 0.1967 + 3/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9067 - false_negatives_4: 26.0000 - false_positives_4: 19.3333 - loss: 0.2378
```  ```
- 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 74ms/step - binary_accuracy: 0.9307 - false_negatives_4: 19.5000 - false_positives_4: 24.0000 - loss: 0.1964 + 4/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9071 - false_negatives_4: 31.7500 - false_positives_4: 25.7500 - loss: 0.2397
```  ```
- 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9309 - false_negatives_4: 23.8000 - false_positives_4: 28.4000 - loss: 0.1978 + 5/118 ━━━━━━━━━━━━━━━━━━━━ 8s 77ms/step - binary_accuracy: 0.9071 - false_negatives_4: 38.8000 - false_positives_4: 31.0000 - loss: 0.2410
```  ```
- 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9314 - false_negatives_4: 27.5000 - false_positives_4: 33.0000 - loss: 0.1979 + 6/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9075 - false_negatives_4: 44.1667 - false_positives_4: 37.1667 - loss: 0.2408
```  ```
- 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9319 - false_negatives_4: 31.5714 - false_positives_4: 37.0000 - loss: 0.1971 + 7/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9075 - false_negatives_4: 50.5714 - false_positives_4: 42.7143 - loss: 0.2404
```  ```
- 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 73ms/step - binary_accuracy: 0.9324 - false_negatives_4: 34.6250 - false_positives_4: 41.7500 - loss: 0.1962 + 8/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9074 - false_negatives_4: 57.3750 - false_positives_4: 48.2500 - loss: 0.2406
```  ```
- 9/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9326 - false_negatives_4: 38.4444 - false_positives_4: 46.3333 - loss: 0.1964 + 9/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9068 - false_negatives_4: 64.8889 - false_positives_4: 54.1111 - loss: 0.2419
```  ```
- 10/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9322 - false_negatives_4: 41.6000 - false_positives_4: 52.9000 - loss: 0.1973 + 10/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 71.7000 - false_positives_4: 61.2000 - loss: 0.2433
```  ```
- 11/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9316 - false_negatives_4: 46.4545 - false_positives_4: 58.5455 - loss: 0.1984 + 11/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9052 - false_negatives_4: 79.5455 - false_positives_4: 67.7273 - loss: 0.2449
```  ```
- 12/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9312 - false_negatives_4: 50.9167 - false_positives_4: 64.0000 - loss: 0.1991 + 12/118 ━━━━━━━━━━━━━━━━━━━━ 8s 76ms/step - binary_accuracy: 0.9044 - false_negatives_4: 86.5833 - false_positives_4: 74.9167 - loss: 0.2464
```  ```
- 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9309 - false_negatives_4: 55.2308 - false_positives_4: 69.3846 - loss: 0.1996 + 13/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9037 - false_negatives_4: 93.7692 - false_positives_4: 82.0769 - loss: 0.2477
```  ```
- 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9307 - false_negatives_4: 59.8571 - false_positives_4: 74.4286 - loss: 0.1999 + 14/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9033 - false_negatives_4: 100.5000 - false_positives_4: 89.0714 - loss: 0.2484
``` - + ```
- 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9305 - false_negatives_4: 64.2000 - false_positives_4: 79.6000 - loss: 0.2003 + 15/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9029 - false_negatives_4: 107.1333 - false_positives_4: 96.2000 - loss: 0.2491
``` - + ```
- 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9304 - false_negatives_4: 68.6250 - false_positives_4: 84.5000 - loss: 0.2006 + 16/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9026 - false_negatives_4: 113.6875 - false_positives_4: 102.9375 - loss: 0.2496
``` - + ```
- 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9303 - false_negatives_4: 72.8824 - false_positives_4: 89.5294 - loss: 0.2009 + 17/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9023 - false_negatives_4: 119.5882 - false_positives_4: 110.3529 - loss: 0.2501
``` - + ```
- 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9302 - false_negatives_4: 77.3889 - false_positives_4: 94.1667 - loss: 0.2012 + 18/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9022 - false_negatives_4: 125.7778 - false_positives_4: 117.0556 - loss: 0.2504
``` - + ```
- 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9302 - false_negatives_4: 81.5789 - false_positives_4: 98.8421 - loss: 0.2016 + 19/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9022 - false_negatives_4: 131.6316 - false_positives_4: 123.5789 - loss: 0.2504
``` - + ```
- 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9302 - false_negatives_4: 85.7500 - false_positives_4: 103.3000 - loss: 0.2018 + 20/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9023 - false_negatives_4: 136.9500 - false_positives_4: 129.8500 - loss: 0.2502
``` - + ```
- 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9302 - false_negatives_4: 89.8095 - false_positives_4: 108.1905 - loss: 0.2022 + 21/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9025 - false_negatives_4: 142.2381 - false_positives_4: 135.7143 - loss: 0.2499
``` - + ```
- 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 73ms/step - binary_accuracy: 0.9301 - false_negatives_4: 94.5000 - false_positives_4: 112.8636 - loss: 0.2026 + 22/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9028 - false_negatives_4: 147.3636 - false_positives_4: 141.5455 - loss: 0.2495
``` - + ```
- 23/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9300 - false_negatives_4: 98.9130 - false_positives_4: 117.8696 - loss: 0.2030 + 23/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9030 - false_negatives_4: 152.3478 - false_positives_4: 147.3044 - loss: 0.2490
``` - + ```
- 24/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9299 - false_negatives_4: 103.4583 - false_positives_4: 122.8750 - loss: 0.2034 + 24/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9033 - false_negatives_4: 157.4167 - false_positives_4: 153.0000 - loss: 0.2487
```  ```
- 25/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9298 - false_negatives_4: 108.0000 - false_positives_4: 127.6800 - loss: 0.2037 + 25/118 ━━━━━━━━━━━━━━━━━━━━ 7s 76ms/step - binary_accuracy: 0.9035 - false_negatives_4: 162.2400 - false_positives_4: 158.8400 - loss: 0.2484
```  ```
- 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9298 - false_negatives_4: 112.3846 - false_positives_4: 132.6538 - loss: 0.2040 + 26/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9037 - false_negatives_4: 167.6538 - false_positives_4: 164.5000 - loss: 0.2481
```  ```
- 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9297 - false_negatives_4: 116.9630 - false_positives_4: 137.4444 - loss: 0.2043 + 27/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9039 - false_negatives_4: 172.9259 - false_positives_4: 170.7407 - loss: 0.2480
```  ```
- 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9297 - false_negatives_4: 121.3571 - false_positives_4: 142.3571 - loss: 0.2045 + 28/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9040 - false_negatives_4: 178.2500 - false_positives_4: 176.6786 - loss: 0.2479
```  ```
- 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 125.6897 - false_positives_4: 147.1035 - loss: 0.2047 + 29/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9042 - false_negatives_4: 183.3793 - false_positives_4: 182.5517 - loss: 0.2478
```  ```
- 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 129.8667 - false_positives_4: 151.9000 - loss: 0.2048 + 30/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9043 - false_negatives_4: 188.5333 - false_positives_4: 188.5000 - loss: 0.2476
```  ```
- 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 134.2258 - false_positives_4: 156.6129 - loss: 0.2049 + 31/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9045 - false_negatives_4: 193.5161 - false_positives_4: 194.5484 - loss: 0.2475
```  ```
- 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 138.5938 - false_positives_4: 161.3125 - loss: 0.2050 + 32/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9047 - false_negatives_4: 198.6875 - false_positives_4: 200.3750 - loss: 0.2473
```  ```
- 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 142.9697 - false_positives_4: 165.9697 - loss: 0.2050 + 33/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9048 - false_negatives_4: 203.8182 - false_positives_4: 206.3030 - loss: 0.2471
```  ```
- 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 147.3529 - false_positives_4: 170.6176 - loss: 0.2051 + 34/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9050 - false_negatives_4: 209.0294 - false_positives_4: 212.0882 - loss: 0.2470
```  ```
- 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9296 - false_negatives_4: 151.6857 - false_positives_4: 175.2571 - loss: 0.2052 + 35/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9051 - false_negatives_4: 214.0000 - false_positives_4: 218.2857 - loss: 0.2469
```  ```
- 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 73ms/step - binary_accuracy: 0.9295 - false_negatives_4: 156.1111 - false_positives_4: 179.9722 - loss: 0.2053 + 36/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9052 - false_negatives_4: 219.5556 - false_positives_4: 224.2500 - loss: 0.2470
```  ```
- 37/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9295 - false_negatives_4: 160.6487 - false_positives_4: 184.6216 - loss: 0.2054 + 37/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9053 - false_negatives_4: 225.0540 - false_positives_4: 230.1892 - loss: 0.2470
```  ```
- 38/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9295 - false_negatives_4: 165.0789 - false_positives_4: 189.6316 - loss: 0.2056 + 38/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9053 - false_negatives_4: 230.5263 - false_positives_4: 236.2368 - loss: 0.2470
```  ```
- 39/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9294 - false_negatives_4: 170.0256 - false_positives_4: 194.5128 - loss: 0.2058 + 39/118 ━━━━━━━━━━━━━━━━━━━━ 6s 76ms/step - binary_accuracy: 0.9054 - false_negatives_4: 236.0769 - false_positives_4: 242.2051 - loss: 0.2471
```  ```
- 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9293 - false_negatives_4: 174.8750 - false_positives_4: 199.7500 - loss: 0.2061 + 40/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9055 - false_negatives_4: 241.5000 - false_positives_4: 248.1000 - loss: 0.2471
```  ```
- 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9292 - false_negatives_4: 179.8781 - false_positives_4: 205.0244 - loss: 0.2064 + 41/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9056 - false_negatives_4: 246.9512 - false_positives_4: 254.1219 - loss: 0.2472
```  ```
- 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9290 - false_negatives_4: 184.7857 - false_positives_4: 210.3095 - loss: 0.2066 + 42/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9057 - false_negatives_4: 252.3333 - false_positives_4: 260.0952 - loss: 0.2472
```  ```
- 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9289 - false_negatives_4: 189.7442 - false_positives_4: 215.5581 - loss: 0.2069 + 43/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9057 - false_negatives_4: 257.8140 - false_positives_4: 266.1628 - loss: 0.2473
```  ```
- 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9288 - false_negatives_4: 194.6364 - false_positives_4: 220.7273 - loss: 0.2071 + 44/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9058 - false_negatives_4: 263.2727 - false_positives_4: 272.2273 - loss: 0.2473
```  ```
- 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9287 - false_negatives_4: 199.4222 - false_positives_4: 226.0667 - loss: 0.2073 + 45/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9058 - false_negatives_4: 268.7333 - false_positives_4: 278.3778 - loss: 0.2474
```  ```
- 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9287 - false_negatives_4: 204.1304 - false_positives_4: 231.3044 - loss: 0.2075 + 46/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 274.3478 - false_positives_4: 284.4565 - loss: 0.2474
```  ```
- 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9286 - false_negatives_4: 208.8085 - false_positives_4: 236.4894 - loss: 0.2077 + 47/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 279.8723 - false_positives_4: 290.5957 - loss: 0.2475
```  ```
- 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9285 - false_negatives_4: 213.3750 - false_positives_4: 241.7292 - loss: 0.2078 + 48/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 285.5208 - false_positives_4: 296.7917 - loss: 0.2476
```  ```
- 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 73ms/step - binary_accuracy: 0.9284 - false_negatives_4: 218.0612 - false_positives_4: 246.9184 - loss: 0.2080 + 49/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 291.1224 - false_positives_4: 302.9796 - loss: 0.2477
```  ```
- 50/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9284 - false_negatives_4: 222.6000 - false_positives_4: 252.0800 - loss: 0.2081 + 50/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 297.0600 - false_positives_4: 309.1600 - loss: 0.2478
```  ```
- 51/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9283 - false_negatives_4: 227.2353 - false_positives_4: 257.1961 - loss: 0.2083 + 51/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 302.9804 - false_positives_4: 315.5294 - loss: 0.2480
```  ```
- 52/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9283 - false_negatives_4: 231.8846 - false_positives_4: 262.2500 - loss: 0.2084 + 52/118 ━━━━━━━━━━━━━━━━━━━━ 5s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 308.9038 - false_positives_4: 321.9231 - loss: 0.2481
```  ```
- 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9282 - false_negatives_4: 236.5094 - false_positives_4: 267.3207 - loss: 0.2085 + 53/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 314.6793 - false_positives_4: 328.3585 - loss: 0.2482
```  ```
- 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9282 - false_negatives_4: 241.2407 - false_positives_4: 272.3148 - loss: 0.2086 + 54/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 320.5185 - false_positives_4: 334.7222 - loss: 0.2483
```  ```
- 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9281 - false_negatives_4: 245.8909 - false_positives_4: 277.6727 - loss: 0.2088 + 55/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 326.2364 - false_positives_4: 341.2727 - loss: 0.2485
```  ```
- 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9280 - false_negatives_4: 250.7143 - false_positives_4: 282.8929 - loss: 0.2089 + 56/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 332.0714 - false_positives_4: 347.7500 - loss: 0.2486
```  ```
- 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9280 - false_negatives_4: 255.5263 - false_positives_4: 288.1228 - loss: 0.2091 + 57/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 337.8421 - false_positives_4: 354.2105 - loss: 0.2487
```  ```
- 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9279 - false_negatives_4: 260.3103 - false_positives_4: 293.5172 - loss: 0.2093 + 58/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 343.6207 - false_positives_4: 360.6552 - loss: 0.2489
```  ```
- 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9278 - false_negatives_4: 265.0508 - false_positives_4: 298.8136 - loss: 0.2094 + 59/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 349.3220 - false_positives_4: 367.0678 - loss: 0.2490
```  ```
- 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9278 - false_negatives_4: 269.7667 - false_positives_4: 304.2167 - loss: 0.2096 + 60/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 355.0500 - false_positives_4: 373.3667 - loss: 0.2491
```  ```
- 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9277 - false_negatives_4: 274.5901 - false_positives_4: 309.5738 - loss: 0.2098 + 61/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 360.7541 - false_positives_4: 379.6230 - loss: 0.2491
```  ```
- 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 73ms/step - binary_accuracy: 0.9276 - false_negatives_4: 279.4032 - false_positives_4: 314.9677 - loss: 0.2099 + 62/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 366.4516 - false_positives_4: 385.8387 - loss: 0.2492
```  ```
- 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 74ms/step - binary_accuracy: 0.9276 - false_negatives_4: 284.1746 - false_positives_4: 320.3016 - loss: 0.2101 + 63/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 372.0476 - false_positives_4: 392.0317 - loss: 0.2492
```  ```
- 64/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9275 - false_negatives_4: 288.9219 - false_positives_4: 325.6250 - loss: 0.2102 + 64/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 377.6250 - false_positives_4: 398.1562 - loss: 0.2493
```  ```
- 65/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9275 - false_negatives_4: 293.6615 - false_positives_4: 330.9385 - loss: 0.2104 + 65/118 ━━━━━━━━━━━━━━━━━━━━ 4s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 383.1846 - false_positives_4: 404.3385 - loss: 0.2493
```  ```
- 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9274 - false_negatives_4: 298.2879 - false_positives_4: 336.2879 - loss: 0.2105 + 66/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 388.8182 - false_positives_4: 410.4697 - loss: 0.2494
```  ```
- 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9274 - false_negatives_4: 303.0448 - false_positives_4: 341.5373 - loss: 0.2106 + 67/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 394.4478 - false_positives_4: 416.6567 - loss: 0.2494
```  ```
- 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9273 - false_negatives_4: 307.7500 - false_positives_4: 346.8529 - loss: 0.2107 + 68/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 400.0147 - false_positives_4: 422.9118 - loss: 0.2495
```  ```
- 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9272 - false_negatives_4: 312.5797 - false_positives_4: 352.1014 - loss: 0.2109 + 69/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 405.7971 - false_positives_4: 429.1159 - loss: 0.2496
```  ```
- 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9272 - false_negatives_4: 317.3857 - false_positives_4: 357.4000 - loss: 0.2110 + 70/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 411.4286 - false_positives_4: 435.6714 - loss: 0.2497
```  ```
- 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9271 - false_negatives_4: 322.1690 - false_positives_4: 362.6338 - loss: 0.2111 + 71/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 417.2113 - false_positives_4: 442.1408 - loss: 0.2498
```  ```
- 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 74ms/step - binary_accuracy: 0.9271 - false_negatives_4: 326.9028 - false_positives_4: 367.8472 - loss: 0.2112 + 72/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 422.9305 - false_positives_4: 448.6389 - loss: 0.2499
```  ```
- 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9271 - false_negatives_4: 331.6986 - false_positives_4: 372.9726 - loss: 0.2113 + 73/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 428.5891 - false_positives_4: 455.1096 - loss: 0.2500
```  ```
- 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9270 - false_negatives_4: 336.3784 - false_positives_4: 378.2027 - loss: 0.2114 + 74/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 434.2297 - false_positives_4: 461.7027 - loss: 0.2500
```  ```
- 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9270 - false_negatives_4: 341.2267 - false_positives_4: 383.3733 - loss: 0.2115 + 75/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 439.9600 - false_positives_4: 468.2133 - loss: 0.2501
```  ```
- 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9269 - false_negatives_4: 346.0526 - false_positives_4: 388.6184 - loss: 0.2116 + 76/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 445.6711 - false_positives_4: 474.7368 - loss: 0.2502
```  ```
- 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 73ms/step - binary_accuracy: 0.9269 - false_negatives_4: 350.9091 - false_positives_4: 393.7792 - loss: 0.2117 + 77/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 451.3247 - false_positives_4: 481.2338 - loss: 0.2503
```  ```
- 78/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_4: 355.7180 - false_positives_4: 398.9487 - loss: 0.2118 + 78/118 ━━━━━━━━━━━━━━━━━━━━ 3s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 457.0513 - false_positives_4: 487.6538 - loss: 0.2504
```  ```
- 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_4: 360.5063 - false_positives_4: 404.0380 - loss: 0.2119 + 79/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 462.7215 - false_positives_4: 494.1266 - loss: 0.2504
```  ```
- 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9268 - false_negatives_4: 365.2250 - false_positives_4: 409.1625 - loss: 0.2119 + 80/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 468.4250 - false_positives_4: 500.5125 - loss: 0.2505
```  ```
- 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 369.9506 - false_positives_4: 414.2346 - loss: 0.2120 + 81/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 474.0617 - false_positives_4: 506.9136 - loss: 0.2506
```  ```
- 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 374.6707 - false_positives_4: 419.2683 - loss: 0.2121 + 82/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 479.7805 - false_positives_4: 513.2439 - loss: 0.2506
```  ```
- 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 379.3615 - false_positives_4: 424.3253 - loss: 0.2122 + 83/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 485.4699 - false_positives_4: 519.6385 - loss: 0.2507
```  ```
- 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9267 - false_negatives_4: 384.0714 - false_positives_4: 429.3571 - loss: 0.2123 + 84/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 491.2381 - false_positives_4: 525.9286 - loss: 0.2507
```  ```
- 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 388.7647 - false_positives_4: 434.4588 - loss: 0.2123 + 85/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 496.9765 - false_positives_4: 532.2353 - loss: 0.2508
```  ```
- 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 393.4767 - false_positives_4: 439.5349 - loss: 0.2124 + 86/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 502.7093 - false_positives_4: 538.5349 - loss: 0.2508
```  ```
- 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 398.1494 - false_positives_4: 444.6437 - loss: 0.2125 + 87/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 508.4598 - false_positives_4: 544.8506 - loss: 0.2509
```  ```
- 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9266 - false_negatives_4: 402.8977 - false_positives_4: 449.7273 - loss: 0.2126 + 88/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 514.1818 - false_positives_4: 551.1705 - loss: 0.2509
```  ```
- 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9265 - false_negatives_4: 407.5506 - false_positives_4: 454.9438 - loss: 0.2126 + 89/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 519.9213 - false_positives_4: 557.4607 - loss: 0.2510
```  ```
- 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 73ms/step - binary_accuracy: 0.9265 - false_negatives_4: 412.2889 - false_positives_4: 460.1333 - loss: 0.2127 + 90/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 525.5778 - false_positives_4: 563.7667 - loss: 0.2510
```  ```
- 91/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9265 - false_negatives_4: 416.9780 - false_positives_4: 465.4615 - loss: 0.2128 + 91/118 ━━━━━━━━━━━━━━━━━━━━ 2s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 531.2747 - false_positives_4: 570.0769 - loss: 0.2511
```  ```
- 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9264 - false_negatives_4: 421.8478 - false_positives_4: 470.7500 - loss: 0.2129 + 92/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 536.9348 - false_positives_4: 576.3587 - loss: 0.2511
```  ```
- 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9264 - false_negatives_4: 426.6559 - false_positives_4: 476.0860 - loss: 0.2130 + 93/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 542.5591 - false_positives_4: 582.7419 - loss: 0.2511
```  ```
- 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9264 - false_negatives_4: 431.4681 - false_positives_4: 481.4362 - loss: 0.2131 + 94/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 548.2872 - false_positives_4: 589.0638 - loss: 0.2512
```  ```
- 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9263 - false_negatives_4: 436.2526 - false_positives_4: 486.8210 - loss: 0.2132 + 95/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 554.0421 - false_positives_4: 595.3895 - loss: 0.2512
```  ```
- 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9263 - false_negatives_4: 440.9896 - false_positives_4: 492.2188 - loss: 0.2133 + 96/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 559.7812 - false_positives_4: 601.7708 - loss: 0.2513
```  ```
- 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9262 - false_negatives_4: 445.7629 - false_positives_4: 497.5670 - loss: 0.2133 + 97/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 565.5154 - false_positives_4: 608.1237 - loss: 0.2513
```  ```
- 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9262 - false_negatives_4: 450.4592 - false_positives_4: 502.8878 - loss: 0.2134 + 98/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 571.2857 - false_positives_4: 614.5306 - loss: 0.2514
```  ```
- 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9262 - false_negatives_4: 455.1818 - false_positives_4: 508.1313 - loss: 0.2135 + 99/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 577.0909 - false_positives_4: 620.9495 - loss: 0.2514
```  ```
- 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9262 - false_negatives_4: 459.8500 - false_positives_4: 513.4500 - loss: 0.2135 + 100/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 582.9200 - false_positives_4: 627.3600 - loss: 0.2515
```  ```
- 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9261 - false_negatives_4: 464.5644 - false_positives_4: 518.7228 - loss: 0.2136 + 101/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 588.7426 - false_positives_4: 633.7525 - loss: 0.2516
```  ```
- 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9261 - false_negatives_4: 469.2255 - false_positives_4: 524.0980 - loss: 0.2137 + 102/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 594.5098 - false_positives_4: 640.1373 - loss: 0.2516
```  ```
- 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9261 - false_negatives_4: 473.9514 - false_positives_4: 529.4272 - loss: 0.2137 + 103/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 600.2719 - false_positives_4: 646.4757 - loss: 0.2517
```  ```
- 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 73ms/step - binary_accuracy: 0.9260 - false_negatives_4: 478.6154 - false_positives_4: 534.8558 - loss: 0.2138 + 104/118 ━━━━━━━━━━━━━━━━━━━━ 1s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 606.0289 - false_positives_4: 652.7885 - loss: 0.2517
```  ```
- 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9260 - false_negatives_4: 483.3905 - false_positives_4: 540.2381 - loss: 0.2139 + 105/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 611.7619 - false_positives_4: 659.1714 - loss: 0.2517
```  ```
- 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9260 - false_negatives_4: 488.1132 - false_positives_4: 545.6698 - loss: 0.2140 + 106/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9061 - false_negatives_4: 617.5472 - false_positives_4: 665.4811 - loss: 0.2518
```  ```
- 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9259 - false_negatives_4: 492.8318 - false_positives_4: 551.0654 - loss: 0.2140 + 107/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 623.2523 - false_positives_4: 671.9532 - loss: 0.2518
```  ```
- 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9259 - false_negatives_4: 497.5555 - false_positives_4: 556.4074 - loss: 0.2141 + 108/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 629.1574 - false_positives_4: 678.3704 - loss: 0.2519
```  ```
- 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9259 - false_negatives_4: 502.2385 - false_positives_4: 561.7798 - loss: 0.2142 + 109/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 634.9633 - false_positives_4: 684.8991 - loss: 0.2520
```  ```
- 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9259 - false_negatives_4: 506.9091 - false_positives_4: 567.1545 - loss: 0.2143 + 110/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 640.9000 - false_positives_4: 691.3455 - loss: 0.2520
```  ```
- 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9258 - false_negatives_4: 511.6306 - false_positives_4: 572.4684 - loss: 0.2143 + 111/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 646.7748 - false_positives_4: 697.8289 - loss: 0.2521
```  ```
- 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9258 - false_negatives_4: 516.3125 - false_positives_4: 577.7857 - loss: 0.2144 + 112/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 652.6875 - false_positives_4: 704.2946 - loss: 0.2522
```  ```
- 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9258 - false_negatives_4: 521.0000 - false_positives_4: 583.0708 - loss: 0.2144 + 113/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 658.6106 - false_positives_4: 710.7699 - loss: 0.2522
```  ```
- 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9258 - false_negatives_4: 525.7193 - false_positives_4: 588.3333 - loss: 0.2145 + 114/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 664.4825 - false_positives_4: 717.3333 - loss: 0.2523
```  ```
- 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9257 - false_negatives_4: 530.4087 - false_positives_4: 593.6435 - loss: 0.2146 + 115/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9060 - false_negatives_4: 670.3826 - false_positives_4: 723.9044 - loss: 0.2523
```  ```
- 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9257 - false_negatives_4: 535.1121 - false_positives_4: 598.8793 - loss: 0.2146 + 116/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 676.2672 - false_positives_4: 730.4655 - loss: 0.2524
```  ```
- 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 73ms/step - binary_accuracy: 0.9257 - false_negatives_4: 539.7521 - false_positives_4: 604.0854 - loss: 0.2147 + 117/118 ━━━━━━━━━━━━━━━━━━━━ 0s 76ms/step - binary_accuracy: 0.9059 - false_negatives_4: 682.1453 - false_positives_4: 737.0513 - loss: 0.2525
``` -Epoch 6: val_loss did not improve from 0.33508 +Epoch 6: val_loss did not improve from 0.35707  ```
- 118/118 ━━━━━━━━━━━━━━━━━━━━ 9s 78ms/step - binary_accuracy: 0.9257 - false_negatives_4: 548.8488 - false_positives_4: 614.2521 - loss: 0.2148 - val_binary_accuracy: 0.8490 - val_false_negatives_4: 221.0000 - val_false_positives_4: 534.0000 - val_loss: 0.4121 + 118/118 ━━━━━━━━━━━━━━━━━━━━ 10s 82ms/step - binary_accuracy: 0.9059 - false_negatives_4: 693.6387 - false_positives_4: 749.9412 - loss: 0.2526 - val_binary_accuracy: 0.8454 - val_false_negatives_4: 391.0000 - val_false_positives_4: 382.0000 - val_loss: 0.3620
@@ -32825,13 +31874,13 @@ Epoch 6: early stopping ```
-![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_17_2582.png) +![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_17_2767.png) -![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_17_2583.png) +![png](/img/examples/nlp/active_learning_review_classification/active_learning_review_classification_17_2768.png) @@ -32839,7 +31888,7 @@ Epoch 6: early stopping ``` ---------------------------------------------------------------------------------------------------- -Test set evaluation: {'binary_accuracy': 0.8564000129699707, 'false_negatives_4': 328.0, 'false_positives_4': 390.0, 'loss': 0.338928759098053} +Test set evaluation: {'binary_accuracy': 0.8424000144004822, 'false_negatives_4': 491.0, 'false_positives_4': 297.0, 'loss': 0.3661557137966156} ---------------------------------------------------------------------------------------------------- ```