diff --git a/BETA_E_Model_T&T.ipynb b/BETA_E_Model_T&T.ipynb index 9988e0e..058612b 100644 --- a/BETA_E_Model_T&T.ipynb +++ b/BETA_E_Model_T&T.ipynb @@ -56,7 +56,31 @@ "groupValue": "123" } }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "c:\\Users\\aydin\\Desktop\\Pneumonia AI Dev\\venv\\lib\\site-packages\\tensorflow_addons\\utils\\tfa_eol_msg.py:23: UserWarning: \n", + "\n", + "TensorFlow Addons (TFA) has ended development and introduction of new features.\n", + "TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.\n", + "Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). \n", + "\n", + "For more information see: https://github.com/tensorflow/addons/issues/2807 \n", + "\n", + " warnings.warn(\n", + "c:\\Users\\aydin\\Desktop\\Pneumonia AI Dev\\venv\\lib\\site-packages\\tensorflow_addons\\utils\\ensure_tf_install.py:53: UserWarning: Tensorflow Addons supports using Python ops for all Tensorflow versions above or equal to 2.12.0 and strictly below 2.15.0 (nightly versions are not supported). \n", + " The versions of TensorFlow you are currently using is 2.10.1 and is not supported. \n", + "Some things might work, some things might not.\n", + "If you were to encounter a bug, do not file an issue.\n", + "If you want to make sure you're using a tested and supported configuration, either change the TensorFlow version or the TensorFlow Addons's version. \n", + "You can find the compatibility matrix in TensorFlow Addon's readme:\n", + "https://github.com/tensorflow/addons\n", + " warnings.warn(\n" + ] + } + ], "source": [ "import io\n", "import os\n", @@ -83,6 +107,7 @@ "import tensorflow as tf\n", "from keras.models import Model\n", "import matplotlib.pyplot as plt\n", + "from vit_keras import vit\n", "from keras.optimizers import * # noqa: F403\n", "from adabelief_tf import AdaBeliefOptimizer # noqa: F401\n", "\n", @@ -4827,93 +4852,129 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Creating the model...\n" - ] - }, - { - "ename": "NameError", - "evalue": "name 'KENB7' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[9], line 61\u001b[0m\n\u001b[0;32m 59\u001b[0m \u001b[38;5;66;03m# Main\u001b[39;00m\n\u001b[0;32m 60\u001b[0m freeze_layers \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m\n\u001b[1;32m---> 61\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[43mEff_B7_NS\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfreeze_layers\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 62\u001b[0m model\u001b[38;5;241m.\u001b[39msummary(show_trainable\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, expand_nested\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 63\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdone.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "Cell \u001b[1;32mIn[9], line 3\u001b[0m, in \u001b[0;36mEff_B7_NS\u001b[1;34m(freeze_layers)\u001b[0m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mEff_B7_NS\u001b[39m(freeze_layers):\n\u001b[1;32m----> 3\u001b[0m base_model \u001b[38;5;241m=\u001b[39m \u001b[43mKENB7\u001b[49m(\n\u001b[0;32m 4\u001b[0m input_shape\u001b[38;5;241m=\u001b[39m(img_res[\u001b[38;5;241m0\u001b[39m], img_res[\u001b[38;5;241m1\u001b[39m], img_res[\u001b[38;5;241m2\u001b[39m]),\n\u001b[0;32m 5\u001b[0m weights\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnoisy-student\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m 6\u001b[0m include_top\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[0;32m 7\u001b[0m )\n\u001b[0;32m 8\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mTotal layers in the base model: \u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mlen\u001b[39m(base_model\u001b[38;5;241m.\u001b[39mlayers))\n\u001b[0;32m 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFreezing \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mfreeze_layers\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m layers in the base model...\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[1;31mNameError\u001b[0m: name 'KENB7' is not defined" + "Model: \"vit-l16\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " input_1 (InputLayer) [(None, 224, 224, 3)] 0 \n", + " \n", + " embedding (Conv2D) (None, 14, 14, 1024) 787456 \n", + " \n", + " reshape (Reshape) (None, 196, 1024) 0 \n", + " \n", + " class_token (ClassToken) (None, 197, 1024) 1024 \n", + " \n", + " Transformer/posembed_input (None, 197, 1024) 201728 \n", + " (AddPositionEmbs) \n", + " \n", + " Transformer/encoderblock_0 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_1 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_2 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_3 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_4 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_5 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_6 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_7 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_8 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_9 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_10 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_11 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_12 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_13 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_14 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_15 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_16 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_17 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_18 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_19 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_20 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_21 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_22 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoderblock_23 ((None, 197, 1024), 12596224 \n", + " (TransformerBlock) (None, 16, None, None)) \n", + " \n", + " Transformer/encoder_norm (L (None, 197, 1024) 2048 \n", + " ayerNormalization) \n", + " \n", + " ExtractToken (Lambda) (None, 1024) 0 \n", + " \n", + " head (Dense) (None, 2) 2050 \n", + " \n", + "=================================================================\n", + "Total params: 303,303,682\n", + "Trainable params: 303,303,682\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" ] } ], "source": [ - "# FUNC\n", - "def Eff_B7_NS(freeze_layers):\n", - " base_model = KENB7(\n", - " input_shape=(img_res[0], img_res[1], img_res[2]),\n", - " weights=\"noisy-student\",\n", - " include_top=False,\n", - " )\n", - " print(\"Total layers in the base model: \", len(base_model.layers))\n", - " print(f\"Freezing {freeze_layers} layers in the base model...\")\n", - " # Freeze the specified number of layers\n", - " for layer in base_model.layers[:freeze_layers]:\n", - " layer.trainable = False\n", - "\n", - " # Unfreeze the rest\n", - " for layer in base_model.layers[freeze_layers:]:\n", - " layer.trainable = True\n", - "\n", - " # Calculate the percentage of the model that is frozen\n", - " frozen_percentage = ((freeze_layers + 1e-10) / len(base_model.layers)) * 100\n", - " print(f\"Percentage of the base model that is frozen: {frozen_percentage:.2f}%\")\n", - " # adding CDL>>>\n", - " # GlobalAveragePooling2D\n", - " base_model_FT = GlobalAveragePooling2D(name=\"FC_INPUT_Avg-Pooling\")(base_model.output)\n", - " # Dense\n", - " Dense_L1 = Dense(512, activation=\"relu\", kernel_regularizer=l2(0.0026), name=\"FC_C_Dense-L1-512\")(base_model_FT)\n", - " # Dropout\n", - " Dropout_L1 = Dropout(0.125, name=\"FC_C_Dropout-L1-0.1\")(Dense_L1)\n", - " # BatchNormalization\n", - " BatchNorm_L2 = BatchNormalization(name=\"FC_C_Avg-BatchNormalization-L1\")(Dropout_L1)\n", - " # Dense\n", - " Dense_L2 = Dense(256, activation=\"relu\", kernel_regularizer=l2(0.0015), name=\"FC_C_Dense-L2-512\")(BatchNorm_L2)\n", - " # BatchNormalization\n", - " BatchNorm_L3 = BatchNormalization(name=\"FC_C_Avg-BatchNormalization-L2\")(Dense_L2)\n", - " # Dense\n", - " Dense_L3 = Dense(128, activation=\"relu\", name=\"FC_C_Dense-L3-128\")(BatchNorm_L3)\n", - " # Dense\n", - " # predictions = Dense(2, activation='softmax')(Dense_L3) / predictions = Dense(1, activation='sigmoid')(Dense_L3)\n", - " predictions = Dense(2, activation=\"softmax\", name=\"FC_OUTPUT_Dense-2\")(Dense_L3)\n", - " # CDL<<<\n", - " model_EfficientNetB7_NS = Model(inputs=base_model.input, outputs=predictions)\n", - " print(\"Total model layers: \", len(model_EfficientNetB7_NS.layers))\n", - " # OPT/compile\n", - " opt = SGD(momentum=0.86, learning_rate=0.01, nesterov=False) # noqa: F405\n", - " # opt = Nadam() # noqa: F405\n", - " # opt = Adamax() # noqa: F405\n", - " # opt = Adam(amsgrad=True) # noqa: F405\n", - " # opt = RMSprop(momentum=0.9) # noqa: F405\n", - " # opt = Adagrad() # noqa: F405\n", - " # opt = AdaBeliefOptimizer(epsilon=1e-7, rectify=False, weight_decay=5e-4, print_change_log=False, amsgrad=True) # noqa: F405\n", - " # opt = Yogi() # noqa: F405\n", - " model_EfficientNetB7_NS.compile(\n", - " optimizer=opt, loss=\"categorical_crossentropy\", metrics=[\"accuracy\"]\n", - " ) # categorical_crossentropy / binary_crossentropy\n", - "\n", - " return model_EfficientNetB7_NS\n", - "\n", - "\n", - "print(\"Creating the model...\")\n", - "# Main\n", - "freeze_layers = 0\n", - "model = Eff_B7_NS(freeze_layers)\n", - "model.summary(show_trainable=True, expand_nested=True)\n", - "print(\"done.\")" + "# Create a simple transformer model\n", + "model = vit.vit_l16(\n", + " image_size=224,\n", + " activation='sigmoid',\n", + " pretrained=True,\n", + " include_top=True,\n", + " pretrained_top=False,\n", + " classes=2\n", + ")\n", + "# model compile + summary\n", + "opt = SGD(learning_rate=0.01, momentum=0.9)\n", + "model.compile(loss='categorical_crossentropy', optimizer=opt, metrics=['accuracy'])\n", + "model.summary()" ] }, { @@ -7318,7 +7379,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": { "ExecuteTime": { "end_time": "2023-12-28T07:04:23.573633300Z", @@ -7333,8 +7394,8 @@ "Training the model...\n", "\u001b[0;33m\n", "Setup Verbose:\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mExperiment name: \u001b[0m\u001b[0;32m[_y2024_m03_d29-h20_m44_s53]\u001b[0m\u001b[0;36m...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSetting TensorBoard Log dir to \u001b[0m\u001b[0;32m[logs/fit/_y2024_m03_d29-h20_m44_s53]\u001b[0m\u001b[0;36m...\u001b[0m\n", + "\u001b[0m\u001b[0m\u001b[0;36mExperiment name: \u001b[0m\u001b[0;32m[ViT_Bigboy_y2024_m04_d05-h22_m43_s56]\u001b[0m\u001b[0;36m...\u001b[0m\n", + "\u001b[0m\u001b[0m\u001b[0;36mSetting TensorBoard Log dir to \u001b[0m\u001b[0;32m[logs/fit/ViT_Bigboy_y2024_m04_d05-h22_m43_s56]\u001b[0m\u001b[0;36m...\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36mUse_extended_tensorboard \u001b[0m\u001b[0;32m[False]\u001b[0m\u001b[0;36m.\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36mDebug_OUTPUT_DPS \u001b[0m\u001b[0;32m[True]\u001b[0m\u001b[0;36m.\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36mUse_OneCycleLr \u001b[0m\u001b[0;32m[False]\u001b[0m\u001b[0;36m.\u001b[0m\n", @@ -7345,7 +7406,7 @@ "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mname: \u001b[0m\u001b[0;32mSGD\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mlearning_rate: \u001b[0m\u001b[0;32m0.009999999776482582\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mdecay: \u001b[0m\u001b[0;32m0.0\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mmomentum: \u001b[0m\u001b[0;32m0.8899999856948853\u001b[0m\n", + "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mmomentum: \u001b[0m\u001b[0;32m0.8999999761581421\u001b[0m\n", "\u001b[0m\u001b[0m\u001b[0;36m -- \u001b[0m\u001b[0;96mnesterov: \u001b[0m\u001b[0;32mFalse\u001b[0m\n", "\u001b[0;33mSetup Verbose END.\u001b[0m\n", "\u001b[0m\n", @@ -7354,3037 +7415,7 @@ "\u001b[0;33mPreparing train data...\u001b[0m\n", "\u001b[0;33m- Loading fitted ImageDataGenerator...\u001b[0m\n", "\u001b[0;33m- ImageDataGenerator fit done.\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;31m- Debug DP Sample dir: \u001b[0m\u001b[0;32mSamples/TSR_SUB_400_y2024_m03_d29-h20_m45_s50\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 1/6\n", - "256/256 [==============================] - 94s 289ms/step - loss: 2.1378 - accuracy: 0.6372 - val_loss: 1.8907 - val_accuracy: 0.7372 - lr: 0.0100\n", - "Epoch 2/6\n", - "256/256 [==============================] - 70s 273ms/step - loss: 1.7242 - accuracy: 0.8125 - val_loss: 1.4988 - val_accuracy: 0.8494 - lr: 0.0100\n", - "Epoch 3/6\n", - "256/256 [==============================] - 71s 278ms/step - loss: 1.4643 - accuracy: 0.8684 - val_loss: 1.3688 - val_accuracy: 0.8638 - lr: 0.0100\n", - "Epoch 4/6\n", - "256/256 [==============================] - 72s 281ms/step - loss: 1.2522 - accuracy: 0.8992 - val_loss: 1.2234 - val_accuracy: 0.8381 - lr: 0.0100\n", - "Epoch 5/6\n", - "256/256 [==============================] - 73s 284ms/step - loss: 1.1065 - accuracy: 0.9102 - val_loss: 1.1080 - val_accuracy: 0.9038 - lr: 0.0100\n", - "Epoch 6/6\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.9423 - accuracy: 0.9287 - val_loss: 0.9623 - val_accuracy: 0.8750 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-005-0.9038.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9038\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m1.0990\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.000000 to 0.903846. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from inf to 1.09902048. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 1.95GB, used: 22.05GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m531.25 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m453.88 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m77.36 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [1] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m2\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 6)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 7/12\n", - "256/256 [==============================] - 77s 282ms/step - loss: 1.0754 - accuracy: 0.8726 - val_loss: 0.9810 - val_accuracy: 0.8910 - lr: 0.0100\n", - "Epoch 8/12\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.9141 - accuracy: 0.9070 - val_loss: 1.0838 - val_accuracy: 0.7997 - lr: 0.0100\n", - "Epoch 9/12\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.8049 - accuracy: 0.9192 - val_loss: 0.8255 - val_accuracy: 0.8814 - lr: 0.0100\n", - "Epoch 10/12\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.6986 - accuracy: 0.9326 - val_loss: 0.7473 - val_accuracy: 0.8894 - lr: 0.0100\n", - "Epoch 11/12\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.6178 - accuracy: 0.9426 - val_loss: 0.9366 - val_accuracy: 0.8397 - lr: 0.0100\n", - "Epoch 12/12\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.5278 - accuracy: 0.9568 - val_loss: 1.1692 - val_accuracy: 0.8478 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-007-0.8910.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8910\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.9810\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9038461447. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 1.09902048 to 0.98102009. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.14GB, used: 18.86GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m509.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.94 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m84.52 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [2] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m3\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 12)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 13/18\n", - "256/256 [==============================] - 74s 275ms/step - loss: 0.9580 - accuracy: 0.8875 - val_loss: 0.8333 - val_accuracy: 0.9199 - lr: 0.0100\n", - "Epoch 14/18\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.8153 - accuracy: 0.9146 - val_loss: 0.8155 - val_accuracy: 0.8878 - lr: 0.0100\n", - "Epoch 15/18\n", - "256/256 [==============================] - 69s 271ms/step - loss: 0.7287 - accuracy: 0.9175 - val_loss: 0.7287 - val_accuracy: 0.9167 - lr: 0.0100\n", - "Epoch 16/18\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.6085 - accuracy: 0.9424 - val_loss: 0.6945 - val_accuracy: 0.9054 - lr: 0.0100\n", - "Epoch 17/18\n", - "256/256 [==============================] - 69s 271ms/step - loss: 0.5522 - accuracy: 0.9500 - val_loss: 0.6496 - val_accuracy: 0.8830 - lr: 0.0100\n", - "Epoch 18/18\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.4957 - accuracy: 0.9553 - val_loss: 0.5994 - val_accuracy: 0.9199 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-013-0.9199.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9199\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.8333\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.903846 to 0.919872. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.98102009 to 0.83334637. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m491.59 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m422.14 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m69.45 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [3] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m4\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 18)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 19/24\n", - "256/256 [==============================] - 74s 275ms/step - loss: 0.8811 - accuracy: 0.8813 - val_loss: 0.8378 - val_accuracy: 0.9103 - lr: 0.0100\n", - "Epoch 20/24\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.7593 - accuracy: 0.9089 - val_loss: 0.8316 - val_accuracy: 0.8526 - lr: 0.0100\n", - "Epoch 21/24\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.6531 - accuracy: 0.9248 - val_loss: 0.6264 - val_accuracy: 0.9327 - lr: 0.0100\n", - "Epoch 22/24\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.5809 - accuracy: 0.9392 - val_loss: 0.5873 - val_accuracy: 0.9375 - lr: 0.0100\n", - "Epoch 23/24\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.5031 - accuracy: 0.9480 - val_loss: 0.5634 - val_accuracy: 0.9343 - lr: 0.0100\n", - "Epoch 24/24\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.4328 - accuracy: 0.9570 - val_loss: 0.5751 - val_accuracy: 0.8846 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-022-0.9375.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9375\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.5873\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.919872 to 0.937500. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.83334637 to 0.58728427. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m492.19 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m422.44 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m69.75 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [4] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m5\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 24)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 25/30\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.6212 - accuracy: 0.9043 - val_loss: 0.7914 - val_accuracy: 0.8670 - lr: 0.0100\n", - "Epoch 26/30\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.5334 - accuracy: 0.9290 - val_loss: 0.5001 - val_accuracy: 0.9311 - lr: 0.0100\n", - "Epoch 27/30\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.4541 - accuracy: 0.9397 - val_loss: 0.5195 - val_accuracy: 0.9135 - lr: 0.0100\n", - "Epoch 28/30\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.4093 - accuracy: 0.9451 - val_loss: 0.5215 - val_accuracy: 0.9087 - lr: 0.0100\n", - "Epoch 29/30\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.3499 - accuracy: 0.9597 - val_loss: 0.4166 - val_accuracy: 0.9375 - lr: 0.0100\n", - "Epoch 30/30\n", - "256/256 [==============================] - 69s 269ms/step - loss: 0.3113 - accuracy: 0.9634 - val_loss: 0.4444 - val_accuracy: 0.9151 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-029-0.9375.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9375\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4166\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9375000000. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.58728427 to 0.41660872. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m493.68 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.53 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m69.15 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [5] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m6\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 30)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 31/36\n", - "256/256 [==============================] - 75s 276ms/step - loss: 0.4474 - accuracy: 0.9150 - val_loss: 0.3971 - val_accuracy: 0.9375 - lr: 0.0100\n", - "Epoch 32/36\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.3720 - accuracy: 0.9348 - val_loss: 0.3943 - val_accuracy: 0.9295 - lr: 0.0100\n", - "Epoch 33/36\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.3061 - accuracy: 0.9551 - val_loss: 0.3369 - val_accuracy: 0.9487 - lr: 0.0100\n", - "Epoch 34/36\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2716 - accuracy: 0.9651 - val_loss: 0.3636 - val_accuracy: 0.9375 - lr: 0.0100\n", - "Epoch 35/36\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2348 - accuracy: 0.9690 - val_loss: 0.3595 - val_accuracy: 0.9407 - lr: 0.0100\n", - "Epoch 36/36\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2161 - accuracy: 0.9714 - val_loss: 0.3430 - val_accuracy: 0.9359 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-033-0.9487.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9487\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3369\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.937500 to 0.948718. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.41660872 to 0.33694357. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m496.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.14 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m72.47 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [6] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m7\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 36)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 37/42\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.3834 - accuracy: 0.9062 - val_loss: 0.3117 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 38/42\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.3038 - accuracy: 0.9417 - val_loss: 0.3520 - val_accuracy: 0.9423 - lr: 0.0100\n", - "Epoch 39/42\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.2586 - accuracy: 0.9529 - val_loss: 0.3165 - val_accuracy: 0.9295 - lr: 0.0100\n", - "Epoch 40/42\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.2164 - accuracy: 0.9651 - val_loss: 1.0490 - val_accuracy: 0.7901 - lr: 0.0100\n", - "Epoch 41/42\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1917 - accuracy: 0.9736 - val_loss: 0.3480 - val_accuracy: 0.9135 - lr: 0.0100\n", - "Epoch 42/42\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1689 - accuracy: 0.9761 - val_loss: 0.2705 - val_accuracy: 0.9375 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-037-0.9471.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9471\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3118\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9487179518. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.33694357 to 0.31175852. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m496.05 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.58 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m71.48 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [7] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m8\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 42)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 43/48\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.3506 - accuracy: 0.9248 - val_loss: 0.3114 - val_accuracy: 0.9439 - lr: 0.0100\n", - "Epoch 44/48\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.3039 - accuracy: 0.9392 - val_loss: 0.3033 - val_accuracy: 0.9503 - lr: 0.0100\n", - "Epoch 45/48\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2514 - accuracy: 0.9565 - val_loss: 0.3239 - val_accuracy: 0.9167 - lr: 0.0100\n", - "Epoch 46/48\n", - "256/256 [==============================] - 69s 271ms/step - loss: 0.2171 - accuracy: 0.9617 - val_loss: 0.2641 - val_accuracy: 0.9423 - lr: 0.0100\n", - "Epoch 47/48\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1880 - accuracy: 0.9717 - val_loss: 0.3846 - val_accuracy: 0.9054 - lr: 0.0100\n", - "Epoch 48/48\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1528 - accuracy: 0.9807 - val_loss: 0.2730 - val_accuracy: 0.9375 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-044-0.9503.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9503\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3033\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.948718 to 0.950321. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.31175852 to 0.30326003. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m498.87 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.45 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m74.42 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [8] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m9\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 48)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 49/54\n", - "256/256 [==============================] - 75s 279ms/step - loss: 0.3169 - accuracy: 0.9275 - val_loss: 0.3260 - val_accuracy: 0.9215 - lr: 0.0100\n", - "Epoch 50/54\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2677 - accuracy: 0.9438 - val_loss: 0.3534 - val_accuracy: 0.9006 - lr: 0.0100\n", - "Epoch 51/54\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.2187 - accuracy: 0.9622 - val_loss: 0.3277 - val_accuracy: 0.9295 - lr: 0.0100\n", - "Epoch 52/54\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1777 - accuracy: 0.9702 - val_loss: 0.4656 - val_accuracy: 0.9119 - lr: 0.0100\n", - "Epoch 53/54\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1573 - accuracy: 0.9761 - val_loss: 0.2278 - val_accuracy: 0.9487 - lr: 0.0100\n", - "Epoch 54/54\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1485 - accuracy: 0.9785 - val_loss: 0.5326 - val_accuracy: 0.8317 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-053-0.9487.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9487\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2279\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9503205419. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.30326003 to 0.22785568. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m497.91 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m427.05 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m70.86 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [9] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m10\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 54)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 55/60\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.2935 - accuracy: 0.9275 - val_loss: 0.2426 - val_accuracy: 0.9535 - lr: 0.0100\n", - "Epoch 56/60\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.2239 - accuracy: 0.9478 - val_loss: 0.2476 - val_accuracy: 0.9455 - lr: 0.0100\n", - "Epoch 57/60\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1874 - accuracy: 0.9607 - val_loss: 0.3168 - val_accuracy: 0.9183 - lr: 0.0100\n", - "Epoch 58/60\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1435 - accuracy: 0.9746 - val_loss: 0.2209 - val_accuracy: 0.9407 - lr: 0.0100\n", - "Epoch 59/60\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1247 - accuracy: 0.9778 - val_loss: 0.2745 - val_accuracy: 0.9487 - lr: 0.0100\n", - "Epoch 60/60\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1104 - accuracy: 0.9810 - val_loss: 0.2360 - val_accuracy: 0.9487 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-055-0.9535.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9535\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2426\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.950321 to 0.953526. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.2278556824. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m496.06 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m424.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m71.60 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [10] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m11\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 60)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 61/66\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.2740 - accuracy: 0.9314 - val_loss: 0.2571 - val_accuracy: 0.9519 - lr: 0.0100\n", - "Epoch 62/66\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.2121 - accuracy: 0.9539 - val_loss: 0.2049 - val_accuracy: 0.9551 - lr: 0.0100\n", - "Epoch 63/66\n", - "256/256 [==============================] - 70s 275ms/step - loss: 0.1764 - accuracy: 0.9653 - val_loss: 0.1865 - val_accuracy: 0.9615 - lr: 0.0100\n", - "Epoch 64/66\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1430 - accuracy: 0.9741 - val_loss: 0.2043 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 65/66\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1236 - accuracy: 0.9753 - val_loss: 0.2097 - val_accuracy: 0.9583 - lr: 0.0100\n", - "Epoch 66/66\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1056 - accuracy: 0.9819 - val_loss: 0.2676 - val_accuracy: 0.9535 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-063-0.9615.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9615\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1865\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model accuracy from 0.953526 to 0.961538. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.22785568 to 0.18650842. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m501.19 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m426.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m74.76 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [11] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m12\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 66)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 67/72\n", - "256/256 [==============================] - 76s 279ms/step - loss: 0.2568 - accuracy: 0.9346 - val_loss: 0.2103 - val_accuracy: 0.9519 - lr: 0.0100\n", - "Epoch 68/72\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.2037 - accuracy: 0.9536 - val_loss: 0.2022 - val_accuracy: 0.9535 - lr: 0.0100\n", - "Epoch 69/72\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1751 - accuracy: 0.9573 - val_loss: 0.1843 - val_accuracy: 0.9551 - lr: 0.0100\n", - "Epoch 70/72\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1368 - accuracy: 0.9707 - val_loss: 0.1812 - val_accuracy: 0.9599 - lr: 0.0100\n", - "Epoch 71/72\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1159 - accuracy: 0.9780 - val_loss: 0.2526 - val_accuracy: 0.9407 - lr: 0.0100\n", - "Epoch 72/72\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1069 - accuracy: 0.9795 - val_loss: 0.2513 - val_accuracy: 0.9231 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-070-0.9599.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9599\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1812\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.18650842 to 0.18118645. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.13GB, used: 18.87GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m503.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m429.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m74.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [12] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m13\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 72)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 73/78\n", - "256/256 [==============================] - 75s 279ms/step - loss: 0.2414 - accuracy: 0.9294 - val_loss: 0.1788 - val_accuracy: 0.9599 - lr: 0.0100\n", - "Epoch 74/78\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1754 - accuracy: 0.9548 - val_loss: 0.2104 - val_accuracy: 0.9439 - lr: 0.0100\n", - "Epoch 75/78\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1465 - accuracy: 0.9670 - val_loss: 0.1927 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 76/78\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1156 - accuracy: 0.9741 - val_loss: 0.1797 - val_accuracy: 0.9535 - lr: 0.0100\n", - "Epoch 77/78\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0964 - accuracy: 0.9812 - val_loss: 0.3014 - val_accuracy: 0.9423 - lr: 0.0100\n", - "Epoch 78/78\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0891 - accuracy: 0.9807 - val_loss: 0.1904 - val_accuracy: 0.9423 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-073-0.9599.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9599\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1788\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.18118645 to 0.17884569. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.14GB, used: 18.86GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m502.74 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m426.94 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m75.80 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [13] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m14\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 78)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 79/84\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.2316 - accuracy: 0.9380 - val_loss: 0.2060 - val_accuracy: 0.9407 - lr: 0.0100\n", - "Epoch 80/84\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1715 - accuracy: 0.9580 - val_loss: 0.1804 - val_accuracy: 0.9503 - lr: 0.0100\n", - "Epoch 81/84\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1476 - accuracy: 0.9646 - val_loss: 0.3042 - val_accuracy: 0.9087 - lr: 0.0100\n", - "Epoch 82/84\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1162 - accuracy: 0.9746 - val_loss: 0.2478 - val_accuracy: 0.9279 - lr: 0.0100\n", - "Epoch 83/84\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0961 - accuracy: 0.9824 - val_loss: 0.1980 - val_accuracy: 0.9599 - lr: 0.0100\n", - "Epoch 84/84\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.0851 - accuracy: 0.9861 - val_loss: 0.2208 - val_accuracy: 0.9535 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-083-0.9599.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9599\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1980\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1788456887. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m500.63 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m426.28 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m74.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [14] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m15\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 84)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 85/90\n", - "256/256 [==============================] - 75s 277ms/step - loss: 0.2205 - accuracy: 0.9375 - val_loss: 0.1953 - val_accuracy: 0.9487 - lr: 0.0100\n", - "Epoch 86/90\n", - "256/256 [==============================] - 69s 271ms/step - loss: 0.1596 - accuracy: 0.9578 - val_loss: 0.2314 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 87/90\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.1303 - accuracy: 0.9661 - val_loss: 0.2036 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 88/90\n", - "256/256 [==============================] - 70s 271ms/step - loss: 0.0946 - accuracy: 0.9812 - val_loss: 0.2871 - val_accuracy: 0.9311 - lr: 0.0100\n", - "Epoch 89/90\n", - "256/256 [==============================] - 69s 270ms/step - loss: 0.0762 - accuracy: 0.9836 - val_loss: 0.5652 - val_accuracy: 0.8686 - lr: 0.0100\n", - "Epoch 90/90\n", - "256/256 [==============================] - 70s 270ms/step - loss: 0.0751 - accuracy: 0.9851 - val_loss: 0.4255 - val_accuracy: 0.9006 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-085-0.9487.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9487\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1953\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1788456887. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m499.26 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m423.69 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m75.57 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [15] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m16\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 90)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 91/96\n", - "256/256 [==============================] - 76s 280ms/step - loss: 0.2224 - accuracy: 0.9333 - val_loss: 0.2097 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 92/96\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1542 - accuracy: 0.9565 - val_loss: 0.1671 - val_accuracy: 0.9599 - lr: 0.0100\n", - "Epoch 93/96\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1241 - accuracy: 0.9712 - val_loss: 0.2496 - val_accuracy: 0.9199 - lr: 0.0100\n", - "Epoch 94/96\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0903 - accuracy: 0.9802 - val_loss: 0.1669 - val_accuracy: 0.9583 - lr: 0.0100\n", - "Epoch 95/96\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0800 - accuracy: 0.9841 - val_loss: 0.1707 - val_accuracy: 0.9599 - lr: 0.0100\n", - "Epoch 96/96\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0814 - accuracy: 0.9822 - val_loss: 0.2124 - val_accuracy: 0.9455 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-092-0.9599.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9599\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1671\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.17884569 to 0.16713950. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m506.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m428.29 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m78.06 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [16] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m17\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 96)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 97/102\n", - "256/256 [==============================] - 76s 281ms/step - loss: 0.2000 - accuracy: 0.9419 - val_loss: 0.1803 - val_accuracy: 0.9455 - lr: 0.0100\n", - "Epoch 98/102\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1603 - accuracy: 0.9570 - val_loss: 0.1950 - val_accuracy: 0.9391 - lr: 0.0100\n", - "Epoch 99/102\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.1286 - accuracy: 0.9688 - val_loss: 0.1884 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 100/102\n", - "256/256 [==============================] - 70s 272ms/step - loss: 0.1045 - accuracy: 0.9773 - val_loss: 0.2358 - val_accuracy: 0.9311 - lr: 0.0100\n", - "Epoch 101/102\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0909 - accuracy: 0.9807 - val_loss: 0.2543 - val_accuracy: 0.9359 - lr: 0.0100\n", - "Epoch 102/102\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0815 - accuracy: 0.9836 - val_loss: 0.2290 - val_accuracy: 0.9247 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-099-0.9471.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9471\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1884\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1671395004. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m506.73 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m428.74 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m78.00 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [17] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m18\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 102)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 103/108\n", - "256/256 [==============================] - 76s 280ms/step - loss: 0.2191 - accuracy: 0.9355 - val_loss: 0.2022 - val_accuracy: 0.9439 - lr: 0.0100\n", - "Epoch 104/108\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1620 - accuracy: 0.9548 - val_loss: 0.1848 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 105/108\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1338 - accuracy: 0.9631 - val_loss: 0.2283 - val_accuracy: 0.9279 - lr: 0.0100\n", - "Epoch 106/108\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1021 - accuracy: 0.9741 - val_loss: 0.1688 - val_accuracy: 0.9551 - lr: 0.0100\n", - "Epoch 107/108\n", - "256/256 [==============================] - 70s 275ms/step - loss: 0.0819 - accuracy: 0.9819 - val_loss: 0.1969 - val_accuracy: 0.9455 - lr: 0.0100\n", - "Epoch 108/108\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0776 - accuracy: 0.9841 - val_loss: 0.2636 - val_accuracy: 0.8990 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-106-0.9551.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9535\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1688\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1671395004. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m508.41 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m429.53 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m78.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [18] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m19\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 108)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 109/114\n", - "256/256 [==============================] - 76s 281ms/step - loss: 0.1952 - accuracy: 0.9424 - val_loss: 0.1801 - val_accuracy: 0.9487 - lr: 0.0100\n", - "Epoch 110/114\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.1472 - accuracy: 0.9558 - val_loss: 0.1730 - val_accuracy: 0.9503 - lr: 0.0100\n", - "Epoch 111/114\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1048 - accuracy: 0.9722 - val_loss: 0.4313 - val_accuracy: 0.8670 - lr: 0.0100\n", - "Epoch 112/114\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0790 - accuracy: 0.9790 - val_loss: 0.2087 - val_accuracy: 0.9391 - lr: 0.0100\n", - "Epoch 113/114\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0691 - accuracy: 0.9861 - val_loss: 0.1956 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 114/114\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0683 - accuracy: 0.9849 - val_loss: 0.1962 - val_accuracy: 0.9423 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-110-0.9503.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9503\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1730\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1671395004. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m510.54 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m430.22 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m80.32 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [19] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m20\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 114)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 115/120\n", - "256/256 [==============================] - 76s 279ms/step - loss: 0.1874 - accuracy: 0.9419 - val_loss: 0.1975 - val_accuracy: 0.9375 - lr: 0.0100\n", - "Epoch 116/120\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1582 - accuracy: 0.9531 - val_loss: 0.2660 - val_accuracy: 0.9263 - lr: 0.0100\n", - "Epoch 117/120\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1196 - accuracy: 0.9690 - val_loss: 0.2343 - val_accuracy: 0.9327 - lr: 0.0100\n", - "Epoch 118/120\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0896 - accuracy: 0.9792 - val_loss: 0.1768 - val_accuracy: 0.9471 - lr: 0.0100\n", - "Epoch 119/120\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0643 - accuracy: 0.9858 - val_loss: 0.1641 - val_accuracy: 0.9615 - lr: 0.0100\n", - "Epoch 120/120\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0559 - accuracy: 0.9863 - val_loss: 0.1774 - val_accuracy: 0.9471 - lr: 0.0100\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-119-0.9615.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9615\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1641\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.16713950 to 0.16408551. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m513.32 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m429.12 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m84.20 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [20] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m21\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 120)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 121/126\n", - "256/256 [==============================] - 76s 280ms/step - loss: 0.1836 - accuracy: 0.9478 - val_loss: 0.1733 - val_accuracy: 0.9439 - lr: 0.0100\n", - "Epoch 122/126\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1378 - accuracy: 0.9592 - val_loss: 0.1685 - val_accuracy: 0.9439 - lr: 0.0100\n", - "Epoch 123/126\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0880 - accuracy: 0.9766\n", - "Epoch 123: ReduceLROnPlateau reducing learning rate to 0.009819999780505895.\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0880 - accuracy: 0.9766 - val_loss: 0.3659 - val_accuracy: 0.9022 - lr: 0.0100\n", - "Epoch 124/126\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0708 - accuracy: 0.9817 - val_loss: 0.1868 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 125/126\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0506 - accuracy: 0.9890 - val_loss: 0.2319 - val_accuracy: 0.9407 - lr: 0.0098\n", - "Epoch 126/126\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0529 - accuracy: 0.9868 - val_loss: 0.2361 - val_accuracy: 0.9391 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-121-0.9439.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1734\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1640855074. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m511.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m428.85 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m83.04 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [21] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m22\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 126)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 127/132\n", - "256/256 [==============================] - 76s 280ms/step - loss: 0.1919 - accuracy: 0.9417 - val_loss: 0.2013 - val_accuracy: 0.9487 - lr: 0.0098\n", - "Epoch 128/132\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.1440 - accuracy: 0.9563 - val_loss: 0.1692 - val_accuracy: 0.9503 - lr: 0.0098\n", - "Epoch 129/132\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.1061 - accuracy: 0.9709 - val_loss: 0.1920 - val_accuracy: 0.9391 - lr: 0.0098\n", - "Epoch 130/132\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0866 - accuracy: 0.9783 - val_loss: 0.2752 - val_accuracy: 0.9167 - lr: 0.0098\n", - "Epoch 131/132\n", - "256/256 [==============================] - 70s 273ms/step - loss: 0.0707 - accuracy: 0.9834 - val_loss: 0.4520 - val_accuracy: 0.9038 - lr: 0.0098\n", - "Epoch 132/132\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0596 - accuracy: 0.9868 - val_loss: 0.2635 - val_accuracy: 0.9359 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-128-0.9503.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9503\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1692\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1640855074. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m513.73 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m429.30 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m84.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [22] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m23\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 132)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 133/138\n", - "256/256 [==============================] - 76s 281ms/step - loss: 0.1859 - accuracy: 0.9434 - val_loss: 0.1613 - val_accuracy: 0.9519 - lr: 0.0098\n", - "Epoch 134/138\n", - "256/256 [==============================] - 70s 275ms/step - loss: 0.1337 - accuracy: 0.9622 - val_loss: 0.1738 - val_accuracy: 0.9487 - lr: 0.0098\n", - "Epoch 135/138\n", - "256/256 [==============================] - 71s 274ms/step - loss: 0.1014 - accuracy: 0.9734 - val_loss: 0.1834 - val_accuracy: 0.9375 - lr: 0.0098\n", - "Epoch 136/138\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0863 - accuracy: 0.9761 - val_loss: 0.2131 - val_accuracy: 0.9327 - lr: 0.0098\n", - "Epoch 137/138\n", - "256/256 [==============================] - 71s 274ms/step - loss: 0.0600 - accuracy: 0.9868 - val_loss: 0.1950 - val_accuracy: 0.9391 - lr: 0.0098\n", - "Epoch 138/138\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0604 - accuracy: 0.9858 - val_loss: 0.2959 - val_accuracy: 0.9279 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-133-0.9519.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9519\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1613\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.16408551 to 0.16128203. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m516.63 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m430.13 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m86.50 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [23] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m24\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 138)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 139/144\n", - "256/256 [==============================] - 76s 282ms/step - loss: 0.1792 - accuracy: 0.9421 - val_loss: 0.2648 - val_accuracy: 0.9167 - lr: 0.0098\n", - "Epoch 140/144\n", - "256/256 [==============================] - 71s 279ms/step - loss: 0.1274 - accuracy: 0.9597 - val_loss: 0.1855 - val_accuracy: 0.9295 - lr: 0.0098\n", - "Epoch 141/144\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0982 - accuracy: 0.9697 - val_loss: 0.1819 - val_accuracy: 0.9439 - lr: 0.0098\n", - "Epoch 142/144\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0807 - accuracy: 0.9780 - val_loss: 0.2425 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 143/144\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0618 - accuracy: 0.9851 - val_loss: 0.3697 - val_accuracy: 0.8878 - lr: 0.0098\n", - "Epoch 144/144\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0544 - accuracy: 0.9866 - val_loss: 0.2781 - val_accuracy: 0.9359 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-141-0.9439.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1820\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1612820327. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m518.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m432.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m85.06 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [24] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m25\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 144)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 1]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 145/150\n", - "256/256 [==============================] - 76s 280ms/step - loss: 0.1798 - accuracy: 0.9436 - val_loss: 0.1756 - val_accuracy: 0.9407 - lr: 0.0098\n", - "Epoch 146/150\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.1337 - accuracy: 0.9600 - val_loss: 0.1838 - val_accuracy: 0.9615 - lr: 0.0098\n", - "Epoch 147/150\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0957 - accuracy: 0.9753 - val_loss: 0.1846 - val_accuracy: 0.9567 - lr: 0.0098\n", - "Epoch 148/150\n", - "256/256 [==============================] - 71s 274ms/step - loss: 0.0823 - accuracy: 0.9788 - val_loss: 0.2423 - val_accuracy: 0.9439 - lr: 0.0098\n", - "Epoch 149/150\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0595 - accuracy: 0.9846 - val_loss: 0.2196 - val_accuracy: 0.9503 - lr: 0.0098\n", - "Epoch 150/150\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0646 - accuracy: 0.9846 - val_loss: 0.1869 - val_accuracy: 0.9391 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-146-0.9615.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9615\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1839\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1612820327. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m516.77 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m430.03 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m86.75 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [25] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m26\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 150)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 151/156\n", - "256/256 [==============================] - 76s 282ms/step - loss: 0.1690 - accuracy: 0.9475 - val_loss: 0.1507 - val_accuracy: 0.9567 - lr: 0.0098\n", - "Epoch 152/156\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.1301 - accuracy: 0.9624 - val_loss: 0.2251 - val_accuracy: 0.9038 - lr: 0.0098\n", - "Epoch 153/156\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1059 - accuracy: 0.9702 - val_loss: 0.2136 - val_accuracy: 0.9183 - lr: 0.0098\n", - "Epoch 154/156\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0606 - accuracy: 0.9868 - val_loss: 0.3920 - val_accuracy: 0.8942 - lr: 0.0098\n", - "Epoch 155/156\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0563 - accuracy: 0.9861 - val_loss: 0.1865 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 156/156\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0489 - accuracy: 0.9871 - val_loss: 0.2106 - val_accuracy: 0.9487 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-151-0.9567.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9567\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1507\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.16128203 to 0.15071724. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m524.27 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m430.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m93.81 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [26] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m27\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 156)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 157/162\n", - "256/256 [==============================] - 76s 283ms/step - loss: 0.1683 - accuracy: 0.9421 - val_loss: 0.1730 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 158/162\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.1310 - accuracy: 0.9622 - val_loss: 0.2105 - val_accuracy: 0.9439 - lr: 0.0098\n", - "Epoch 159/162\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0979 - accuracy: 0.9705 - val_loss: 0.2328 - val_accuracy: 0.9183 - lr: 0.0098\n", - "Epoch 160/162\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0757 - accuracy: 0.9795 - val_loss: 0.2100 - val_accuracy: 0.9343 - lr: 0.0098\n", - "Epoch 161/162\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0616 - accuracy: 0.9822 - val_loss: 0.2751 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 162/162\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0492 - accuracy: 0.9849 - val_loss: 0.2698 - val_accuracy: 0.9471 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1730}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9471\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2698\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m521.31 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m431.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m89.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [27] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m28\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 162)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 163/168\n", - "256/256 [==============================] - 77s 283ms/step - loss: 0.1891 - accuracy: 0.9412 - val_loss: 0.2367 - val_accuracy: 0.9279 - lr: 0.0098\n", - "Epoch 164/168\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1229 - accuracy: 0.9609 - val_loss: 0.2379 - val_accuracy: 0.8814 - lr: 0.0098\n", - "Epoch 165/168\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0927 - accuracy: 0.9749 - val_loss: 0.1685 - val_accuracy: 0.9407 - lr: 0.0098\n", - "Epoch 166/168\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0695 - accuracy: 0.9792 - val_loss: 0.2267 - val_accuracy: 0.9071 - lr: 0.0098\n", - "Epoch 167/168\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0488 - accuracy: 0.9885 - val_loss: 0.1868 - val_accuracy: 0.9503 - lr: 0.0098\n", - "Epoch 168/168\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0394 - accuracy: 0.9922 - val_loss: 0.2207 - val_accuracy: 0.9439 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9503}, \u001b[0m\u001b[0;33mloss{0.1685}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2207\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m521.12 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m433.13 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m87.99 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [28] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m29\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 168)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 169/174\n", - "256/256 [==============================] - 77s 283ms/step - loss: 0.1920 - accuracy: 0.9395 - val_loss: 0.1970 - val_accuracy: 0.9183 - lr: 0.0098\n", - "Epoch 170/174\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.1269 - accuracy: 0.9636 - val_loss: 0.1754 - val_accuracy: 0.9455 - lr: 0.0098\n", - "Epoch 171/174\n", - "256/256 [==============================] - 70s 275ms/step - loss: 0.0881 - accuracy: 0.9753 - val_loss: 0.2025 - val_accuracy: 0.9423 - lr: 0.0098\n", - "Epoch 172/174\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0649 - accuracy: 0.9812 - val_loss: 0.2053 - val_accuracy: 0.9263 - lr: 0.0098\n", - "Epoch 173/174\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0409 - accuracy: 0.9890 - val_loss: 0.2178 - val_accuracy: 0.9327 - lr: 0.0098\n", - "Epoch 174/174\n", - "256/256 [==============================] - 70s 274ms/step - loss: 0.0601 - accuracy: 0.9810 - val_loss: 0.2450 - val_accuracy: 0.9311 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9455}, \u001b[0m\u001b[0;33mloss{0.1754}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9311\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2450\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m519.28 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m431.00 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m88.28 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [29] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m30\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 174)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 175/180\n", - "256/256 [==============================] - 77s 284ms/step - loss: 0.1802 - accuracy: 0.9473 - val_loss: 0.1820 - val_accuracy: 0.9503 - lr: 0.0098\n", - "Epoch 176/180\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1165 - accuracy: 0.9634 - val_loss: 0.2613 - val_accuracy: 0.9263 - lr: 0.0098\n", - "Epoch 177/180\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0847 - accuracy: 0.9751 - val_loss: 0.2826 - val_accuracy: 0.9247 - lr: 0.0098\n", - "Epoch 178/180\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0618 - accuracy: 0.9819 - val_loss: 0.2232 - val_accuracy: 0.9295 - lr: 0.0098\n", - "Epoch 179/180\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0464 - accuracy: 0.9858 - val_loss: 0.6330 - val_accuracy: 0.8718 - lr: 0.0098\n", - "Epoch 180/180\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0441 - accuracy: 0.9873 - val_loss: 0.3597 - val_accuracy: 0.9247 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9503}, \u001b[0m\u001b[0;33mloss{0.1820}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9247\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3597\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m524.83 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m432.33 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m92.50 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [30] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m31\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 180)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 181/186\n", - "256/256 [==============================] - 77s 283ms/step - loss: 0.1875 - accuracy: 0.9390 - val_loss: 0.3153 - val_accuracy: 0.8798 - lr: 0.0098\n", - "Epoch 182/186\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.1251 - accuracy: 0.9646 - val_loss: 0.2459 - val_accuracy: 0.9215 - lr: 0.0098\n", - "Epoch 183/186\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0922 - accuracy: 0.9729 - val_loss: 0.1697 - val_accuracy: 0.9439 - lr: 0.0098\n", - "Epoch 184/186\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0712 - accuracy: 0.9814 - val_loss: 0.4005 - val_accuracy: 0.8926 - lr: 0.0098\n", - "Epoch 185/186\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0475 - accuracy: 0.9875 - val_loss: 0.2829 - val_accuracy: 0.9311 - lr: 0.0098\n", - "Epoch 186/186\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0462 - accuracy: 0.9895 - val_loss: 0.2588 - val_accuracy: 0.9231 - lr: 0.0098\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9439}, \u001b[0m\u001b[0;33mloss{0.1697}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9231\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2588\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m527.27 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m433.39 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m93.88 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [31] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m32\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 186)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 187/192\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1648 - accuracy: 0.9492 - val_loss: 0.2811 - val_accuracy: 0.9087 - lr: 0.0098\n", - "Epoch 188/192\n", - "256/256 [==============================] - ETA: 0s - loss: 0.1060 - accuracy: 0.9678\n", - "Epoch 188: ReduceLROnPlateau reducing learning rate to 0.009643239349126816.\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.1060 - accuracy: 0.9678 - val_loss: 0.2874 - val_accuracy: 0.9135 - lr: 0.0098\n", - "Epoch 189/192\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0762 - accuracy: 0.9807 - val_loss: 0.1937 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 190/192\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0565 - accuracy: 0.9854 - val_loss: 0.3148 - val_accuracy: 0.9263 - lr: 0.0096\n", - "Epoch 191/192\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0482 - accuracy: 0.9880 - val_loss: 0.2285 - val_accuracy: 0.9006 - lr: 0.0096\n", - "Epoch 192/192\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0387 - accuracy: 0.9895 - val_loss: 0.2529 - val_accuracy: 0.9375 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9375}, \u001b[0m\u001b[0;33mloss{0.1937}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9375\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2529\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m528.81 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.34 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m93.47 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [32] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m33\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 192)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 193/198\n", - "256/256 [==============================] - 77s 284ms/step - loss: 0.1693 - accuracy: 0.9453 - val_loss: 0.1848 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 194/198\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.1097 - accuracy: 0.9668 - val_loss: 0.1614 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 195/198\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0705 - accuracy: 0.9771 - val_loss: 0.2779 - val_accuracy: 0.9247 - lr: 0.0096\n", - "Epoch 196/198\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0583 - accuracy: 0.9824 - val_loss: 0.2878 - val_accuracy: 0.9407 - lr: 0.0096\n", - "Epoch 197/198\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0482 - accuracy: 0.9868 - val_loss: 0.3605 - val_accuracy: 0.9247 - lr: 0.0096\n", - "Epoch 198/198\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0361 - accuracy: 0.9885 - val_loss: 0.2136 - val_accuracy: 0.9391 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9407}, \u001b[0m\u001b[0;33mloss{0.1614}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9391\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2137\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m528.40 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m433.79 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m94.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [33] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m34\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 198)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 199/204\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1925 - accuracy: 0.9436 - val_loss: 0.1574 - val_accuracy: 0.9519 - lr: 0.0096\n", - "Epoch 200/204\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1273 - accuracy: 0.9609 - val_loss: 0.2147 - val_accuracy: 0.9407 - lr: 0.0096\n", - "Epoch 201/204\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0876 - accuracy: 0.9717 - val_loss: 0.2848 - val_accuracy: 0.9022 - lr: 0.0096\n", - "Epoch 202/204\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0617 - accuracy: 0.9822 - val_loss: 0.2692 - val_accuracy: 0.9327 - lr: 0.0096\n", - "Epoch 203/204\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0496 - accuracy: 0.9861 - val_loss: 0.1747 - val_accuracy: 0.9503 - lr: 0.0096\n", - "Epoch 204/204\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0379 - accuracy: 0.9900 - val_loss: 0.2128 - val_accuracy: 0.9407 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9519}, \u001b[0m\u001b[0;33mloss{0.1574}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9407\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2128\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m527.84 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m432.60 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m95.24 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [34] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m35\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 204)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 205/210\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1705 - accuracy: 0.9463 - val_loss: 0.3243 - val_accuracy: 0.9103 - lr: 0.0096\n", - "Epoch 206/210\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.1079 - accuracy: 0.9634 - val_loss: 0.2504 - val_accuracy: 0.9359 - lr: 0.0096\n", - "Epoch 207/210\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0722 - accuracy: 0.9766 - val_loss: 0.3823 - val_accuracy: 0.9119 - lr: 0.0096\n", - "Epoch 208/210\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0482 - accuracy: 0.9863 - val_loss: 0.2689 - val_accuracy: 0.9375 - lr: 0.0096\n", - "Epoch 209/210\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0357 - accuracy: 0.9900 - val_loss: 0.2405 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 210/210\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0374 - accuracy: 0.9885 - val_loss: 0.3618 - val_accuracy: 0.9423 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.2405}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9423\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3618\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m530.09 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.61 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m94.48 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [35] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m36\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 210)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 211/216\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1826 - accuracy: 0.9414 - val_loss: 0.2124 - val_accuracy: 0.9359 - lr: 0.0096\n", - "Epoch 212/216\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1050 - accuracy: 0.9666 - val_loss: 0.2501 - val_accuracy: 0.9327 - lr: 0.0096\n", - "Epoch 213/216\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0695 - accuracy: 0.9780 - val_loss: 0.2009 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 214/216\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0432 - accuracy: 0.9868 - val_loss: 0.1850 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 215/216\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0376 - accuracy: 0.9890 - val_loss: 0.1988 - val_accuracy: 0.9535 - lr: 0.0096\n", - "Epoch 216/216\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0287 - accuracy: 0.9939 - val_loss: 0.2456 - val_accuracy: 0.9439 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9535}, \u001b[0m\u001b[0;33mloss{0.1850}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2456\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m533.03 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.18 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m97.85 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [36] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m37\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 216)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 217/222\n", - "256/256 [==============================] - 77s 284ms/step - loss: 0.1854 - accuracy: 0.9436 - val_loss: 0.1820 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 218/222\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.1210 - accuracy: 0.9619 - val_loss: 0.1830 - val_accuracy: 0.9407 - lr: 0.0096\n", - "Epoch 219/222\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0846 - accuracy: 0.9763 - val_loss: 0.5565 - val_accuracy: 0.8590 - lr: 0.0096\n", - "Epoch 220/222\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0700 - accuracy: 0.9812 - val_loss: 0.2388 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 221/222\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0406 - accuracy: 0.9895 - val_loss: 0.2682 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 222/222\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0396 - accuracy: 0.9912 - val_loss: 0.2547 - val_accuracy: 0.9423 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1820}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9423\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2547\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m530.61 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m433.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m97.26 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [37] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m38\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 222)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 223/228\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1648 - accuracy: 0.9492 - val_loss: 0.1929 - val_accuracy: 0.9359 - lr: 0.0096\n", - "Epoch 224/228\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.1032 - accuracy: 0.9680 - val_loss: 0.2054 - val_accuracy: 0.9391 - lr: 0.0096\n", - "Epoch 225/228\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0676 - accuracy: 0.9827 - val_loss: 0.2465 - val_accuracy: 0.9327 - lr: 0.0096\n", - "Epoch 226/228\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0484 - accuracy: 0.9873 - val_loss: 0.2819 - val_accuracy: 0.9407 - lr: 0.0096\n", - "Epoch 227/228\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0391 - accuracy: 0.9883 - val_loss: 0.3457 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 228/228\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0236 - accuracy: 0.9941 - val_loss: 0.3316 - val_accuracy: 0.9263 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9407}, \u001b[0m\u001b[0;33mloss{0.1929}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9263\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3316\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.19GB, used: 18.81GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m534.80 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.83 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m98.97 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [38] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m39\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 228)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 229/234\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1775 - accuracy: 0.9451 - val_loss: 0.1967 - val_accuracy: 0.9231 - lr: 0.0096\n", - "Epoch 230/234\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.1063 - accuracy: 0.9644 - val_loss: 0.2430 - val_accuracy: 0.9343 - lr: 0.0096\n", - "Epoch 231/234\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0785 - accuracy: 0.9775 - val_loss: 0.1958 - val_accuracy: 0.9279 - lr: 0.0096\n", - "Epoch 232/234\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0495 - accuracy: 0.9863 - val_loss: 0.3232 - val_accuracy: 0.9311 - lr: 0.0096\n", - "Epoch 233/234\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0378 - accuracy: 0.9888 - val_loss: 0.2346 - val_accuracy: 0.9439 - lr: 0.0096\n", - "Epoch 234/234\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0411 - accuracy: 0.9888 - val_loss: 0.4498 - val_accuracy: 0.8926 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9439}, \u001b[0m\u001b[0;33mloss{0.1958}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8926\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4497\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m534.70 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.67 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m99.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [39] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m40\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 234)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 235/240\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1779 - accuracy: 0.9412 - val_loss: 0.2640 - val_accuracy: 0.9022 - lr: 0.0096\n", - "Epoch 236/240\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.1238 - accuracy: 0.9592 - val_loss: 0.2169 - val_accuracy: 0.9391 - lr: 0.0096\n", - "Epoch 237/240\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0842 - accuracy: 0.9756 - val_loss: 0.4989 - val_accuracy: 0.9071 - lr: 0.0096\n", - "Epoch 238/240\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0577 - accuracy: 0.9854 - val_loss: 0.4745 - val_accuracy: 0.8926 - lr: 0.0096\n", - "Epoch 239/240\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0469 - accuracy: 0.9866 - val_loss: 0.2976 - val_accuracy: 0.9279 - lr: 0.0096\n", - "Epoch 240/240\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0304 - accuracy: 0.9937 - val_loss: 0.4848 - val_accuracy: 0.9103 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9391}, \u001b[0m\u001b[0;33mloss{0.2169}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9103\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4847\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m536.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.41 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m101.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [40] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m41\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 240)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 241/246\n", - "256/256 [==============================] - 77s 286ms/step - loss: 0.1722 - accuracy: 0.9431 - val_loss: 0.3465 - val_accuracy: 0.9022 - lr: 0.0096\n", - "Epoch 242/246\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.1058 - accuracy: 0.9678 - val_loss: 0.2628 - val_accuracy: 0.9295 - lr: 0.0096\n", - "Epoch 243/246\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0724 - accuracy: 0.9773 - val_loss: 0.2259 - val_accuracy: 0.9263 - lr: 0.0096\n", - "Epoch 244/246\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0526 - accuracy: 0.9856 - val_loss: 0.4048 - val_accuracy: 0.9071 - lr: 0.0096\n", - "Epoch 245/246\n", - "256/256 [==============================] - 71s 275ms/step - loss: 0.0383 - accuracy: 0.9893 - val_loss: 0.3190 - val_accuracy: 0.9231 - lr: 0.0096\n", - "Epoch 246/246\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0287 - accuracy: 0.9922 - val_loss: 0.5040 - val_accuracy: 0.9215 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9295}, \u001b[0m\u001b[0;33mloss{0.2259}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9215\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.5041\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m532.98 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m432.80 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m100.18 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [41] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m42\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 246)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33m└───Shuffling data...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;31m- Debug DP Sample dir: \u001b[0m\u001b[0;32mSamples/TSR_SUB_400_y2024_m03_d30-h02_m38_s03\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 247/252\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1686 - accuracy: 0.9458 - val_loss: 0.2969 - val_accuracy: 0.9295 - lr: 0.0096\n", - "Epoch 248/252\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0966 - accuracy: 0.9727 - val_loss: 0.2599 - val_accuracy: 0.9423 - lr: 0.0096\n", - "Epoch 249/252\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0879 - accuracy: 0.9775 - val_loss: 0.2880 - val_accuracy: 0.9199 - lr: 0.0096\n", - "Epoch 250/252\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0486 - accuracy: 0.9863 - val_loss: 0.2426 - val_accuracy: 0.9391 - lr: 0.0096\n", - "Epoch 251/252\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0358 - accuracy: 0.9917 - val_loss: 0.2913 - val_accuracy: 0.9263 - lr: 0.0096\n", - "Epoch 252/252\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0311 - accuracy: 0.9915 - val_loss: 0.2226 - val_accuracy: 0.9407 - lr: 0.0096\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.2226}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9407\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2226\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m550.51 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.23 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m115.28 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [42] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m43\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 252)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 253/258\n", - "256/256 [==============================] - ETA: 0s - loss: 0.1562 - accuracy: 0.9495\n", - "Epoch 253: ReduceLROnPlateau reducing learning rate to 0.009469660667702556.\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1562 - accuracy: 0.9495 - val_loss: 0.1962 - val_accuracy: 0.9279 - lr: 0.0096\n", - "Epoch 254/258\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0941 - accuracy: 0.9719 - val_loss: 0.2699 - val_accuracy: 0.9103 - lr: 0.0095\n", - "Epoch 255/258\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0692 - accuracy: 0.9788 - val_loss: 0.3234 - val_accuracy: 0.9103 - lr: 0.0095\n", - "Epoch 256/258\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0420 - accuracy: 0.9895 - val_loss: 0.3635 - val_accuracy: 0.9151 - lr: 0.0095\n", - "Epoch 257/258\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0337 - accuracy: 0.9910 - val_loss: 0.3884 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 258/258\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0294 - accuracy: 0.9919 - val_loss: 0.4633 - val_accuracy: 0.9167 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9295}, \u001b[0m\u001b[0;33mloss{0.1962}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9167\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4633\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m537.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.55 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m102.41 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [43] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m44\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 258)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 259/264\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1649 - accuracy: 0.9478 - val_loss: 0.2313 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 260/264\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.1053 - accuracy: 0.9668 - val_loss: 0.1970 - val_accuracy: 0.9391 - lr: 0.0095\n", - "Epoch 261/264\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0735 - accuracy: 0.9790 - val_loss: 0.2894 - val_accuracy: 0.9103 - lr: 0.0095\n", - "Epoch 262/264\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0540 - accuracy: 0.9861 - val_loss: 0.3597 - val_accuracy: 0.9215 - lr: 0.0095\n", - "Epoch 263/264\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0364 - accuracy: 0.9922 - val_loss: 0.2845 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 264/264\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0347 - accuracy: 0.9912 - val_loss: 0.3006 - val_accuracy: 0.9327 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9391}, \u001b[0m\u001b[0;33mloss{0.1970}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9327\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3006\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m539.13 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.24 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m103.88 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [44] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m45\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 264)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 265/270\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1549 - accuracy: 0.9541 - val_loss: 0.3054 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 266/270\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0943 - accuracy: 0.9709 - val_loss: 0.2693 - val_accuracy: 0.9327 - lr: 0.0095\n", - "Epoch 267/270\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0682 - accuracy: 0.9802 - val_loss: 0.2379 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 268/270\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0489 - accuracy: 0.9868 - val_loss: 0.1810 - val_accuracy: 0.9423 - lr: 0.0095\n", - "Epoch 269/270\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0295 - accuracy: 0.9917 - val_loss: 0.4588 - val_accuracy: 0.9006 - lr: 0.0095\n", - "Epoch 270/270\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0214 - accuracy: 0.9951 - val_loss: 0.4001 - val_accuracy: 0.9119 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1810}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9119\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4001\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m543.38 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.16 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m106.22 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [45] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m46\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 270)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 271/276\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1875 - accuracy: 0.9353 - val_loss: 0.1975 - val_accuracy: 0.9423 - lr: 0.0095\n", - "Epoch 272/276\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.1151 - accuracy: 0.9612 - val_loss: 0.2110 - val_accuracy: 0.9327 - lr: 0.0095\n", - "Epoch 273/276\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0753 - accuracy: 0.9773 - val_loss: 0.1985 - val_accuracy: 0.9423 - lr: 0.0095\n", - "Epoch 274/276\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0634 - accuracy: 0.9802 - val_loss: 0.2084 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 275/276\n", - "256/256 [==============================] - 71s 279ms/step - loss: 0.0407 - accuracy: 0.9868 - val_loss: 0.2229 - val_accuracy: 0.9407 - lr: 0.0095\n", - "Epoch 276/276\n", - "256/256 [==============================] - 72s 278ms/step - loss: 0.0294 - accuracy: 0.9922 - val_loss: 0.2511 - val_accuracy: 0.9423 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1975}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9423\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2511\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m539.92 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m435.51 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m104.41 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [46] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m47\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 276)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 277/282\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1688 - accuracy: 0.9482 - val_loss: 0.1570 - val_accuracy: 0.9471 - lr: 0.0095\n", - "Epoch 278/282\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0959 - accuracy: 0.9692 - val_loss: 0.1613 - val_accuracy: 0.9375 - lr: 0.0095\n", - "Epoch 279/282\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0664 - accuracy: 0.9802 - val_loss: 0.1662 - val_accuracy: 0.9359 - lr: 0.0095\n", - "Epoch 280/282\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0480 - accuracy: 0.9856 - val_loss: 0.2022 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 281/282\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0376 - accuracy: 0.9893 - val_loss: 0.2449 - val_accuracy: 0.9327 - lr: 0.0095\n", - "Epoch 282/282\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0293 - accuracy: 0.9924 - val_loss: 0.2447 - val_accuracy: 0.9391 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1570}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9391\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2447\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.16GB, used: 18.84GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m540.71 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m434.45 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m106.26 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [47] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m48\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 282)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 283/288\n", - "256/256 [==============================] - 77s 285ms/step - loss: 0.1552 - accuracy: 0.9521 - val_loss: 0.2704 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 284/288\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.1001 - accuracy: 0.9688 - val_loss: 0.2616 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 285/288\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0536 - accuracy: 0.9817 - val_loss: 0.4002 - val_accuracy: 0.9135 - lr: 0.0095\n", - "Epoch 286/288\n", - "256/256 [==============================] - 71s 276ms/step - loss: 0.0378 - accuracy: 0.9888 - val_loss: 0.3390 - val_accuracy: 0.9215 - lr: 0.0095\n", - "Epoch 287/288\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0190 - accuracy: 0.9954 - val_loss: 0.5053 - val_accuracy: 0.8862 - lr: 0.0095\n", - "Epoch 288/288\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0199 - accuracy: 0.9939 - val_loss: 0.4386 - val_accuracy: 0.9103 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9295}, \u001b[0m\u001b[0;33mloss{0.2616}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9103\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4385\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m538.49 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m433.36 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m105.13 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [48] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m49\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 288)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 289/294\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1457 - accuracy: 0.9519 - val_loss: 0.2238 - val_accuracy: 0.9279 - lr: 0.0095\n", - "Epoch 290/294\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0863 - accuracy: 0.9753 - val_loss: 0.2242 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 291/294\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0620 - accuracy: 0.9812 - val_loss: 0.2938 - val_accuracy: 0.9231 - lr: 0.0095\n", - "Epoch 292/294\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0400 - accuracy: 0.9880 - val_loss: 0.3755 - val_accuracy: 0.9054 - lr: 0.0095\n", - "Epoch 293/294\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0354 - accuracy: 0.9900 - val_loss: 0.4175 - val_accuracy: 0.9103 - lr: 0.0095\n", - "Epoch 294/294\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0219 - accuracy: 0.9941 - val_loss: 0.4969 - val_accuracy: 0.9054 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9343}, \u001b[0m\u001b[0;33mloss{0.2238}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9054\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4968\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m546.42 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.29 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m109.13 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [49] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m50\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 294)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 295/300\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1733 - accuracy: 0.9436 - val_loss: 0.2319 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 296/300\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.1085 - accuracy: 0.9646 - val_loss: 0.2159 - val_accuracy: 0.9311 - lr: 0.0095\n", - "Epoch 297/300\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0659 - accuracy: 0.9795 - val_loss: 0.2045 - val_accuracy: 0.9343 - lr: 0.0095\n", - "Epoch 298/300\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0421 - accuracy: 0.9885 - val_loss: 0.1744 - val_accuracy: 0.9407 - lr: 0.0095\n", - "Epoch 299/300\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0349 - accuracy: 0.9902 - val_loss: 0.3020 - val_accuracy: 0.9439 - lr: 0.0095\n", - "Epoch 300/300\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0290 - accuracy: 0.9924 - val_loss: 0.3009 - val_accuracy: 0.9455 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9455}, \u001b[0m\u001b[0;33mloss{0.1744}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9455\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3008\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m546.17 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m440.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m105.28 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [50] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m51\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 300)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 301/306\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1551 - accuracy: 0.9495 - val_loss: 0.1855 - val_accuracy: 0.9487 - lr: 0.0095\n", - "Epoch 302/306\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0895 - accuracy: 0.9719 - val_loss: 0.2617 - val_accuracy: 0.9359 - lr: 0.0095\n", - "Epoch 303/306\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0615 - accuracy: 0.9844 - val_loss: 0.2679 - val_accuracy: 0.9359 - lr: 0.0095\n", - "Epoch 304/306\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0486 - accuracy: 0.9863 - val_loss: 0.2134 - val_accuracy: 0.9359 - lr: 0.0095\n", - "Epoch 305/306\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0334 - accuracy: 0.9912 - val_loss: 0.2021 - val_accuracy: 0.9295 - lr: 0.0095\n", - "Epoch 306/306\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0224 - accuracy: 0.9944 - val_loss: 0.2594 - val_accuracy: 0.9343 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9487}, \u001b[0m\u001b[0;33mloss{0.1855}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9343\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2593\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m545.63 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m436.74 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m108.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [51] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m52\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 306)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 307/312\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1859 - accuracy: 0.9370 - val_loss: 0.2198 - val_accuracy: 0.9327 - lr: 0.0095\n", - "Epoch 308/312\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.1066 - accuracy: 0.9648 - val_loss: 0.2533 - val_accuracy: 0.9247 - lr: 0.0095\n", - "Epoch 309/312\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0696 - accuracy: 0.9780 - val_loss: 0.3515 - val_accuracy: 0.9263 - lr: 0.0095\n", - "Epoch 310/312\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0519 - accuracy: 0.9836 - val_loss: 0.2943 - val_accuracy: 0.9311 - lr: 0.0095\n", - "Epoch 311/312\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0390 - accuracy: 0.9900 - val_loss: 0.3001 - val_accuracy: 0.9311 - lr: 0.0095\n", - "Epoch 312/312\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0265 - accuracy: 0.9937 - val_loss: 0.4250 - val_accuracy: 0.9295 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9327}, \u001b[0m\u001b[0;33mloss{0.2198}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9295\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4250\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m547.27 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m436.31 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m110.95 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [52] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m53\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 312)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 313/318\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1569 - accuracy: 0.9460 - val_loss: 0.2276 - val_accuracy: 0.9375 - lr: 0.0095\n", - "Epoch 314/318\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0949 - accuracy: 0.9717 - val_loss: 0.2151 - val_accuracy: 0.9407 - lr: 0.0095\n", - "Epoch 315/318\n", - "256/256 [==============================] - 72s 278ms/step - loss: 0.0694 - accuracy: 0.9800 - val_loss: 0.2282 - val_accuracy: 0.9391 - lr: 0.0095\n", - "Epoch 316/318\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0497 - accuracy: 0.9868 - val_loss: 0.2215 - val_accuracy: 0.9375 - lr: 0.0095\n", - "Epoch 317/318\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0354 - accuracy: 0.9900 - val_loss: 0.2642 - val_accuracy: 0.9311 - lr: 0.0095\n", - "Epoch 318/318\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0274 - accuracy: 0.9937\n", - "Epoch 318: ReduceLROnPlateau reducing learning rate to 0.009299207033589482.\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0274 - accuracy: 0.9937 - val_loss: 0.2980 - val_accuracy: 0.9263 - lr: 0.0095\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9407}, \u001b[0m\u001b[0;33mloss{0.2151}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9263\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2981\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m550.42 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.37 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m113.05 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [53] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m54\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 318)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 319/324\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1510 - accuracy: 0.9531 - val_loss: 0.1710 - val_accuracy: 0.9407 - lr: 0.0093\n", - "Epoch 320/324\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0903 - accuracy: 0.9714 - val_loss: 0.1643 - val_accuracy: 0.9423 - lr: 0.0093\n", - "Epoch 321/324\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0601 - accuracy: 0.9824 - val_loss: 0.2904 - val_accuracy: 0.9327 - lr: 0.0093\n", - "Epoch 322/324\n", - "256/256 [==============================] - 72s 278ms/step - loss: 0.0391 - accuracy: 0.9893 - val_loss: 0.2208 - val_accuracy: 0.9391 - lr: 0.0093\n", - "Epoch 323/324\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0324 - accuracy: 0.9915 - val_loss: 0.2139 - val_accuracy: 0.9439 - lr: 0.0093\n", - "Epoch 324/324\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0207 - accuracy: 0.9939 - val_loss: 0.2766 - val_accuracy: 0.9407 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9439}, \u001b[0m\u001b[0;33mloss{0.1643}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9407\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2766\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m550.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.08 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m112.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [54] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m55\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 324)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 325/330\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1381 - accuracy: 0.9590 - val_loss: 0.1834 - val_accuracy: 0.9391 - lr: 0.0093\n", - "Epoch 326/330\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0842 - accuracy: 0.9736 - val_loss: 0.2042 - val_accuracy: 0.9407 - lr: 0.0093\n", - "Epoch 327/330\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0535 - accuracy: 0.9854 - val_loss: 0.3113 - val_accuracy: 0.9199 - lr: 0.0093\n", - "Epoch 328/330\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0324 - accuracy: 0.9924 - val_loss: 0.2379 - val_accuracy: 0.9439 - lr: 0.0093\n", - "Epoch 329/330\n", - "256/256 [==============================] - 72s 283ms/step - loss: 0.0262 - accuracy: 0.9937 - val_loss: 0.1793 - val_accuracy: 0.9487 - lr: 0.0093\n", - "Epoch 330/330\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0233 - accuracy: 0.9941 - val_loss: 0.2066 - val_accuracy: 0.9455 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9487}, \u001b[0m\u001b[0;33mloss{0.1793}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9455\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2066\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m549.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m110.00 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [55] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m56\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 330)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 331/336\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1498 - accuracy: 0.9478 - val_loss: 0.1643 - val_accuracy: 0.9455 - lr: 0.0093\n", - "Epoch 332/336\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0890 - accuracy: 0.9705 - val_loss: 0.1541 - val_accuracy: 0.9471 - lr: 0.0093\n", - "Epoch 333/336\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0583 - accuracy: 0.9802 - val_loss: 0.2413 - val_accuracy: 0.9359 - lr: 0.0093\n", - "Epoch 334/336\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0374 - accuracy: 0.9866 - val_loss: 0.3158 - val_accuracy: 0.9375 - lr: 0.0093\n", - "Epoch 335/336\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0314 - accuracy: 0.9912 - val_loss: 0.2443 - val_accuracy: 0.9407 - lr: 0.0093\n", - "Epoch 336/336\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0226 - accuracy: 0.9934 - val_loss: 0.2873 - val_accuracy: 0.9295 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1541}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9295\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2872\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.16GB, used: 18.84GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m551.47 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.88 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m113.59 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [56] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m57\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 336)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 337/342\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1644 - accuracy: 0.9434 - val_loss: 0.1689 - val_accuracy: 0.9471 - lr: 0.0093\n", - "Epoch 338/342\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0994 - accuracy: 0.9683 - val_loss: 0.1996 - val_accuracy: 0.9391 - lr: 0.0093\n", - "Epoch 339/342\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0547 - accuracy: 0.9817 - val_loss: 0.2180 - val_accuracy: 0.9439 - lr: 0.0093\n", - "Epoch 340/342\n", - "256/256 [==============================] - 71s 277ms/step - loss: 0.0324 - accuracy: 0.9888 - val_loss: 0.3856 - val_accuracy: 0.9135 - lr: 0.0093\n", - "Epoch 341/342\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0305 - accuracy: 0.9907 - val_loss: 0.3454 - val_accuracy: 0.9391 - lr: 0.0093\n", - "Epoch 342/342\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0255 - accuracy: 0.9939 - val_loss: 0.4204 - val_accuracy: 0.9215 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1689}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9215\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4204\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m550.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m436.75 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m113.87 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [57] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m58\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 342)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 343/348\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1762 - accuracy: 0.9375 - val_loss: 0.2056 - val_accuracy: 0.9183 - lr: 0.0093\n", - "Epoch 344/348\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.1109 - accuracy: 0.9626 - val_loss: 0.1948 - val_accuracy: 0.9311 - lr: 0.0093\n", - "Epoch 345/348\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0762 - accuracy: 0.9780 - val_loss: 0.2274 - val_accuracy: 0.9343 - lr: 0.0093\n", - "Epoch 346/348\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0495 - accuracy: 0.9851 - val_loss: 0.2694 - val_accuracy: 0.9311 - lr: 0.0093\n", - "Epoch 347/348\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0362 - accuracy: 0.9895 - val_loss: 0.2763 - val_accuracy: 0.9423 - lr: 0.0093\n", - "Epoch 348/348\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0209 - accuracy: 0.9946 - val_loss: 0.2977 - val_accuracy: 0.9391 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1948}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9391\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2976\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m552.41 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.31 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m113.10 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [58] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m59\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 348)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 349/354\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1428 - accuracy: 0.9558 - val_loss: 0.2571 - val_accuracy: 0.9151 - lr: 0.0093\n", - "Epoch 350/354\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0798 - accuracy: 0.9736 - val_loss: 0.2159 - val_accuracy: 0.9535 - lr: 0.0093\n", - "Epoch 351/354\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0534 - accuracy: 0.9836 - val_loss: 0.2903 - val_accuracy: 0.9263 - lr: 0.0093\n", - "Epoch 352/354\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0337 - accuracy: 0.9927 - val_loss: 0.2496 - val_accuracy: 0.9423 - lr: 0.0093\n", - "Epoch 353/354\n", - "256/256 [==============================] - 72s 278ms/step - loss: 0.0310 - accuracy: 0.9924 - val_loss: 0.2418 - val_accuracy: 0.9407 - lr: 0.0093\n", - "Epoch 354/354\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0266 - accuracy: 0.9922 - val_loss: 0.3734 - val_accuracy: 0.9311 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9535}, \u001b[0m\u001b[0;33mloss{0.2159}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9311\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3735\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m550.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.79 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m113.17 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [59] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m60\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 354)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 355/360\n", - "256/256 [==============================] - 78s 286ms/step - loss: 0.1507 - accuracy: 0.9507 - val_loss: 0.1681 - val_accuracy: 0.9359 - lr: 0.0093\n", - "Epoch 356/360\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0962 - accuracy: 0.9705 - val_loss: 0.2051 - val_accuracy: 0.9391 - lr: 0.0093\n", - "Epoch 357/360\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0647 - accuracy: 0.9788 - val_loss: 0.2295 - val_accuracy: 0.9423 - lr: 0.0093\n", - "Epoch 358/360\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0327 - accuracy: 0.9905 - val_loss: 0.2502 - val_accuracy: 0.9455 - lr: 0.0093\n", - "Epoch 359/360\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0246 - accuracy: 0.9937 - val_loss: 0.2248 - val_accuracy: 0.9439 - lr: 0.0093\n", - "Epoch 360/360\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0268 - accuracy: 0.9944 - val_loss: 0.2514 - val_accuracy: 0.9391 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9455}, \u001b[0m\u001b[0;33mloss{0.1681}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9391\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2514\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m555.71 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.11 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m116.60 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [60] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m61\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 360)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 361/366\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1526 - accuracy: 0.9478 - val_loss: 0.1712 - val_accuracy: 0.9375 - lr: 0.0093\n", - "Epoch 362/366\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0930 - accuracy: 0.9712 - val_loss: 0.1701 - val_accuracy: 0.9487 - lr: 0.0093\n", - "Epoch 363/366\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0547 - accuracy: 0.9846 - val_loss: 0.3175 - val_accuracy: 0.9295 - lr: 0.0093\n", - "Epoch 364/366\n", - "256/256 [==============================] - 71s 278ms/step - loss: 0.0312 - accuracy: 0.9895 - val_loss: 0.2525 - val_accuracy: 0.9407 - lr: 0.0093\n", - "Epoch 365/366\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0218 - accuracy: 0.9941 - val_loss: 0.3255 - val_accuracy: 0.9327 - lr: 0.0093\n", - "Epoch 366/366\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0187 - accuracy: 0.9954 - val_loss: 0.2214 - val_accuracy: 0.9439 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9487}, \u001b[0m\u001b[0;33mloss{0.1701}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2214\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m552.81 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m437.90 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m114.90 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [61] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m62\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 366)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 367/372\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1570 - accuracy: 0.9517 - val_loss: 0.2226 - val_accuracy: 0.9263 - lr: 0.0093\n", - "Epoch 368/372\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.1003 - accuracy: 0.9690 - val_loss: 0.2266 - val_accuracy: 0.9327 - lr: 0.0093\n", - "Epoch 369/372\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0663 - accuracy: 0.9817 - val_loss: 0.3376 - val_accuracy: 0.9167 - lr: 0.0093\n", - "Epoch 370/372\n", - "256/256 [==============================] - 71s 279ms/step - loss: 0.0470 - accuracy: 0.9844 - val_loss: 0.2824 - val_accuracy: 0.9151 - lr: 0.0093\n", - "Epoch 371/372\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0282 - accuracy: 0.9912 - val_loss: 0.3004 - val_accuracy: 0.9167 - lr: 0.0093\n", - "Epoch 372/372\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0243 - accuracy: 0.9944 - val_loss: 0.2254 - val_accuracy: 0.9327 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9327}, \u001b[0m\u001b[0;33mloss{0.2226}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9327\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2254\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m551.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.57 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m112.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [62] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m63\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 372)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 373/378\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1464 - accuracy: 0.9521 - val_loss: 0.3296 - val_accuracy: 0.9135 - lr: 0.0093\n", - "Epoch 374/378\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0846 - accuracy: 0.9758 - val_loss: 0.3144 - val_accuracy: 0.9167 - lr: 0.0093\n", - "Epoch 375/378\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0528 - accuracy: 0.9841 - val_loss: 0.2769 - val_accuracy: 0.9151 - lr: 0.0093\n", - "Epoch 376/378\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0304 - accuracy: 0.9897 - val_loss: 0.4158 - val_accuracy: 0.9071 - lr: 0.0093\n", - "Epoch 377/378\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0290 - accuracy: 0.9937 - val_loss: 0.2375 - val_accuracy: 0.9215 - lr: 0.0093\n", - "Epoch 378/378\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0267 - accuracy: 0.9927 - val_loss: 0.1940 - val_accuracy: 0.9407 - lr: 0.0093\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9407}, \u001b[0m\u001b[0;33mloss{0.1940}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9407\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1940\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m555.86 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m440.61 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m115.25 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [63] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m64\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 378)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 379/384\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1658 - accuracy: 0.9478 - val_loss: 0.1683 - val_accuracy: 0.9311 - lr: 0.0093\n", - "Epoch 380/384\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.1027 - accuracy: 0.9697 - val_loss: 0.1709 - val_accuracy: 0.9327 - lr: 0.0093\n", - "Epoch 381/384\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0663 - accuracy: 0.9802 - val_loss: 0.1952 - val_accuracy: 0.9423 - lr: 0.0093\n", - "Epoch 382/384\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0364 - accuracy: 0.9895 - val_loss: 0.2132 - val_accuracy: 0.9279 - lr: 0.0093\n", - "Epoch 383/384\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0272 - accuracy: 0.9941\n", - "Epoch 383: ReduceLROnPlateau reducing learning rate to 0.009131821744143963.\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0272 - accuracy: 0.9941 - val_loss: 0.2627 - val_accuracy: 0.9151 - lr: 0.0093\n", - "Epoch 384/384\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0305 - accuracy: 0.9937 - val_loss: 0.2253 - val_accuracy: 0.9263 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1683}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9263\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2253\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m557.97 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m440.50 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m117.47 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [64] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m65\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 384)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 385/390\n", - "256/256 [==============================] - 78s 287ms/step - loss: 0.1475 - accuracy: 0.9512 - val_loss: 0.1970 - val_accuracy: 0.9247 - lr: 0.0091\n", - "Epoch 386/390\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0880 - accuracy: 0.9719 - val_loss: 0.2173 - val_accuracy: 0.9375 - lr: 0.0091\n", - "Epoch 387/390\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0646 - accuracy: 0.9817 - val_loss: 0.1910 - val_accuracy: 0.9375 - lr: 0.0091\n", - "Epoch 388/390\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0267 - accuracy: 0.9937 - val_loss: 0.3254 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 389/390\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0243 - accuracy: 0.9934 - val_loss: 0.2513 - val_accuracy: 0.9359 - lr: 0.0091\n", - "Epoch 390/390\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0185 - accuracy: 0.9941 - val_loss: 0.2746 - val_accuracy: 0.9295 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9375}, \u001b[0m\u001b[0;33mloss{0.1910}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9295\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2746\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m555.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.76 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m116.27 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [65] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m66\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 390)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 391/396\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1466 - accuracy: 0.9553 - val_loss: 0.1735 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 392/396\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0834 - accuracy: 0.9744 - val_loss: 0.2050 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 393/396\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0528 - accuracy: 0.9849 - val_loss: 0.2451 - val_accuracy: 0.9247 - lr: 0.0091\n", - "Epoch 394/396\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0319 - accuracy: 0.9907 - val_loss: 0.2601 - val_accuracy: 0.9407 - lr: 0.0091\n", - "Epoch 395/396\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0238 - accuracy: 0.9944 - val_loss: 0.3207 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 396/396\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0176 - accuracy: 0.9961 - val_loss: 0.2425 - val_accuracy: 0.9455 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9455}, \u001b[0m\u001b[0;33mloss{0.1735}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9439\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2558\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m561.06 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.89 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m121.16 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [66] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m67\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 396)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 397/402\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1413 - accuracy: 0.9556 - val_loss: 0.2070 - val_accuracy: 0.9215 - lr: 0.0091\n", - "Epoch 398/402\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0911 - accuracy: 0.9719 - val_loss: 0.1711 - val_accuracy: 0.9407 - lr: 0.0091\n", - "Epoch 399/402\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0450 - accuracy: 0.9868 - val_loss: 0.2181 - val_accuracy: 0.9263 - lr: 0.0091\n", - "Epoch 400/402\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0310 - accuracy: 0.9922 - val_loss: 0.1772 - val_accuracy: 0.9375 - lr: 0.0091\n", - "Epoch 401/402\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0230 - accuracy: 0.9941 - val_loss: 0.1968 - val_accuracy: 0.9471 - lr: 0.0091\n", - "Epoch 402/402\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0228 - accuracy: 0.9944 - val_loss: 0.2389 - val_accuracy: 0.9263 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1711}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9263\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2390\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m558.20 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.77 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m118.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [67] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m68\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 402)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 403/408\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1415 - accuracy: 0.9543 - val_loss: 0.1678 - val_accuracy: 0.9423 - lr: 0.0091\n", - "Epoch 404/408\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0974 - accuracy: 0.9717 - val_loss: 0.2233 - val_accuracy: 0.9167 - lr: 0.0091\n", - "Epoch 405/408\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0535 - accuracy: 0.9839 - val_loss: 0.1927 - val_accuracy: 0.9279 - lr: 0.0091\n", - "Epoch 406/408\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0391 - accuracy: 0.9883 - val_loss: 0.2091 - val_accuracy: 0.9279 - lr: 0.0091\n", - "Epoch 407/408\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0260 - accuracy: 0.9924 - val_loss: 0.2332 - val_accuracy: 0.9295 - lr: 0.0091\n", - "Epoch 408/408\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0215 - accuracy: 0.9949 - val_loss: 0.2343 - val_accuracy: 0.9279 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1678}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9279\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2343\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m558.04 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.78 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m119.26 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [68] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m69\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 408)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 409/414\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1623 - accuracy: 0.9475 - val_loss: 0.1975 - val_accuracy: 0.9391 - lr: 0.0091\n", - "Epoch 410/414\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.1023 - accuracy: 0.9653 - val_loss: 0.1627 - val_accuracy: 0.9471 - lr: 0.0091\n", - "Epoch 411/414\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0608 - accuracy: 0.9824 - val_loss: 0.2578 - val_accuracy: 0.9199 - lr: 0.0091\n", - "Epoch 412/414\n", - "256/256 [==============================] - 72s 278ms/step - loss: 0.0401 - accuracy: 0.9888 - val_loss: 0.2376 - val_accuracy: 0.9375 - lr: 0.0091\n", - "Epoch 413/414\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0334 - accuracy: 0.9902 - val_loss: 0.2274 - val_accuracy: 0.9359 - lr: 0.0091\n", - "Epoch 414/414\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0218 - accuracy: 0.9941 - val_loss: 0.2506 - val_accuracy: 0.9311 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9471}, \u001b[0m\u001b[0;33mloss{0.1627}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9311\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2506\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m559.65 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.56 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m120.09 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [69] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m70\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 414)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 415/420\n", - "256/256 [==============================] - 78s 289ms/step - loss: 0.1488 - accuracy: 0.9524 - val_loss: 0.1494 - val_accuracy: 0.9423 - lr: 0.0091\n", - "Epoch 416/420\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0901 - accuracy: 0.9719 - val_loss: 0.1522 - val_accuracy: 0.9439 - lr: 0.0091\n", - "Epoch 417/420\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0483 - accuracy: 0.9863 - val_loss: 0.1585 - val_accuracy: 0.9455 - lr: 0.0091\n", - "Epoch 418/420\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0380 - accuracy: 0.9880 - val_loss: 0.2341 - val_accuracy: 0.9263 - lr: 0.0091\n", - "Epoch 419/420\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0260 - accuracy: 0.9922 - val_loss: 0.1966 - val_accuracy: 0.9487 - lr: 0.0091\n", - "Epoch 420/420\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0216 - accuracy: 0.9937 - val_loss: 0.3120 - val_accuracy: 0.9135 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-419-0.9487.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9487\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1967\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m564.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.50 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m123.11 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [70] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m71\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 420)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 421/426\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1333 - accuracy: 0.9587 - val_loss: 0.1808 - val_accuracy: 0.9407 - lr: 0.0091\n", - "Epoch 422/426\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0725 - accuracy: 0.9785 - val_loss: 0.2205 - val_accuracy: 0.9263 - lr: 0.0091\n", - "Epoch 423/426\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0480 - accuracy: 0.9873 - val_loss: 0.2139 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 424/426\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0302 - accuracy: 0.9927 - val_loss: 0.2470 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 425/426\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0242 - accuracy: 0.9939 - val_loss: 0.3428 - val_accuracy: 0.8958 - lr: 0.0091\n", - "Epoch 426/426\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0226 - accuracy: 0.9937 - val_loss: 0.2293 - val_accuracy: 0.9359 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9407}, \u001b[0m\u001b[0;33mloss{0.1808}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9359\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2293\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m561.24 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.60 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m122.64 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [71] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m72\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 426)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 427/432\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1330 - accuracy: 0.9551 - val_loss: 0.1782 - val_accuracy: 0.9375 - lr: 0.0091\n", - "Epoch 428/432\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0870 - accuracy: 0.9707 - val_loss: 0.2001 - val_accuracy: 0.9231 - lr: 0.0091\n", - "Epoch 429/432\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0539 - accuracy: 0.9814 - val_loss: 0.2954 - val_accuracy: 0.9215 - lr: 0.0091\n", - "Epoch 430/432\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0305 - accuracy: 0.9929 - val_loss: 0.3820 - val_accuracy: 0.9151 - lr: 0.0091\n", - "Epoch 431/432\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0232 - accuracy: 0.9956 - val_loss: 0.2771 - val_accuracy: 0.9279 - lr: 0.0091\n", - "Epoch 432/432\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0206 - accuracy: 0.9941 - val_loss: 0.2467 - val_accuracy: 0.9199 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9375}, \u001b[0m\u001b[0;33mloss{0.1782}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9199\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2466\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.16GB, used: 18.84GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m562.22 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m438.66 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m123.56 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [72] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m73\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 432)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 433/438\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1536 - accuracy: 0.9478 - val_loss: 0.2038 - val_accuracy: 0.9311 - lr: 0.0091\n", - "Epoch 434/438\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0833 - accuracy: 0.9751 - val_loss: 0.2294 - val_accuracy: 0.9087 - lr: 0.0091\n", - "Epoch 435/438\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0488 - accuracy: 0.9866 - val_loss: 0.2332 - val_accuracy: 0.9151 - lr: 0.0091\n", - "Epoch 436/438\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0327 - accuracy: 0.9897 - val_loss: 0.2499 - val_accuracy: 0.9167 - lr: 0.0091\n", - "Epoch 437/438\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0235 - accuracy: 0.9927 - val_loss: 0.3192 - val_accuracy: 0.9119 - lr: 0.0091\n", - "Epoch 438/438\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0188 - accuracy: 0.9944 - val_loss: 0.2932 - val_accuracy: 0.9167 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9311}, \u001b[0m\u001b[0;33mloss{0.2038}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9167\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2931\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m561.86 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.36 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m122.50 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [73] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m74\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 438)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 439/444\n", - "256/256 [==============================] - 78s 289ms/step - loss: 0.1456 - accuracy: 0.9500 - val_loss: 0.2129 - val_accuracy: 0.9022 - lr: 0.0091\n", - "Epoch 440/444\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0840 - accuracy: 0.9722 - val_loss: 0.3310 - val_accuracy: 0.9071 - lr: 0.0091\n", - "Epoch 441/444\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0483 - accuracy: 0.9849 - val_loss: 0.3311 - val_accuracy: 0.9151 - lr: 0.0091\n", - "Epoch 442/444\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0315 - accuracy: 0.9915 - val_loss: 0.2708 - val_accuracy: 0.9231 - lr: 0.0091\n", - "Epoch 443/444\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0227 - accuracy: 0.9951 - val_loss: 0.2968 - val_accuracy: 0.9231 - lr: 0.0091\n", - "Epoch 444/444\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0191 - accuracy: 0.9961 - val_loss: 0.2900 - val_accuracy: 0.9183 - lr: 0.0091\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9231}, \u001b[0m\u001b[0;33mloss{0.2129}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9183\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2900\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m569.56 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.04 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m127.52 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [74] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m75\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 444)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 445/450\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1509 - accuracy: 0.9526 - val_loss: 0.2378 - val_accuracy: 0.9006 - lr: 0.0091\n", - "Epoch 446/450\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0915 - accuracy: 0.9707 - val_loss: 0.2024 - val_accuracy: 0.9199 - lr: 0.0091\n", - "Epoch 447/450\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0512 - accuracy: 0.9819 - val_loss: 0.3725 - val_accuracy: 0.9135 - lr: 0.0091\n", - "Epoch 448/450\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0394 - accuracy: 0.9893\n", - "Epoch 448: ReduceLROnPlateau reducing learning rate to 0.008967449011281133.\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0394 - accuracy: 0.9893 - val_loss: 0.2490 - val_accuracy: 0.9119 - lr: 0.0091\n", - "Epoch 449/450\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0200 - accuracy: 0.9951 - val_loss: 0.2879 - val_accuracy: 0.9231 - lr: 0.0090\n", - "Epoch 450/450\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0201 - accuracy: 0.9954 - val_loss: 0.3820 - val_accuracy: 0.9119 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9231}, \u001b[0m\u001b[0;33mloss{0.2024}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9119\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3820\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m564.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m122.99 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [75] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m76\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 450)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 451/456\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1432 - accuracy: 0.9556 - val_loss: 0.3285 - val_accuracy: 0.8990 - lr: 0.0090\n", - "Epoch 452/456\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0862 - accuracy: 0.9749 - val_loss: 0.2752 - val_accuracy: 0.9119 - lr: 0.0090\n", - "Epoch 453/456\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0580 - accuracy: 0.9849 - val_loss: 0.2599 - val_accuracy: 0.9215 - lr: 0.0090\n", - "Epoch 454/456\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0491 - accuracy: 0.9873 - val_loss: 0.3314 - val_accuracy: 0.9199 - lr: 0.0090\n", - "Epoch 455/456\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0426 - accuracy: 0.9885 - val_loss: 0.4193 - val_accuracy: 0.9103 - lr: 0.0090\n", - "Epoch 456/456\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0298 - accuracy: 0.9927 - val_loss: 0.3315 - val_accuracy: 0.9183 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9215}, \u001b[0m\u001b[0;33mloss{0.2599}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9199\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3315\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.83GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m565.54 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m440.57 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m124.97 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [76] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m77\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 456)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 457/462\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1317 - accuracy: 0.9607 - val_loss: 0.1910 - val_accuracy: 0.9359 - lr: 0.0090\n", - "Epoch 458/462\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0786 - accuracy: 0.9778 - val_loss: 0.2189 - val_accuracy: 0.9231 - lr: 0.0090\n", - "Epoch 459/462\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0537 - accuracy: 0.9846 - val_loss: 0.2701 - val_accuracy: 0.9071 - lr: 0.0090\n", - "Epoch 460/462\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0304 - accuracy: 0.9919 - val_loss: 0.2740 - val_accuracy: 0.9279 - lr: 0.0090\n", - "Epoch 461/462\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0240 - accuracy: 0.9937 - val_loss: 0.3064 - val_accuracy: 0.9263 - lr: 0.0090\n", - "Epoch 462/462\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0166 - accuracy: 0.9951 - val_loss: 0.3085 - val_accuracy: 0.9311 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9359}, \u001b[0m\u001b[0;33mloss{0.1910}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9311\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3085\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m562.59 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.06 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m123.53 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [77] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m78\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 462)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 463/468\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1341 - accuracy: 0.9551 - val_loss: 0.2453 - val_accuracy: 0.8894 - lr: 0.0090\n", - "Epoch 464/468\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0742 - accuracy: 0.9746 - val_loss: 0.2062 - val_accuracy: 0.9199 - lr: 0.0090\n", - "Epoch 465/468\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0496 - accuracy: 0.9841 - val_loss: 0.2408 - val_accuracy: 0.9295 - lr: 0.0090\n", - "Epoch 466/468\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0233 - accuracy: 0.9927 - val_loss: 0.2731 - val_accuracy: 0.9311 - lr: 0.0090\n", - "Epoch 467/468\n", - "256/256 [==============================] - 73s 282ms/step - loss: 0.0219 - accuracy: 0.9949 - val_loss: 0.2976 - val_accuracy: 0.9295 - lr: 0.0090\n", - "Epoch 468/468\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0160 - accuracy: 0.9954 - val_loss: 0.3426 - val_accuracy: 0.9263 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9311}, \u001b[0m\u001b[0;33mloss{0.2062}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9263\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3425\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m566.24 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m443.29 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m122.95 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [78] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m79\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 468)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 469/474\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1446 - accuracy: 0.9548 - val_loss: 0.1887 - val_accuracy: 0.9311 - lr: 0.0090\n", - "Epoch 470/474\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0811 - accuracy: 0.9758 - val_loss: 0.1896 - val_accuracy: 0.9407 - lr: 0.0090\n", - "Epoch 471/474\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0573 - accuracy: 0.9822 - val_loss: 0.2068 - val_accuracy: 0.9359 - lr: 0.0090\n", - "Epoch 472/474\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0319 - accuracy: 0.9912 - val_loss: 0.2018 - val_accuracy: 0.9343 - lr: 0.0090\n", - "Epoch 473/474\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0297 - accuracy: 0.9915 - val_loss: 0.2370 - val_accuracy: 0.9423 - lr: 0.0090\n", - "Epoch 474/474\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0218 - accuracy: 0.9958 - val_loss: 0.2261 - val_accuracy: 0.9423 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1887}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9423\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2261\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m570.84 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.02 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m129.82 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [79] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m80\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 474)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 475/480\n", - "256/256 [==============================] - 79s 291ms/step - loss: 0.1372 - accuracy: 0.9600 - val_loss: 0.1696 - val_accuracy: 0.9407 - lr: 0.0090\n", - "Epoch 476/480\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0866 - accuracy: 0.9739 - val_loss: 0.1879 - val_accuracy: 0.9487 - lr: 0.0090\n", - "Epoch 477/480\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0508 - accuracy: 0.9839 - val_loss: 0.2168 - val_accuracy: 0.9439 - lr: 0.0090\n", - "Epoch 478/480\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0376 - accuracy: 0.9883 - val_loss: 0.2498 - val_accuracy: 0.9439 - lr: 0.0090\n", - "Epoch 479/480\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0249 - accuracy: 0.9941 - val_loss: 0.2011 - val_accuracy: 0.9343 - lr: 0.0090\n", - "Epoch 480/480\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0199 - accuracy: 0.9963 - val_loss: 0.2483 - val_accuracy: 0.9295 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9487}, \u001b[0m\u001b[0;33mloss{0.1696}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9295\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2483\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m568.81 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.35 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m127.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [80] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m81\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 480)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 481/486\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1453 - accuracy: 0.9512 - val_loss: 0.2448 - val_accuracy: 0.9231 - lr: 0.0090\n", - "Epoch 482/486\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0865 - accuracy: 0.9734 - val_loss: 0.5154 - val_accuracy: 0.9119 - lr: 0.0090\n", - "Epoch 483/486\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0515 - accuracy: 0.9846 - val_loss: 0.2043 - val_accuracy: 0.9375 - lr: 0.0090\n", - "Epoch 484/486\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0302 - accuracy: 0.9917 - val_loss: 0.1861 - val_accuracy: 0.9423 - lr: 0.0090\n", - "Epoch 485/486\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0303 - accuracy: 0.9910 - val_loss: 0.6762 - val_accuracy: 0.8990 - lr: 0.0090\n", - "Epoch 486/486\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0413 - accuracy: 0.9907 - val_loss: 0.3812 - val_accuracy: 0.9054 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9423}, \u001b[0m\u001b[0;33mloss{0.1861}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9038\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4067\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m571.00 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.56 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m129.43 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [81] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m82\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 486)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 487/492\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1381 - accuracy: 0.9534 - val_loss: 0.2291 - val_accuracy: 0.9183 - lr: 0.0090\n", - "Epoch 488/492\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0866 - accuracy: 0.9744 - val_loss: 0.2882 - val_accuracy: 0.8894 - lr: 0.0090\n", - "Epoch 489/492\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0542 - accuracy: 0.9829 - val_loss: 0.3209 - val_accuracy: 0.9006 - lr: 0.0090\n", - "Epoch 490/492\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0381 - accuracy: 0.9883 - val_loss: 0.6577 - val_accuracy: 0.8782 - lr: 0.0090\n", - "Epoch 491/492\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0260 - accuracy: 0.9924 - val_loss: 0.6497 - val_accuracy: 0.8926 - lr: 0.0090\n", - "Epoch 492/492\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0223 - accuracy: 0.9939 - val_loss: 1.7101 - val_accuracy: 0.7997 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9183}, \u001b[0m\u001b[0;33mloss{0.2291}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.7965\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m1.7177\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m568.85 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m440.24 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m128.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [82] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m83\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 492)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 493/498\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1347 - accuracy: 0.9539 - val_loss: 1.3282 - val_accuracy: 0.8141 - lr: 0.0090\n", - "Epoch 494/498\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0738 - accuracy: 0.9780 - val_loss: 1.7828 - val_accuracy: 0.8013 - lr: 0.0090\n", - "Epoch 495/498\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0451 - accuracy: 0.9863 - val_loss: 2.3645 - val_accuracy: 0.8109 - lr: 0.0090\n", - "Epoch 496/498\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0307 - accuracy: 0.9924 - val_loss: 0.8665 - val_accuracy: 0.8734 - lr: 0.0090\n", - "Epoch 497/498\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0228 - accuracy: 0.9949 - val_loss: 0.3687 - val_accuracy: 0.9215 - lr: 0.0090\n", - "Epoch 498/498\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0248 - accuracy: 0.9937 - val_loss: 0.3038 - val_accuracy: 0.9359 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9359}, \u001b[0m\u001b[0;33mloss{0.3038}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9359\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.3038\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m569.57 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m443.66 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m125.92 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [83] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m84\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 498)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33m└───Shuffling data...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;31m- Debug DP Sample dir: \u001b[0m\u001b[0;32mSamples/TSR_SUB_400_y2024_m03_d30-h09_m07_s13\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 499/504\n", - "256/256 [==============================] - 79s 288ms/step - loss: 0.1438 - accuracy: 0.9543 - val_loss: 0.2068 - val_accuracy: 0.9295 - lr: 0.0090\n", - "Epoch 500/504\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0814 - accuracy: 0.9758 - val_loss: 0.3795 - val_accuracy: 0.9054 - lr: 0.0090\n", - "Epoch 501/504\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0593 - accuracy: 0.9827 - val_loss: 0.6725 - val_accuracy: 0.8942 - lr: 0.0090\n", - "Epoch 502/504\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0305 - accuracy: 0.9927 - val_loss: 0.4958 - val_accuracy: 0.9151 - lr: 0.0090\n", - "Epoch 503/504\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0261 - accuracy: 0.9939 - val_loss: 0.3201 - val_accuracy: 0.9279 - lr: 0.0090\n", - "Epoch 504/504\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0251 - accuracy: 0.9941 - val_loss: 0.5018 - val_accuracy: 0.9151 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9295}, \u001b[0m\u001b[0;33mloss{0.2068}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9151\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.4984\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m581.46 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m439.90 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m141.55 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [84] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m85\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 504)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 505/510\n", - "256/256 [==============================] - 78s 288ms/step - loss: 0.1284 - accuracy: 0.9575 - val_loss: 0.9978 - val_accuracy: 0.8830 - lr: 0.0090\n", - "Epoch 506/510\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0736 - accuracy: 0.9758 - val_loss: 0.7478 - val_accuracy: 0.8910 - lr: 0.0090\n", - "Epoch 507/510\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0506 - accuracy: 0.9856 - val_loss: 0.5992 - val_accuracy: 0.9054 - lr: 0.0090\n", - "Epoch 508/510\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0228 - accuracy: 0.9939 - val_loss: 0.7798 - val_accuracy: 0.8782 - lr: 0.0090\n", - "Epoch 509/510\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0185 - accuracy: 0.9958 - val_loss: 0.7670 - val_accuracy: 0.8750 - lr: 0.0090\n", - "Epoch 510/510\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0102 - accuracy: 0.9976 - val_loss: 0.8993 - val_accuracy: 0.8670 - lr: 0.0090\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9054}, \u001b[0m\u001b[0;33mloss{0.5992}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8670\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.8991\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m568.18 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.62 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m125.56 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [85] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m86\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 510)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 511/516\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1551 - accuracy: 0.9495 - val_loss: 0.3373 - val_accuracy: 0.8862 - lr: 0.0090\n", - "Epoch 512/516\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0868 - accuracy: 0.9727 - val_loss: 0.8053 - val_accuracy: 0.8814 - lr: 0.0090\n", - "Epoch 513/516\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0534 - accuracy: 0.9841\n", - "Epoch 513: ReduceLROnPlateau reducing learning rate to 0.008806034876033663.\n", - "256/256 [==============================] - 73s 286ms/step - loss: 0.0534 - accuracy: 0.9841 - val_loss: 0.2876 - val_accuracy: 0.9167 - lr: 0.0090\n", - "Epoch 514/516\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0333 - accuracy: 0.9900 - val_loss: 0.6914 - val_accuracy: 0.8878 - lr: 0.0088\n", - "Epoch 515/516\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0242 - accuracy: 0.9932 - val_loss: 0.5452 - val_accuracy: 0.8942 - lr: 0.0088\n", - "Epoch 516/516\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0241 - accuracy: 0.9934 - val_loss: 0.7726 - val_accuracy: 0.8638 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9167}, \u001b[0m\u001b[0;33mloss{0.2876}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8638\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.7727\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m574.58 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.74 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m131.84 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [86] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m87\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 516)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 517/522\n", - "256/256 [==============================] - 79s 291ms/step - loss: 0.1453 - accuracy: 0.9541 - val_loss: 0.4466 - val_accuracy: 0.8974 - lr: 0.0088\n", - "Epoch 518/522\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0795 - accuracy: 0.9761 - val_loss: 0.5019 - val_accuracy: 0.8926 - lr: 0.0088\n", - "Epoch 519/522\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0578 - accuracy: 0.9841 - val_loss: 0.6239 - val_accuracy: 0.8622 - lr: 0.0088\n", - "Epoch 520/522\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0289 - accuracy: 0.9915 - val_loss: 0.4784 - val_accuracy: 0.9006 - lr: 0.0088\n", - "Epoch 521/522\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0198 - accuracy: 0.9927 - val_loss: 0.8253 - val_accuracy: 0.8846 - lr: 0.0088\n", - "Epoch 522/522\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0190 - accuracy: 0.9954 - val_loss: 1.0015 - val_accuracy: 0.8702 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9006}, \u001b[0m\u001b[0;33mloss{0.4466}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8702\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m1.0208\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m573.36 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.95 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m131.40 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [87] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m88\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 522)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 523/528\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1377 - accuracy: 0.9536 - val_loss: 0.3953 - val_accuracy: 0.9038 - lr: 0.0088\n", - "Epoch 524/528\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0610 - accuracy: 0.9807 - val_loss: 0.4758 - val_accuracy: 0.9038 - lr: 0.0088\n", - "Epoch 525/528\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0381 - accuracy: 0.9873 - val_loss: 0.5061 - val_accuracy: 0.9087 - lr: 0.0088\n", - "Epoch 526/528\n", - "256/256 [==============================] - 72s 280ms/step - loss: 0.0293 - accuracy: 0.9917 - val_loss: 0.8461 - val_accuracy: 0.8990 - lr: 0.0088\n", - "Epoch 527/528\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0155 - accuracy: 0.9958 - val_loss: 0.4623 - val_accuracy: 0.9183 - lr: 0.0088\n", - "Epoch 528/528\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0247 - accuracy: 0.9941 - val_loss: 0.2015 - val_accuracy: 0.9535 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9535}, \u001b[0m\u001b[0;33mloss{0.2015}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9535\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2014\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m572.14 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.48 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m129.67 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [88] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m89\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 528)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 529/534\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1402 - accuracy: 0.9553 - val_loss: 0.3024 - val_accuracy: 0.9359 - lr: 0.0088\n", - "Epoch 530/534\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0776 - accuracy: 0.9746 - val_loss: 0.7350 - val_accuracy: 0.9151 - lr: 0.0088\n", - "Epoch 531/534\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0541 - accuracy: 0.9839 - val_loss: 1.0363 - val_accuracy: 0.8894 - lr: 0.0088\n", - "Epoch 532/534\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0306 - accuracy: 0.9917 - val_loss: 2.3302 - val_accuracy: 0.8574 - lr: 0.0088\n", - "Epoch 533/534\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0208 - accuracy: 0.9946 - val_loss: 2.3128 - val_accuracy: 0.8462 - lr: 0.0088\n", - "Epoch 534/534\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0186 - accuracy: 0.9954 - val_loss: 1.8001 - val_accuracy: 0.8654 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9359}, \u001b[0m\u001b[0;33mloss{0.3024}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8654\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m1.7998\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m572.27 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m441.16 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m131.11 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [89] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m90\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 534)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 535/540\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1489 - accuracy: 0.9570 - val_loss: 0.4613 - val_accuracy: 0.8846 - lr: 0.0088\n", - "Epoch 536/540\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0844 - accuracy: 0.9763 - val_loss: 0.1915 - val_accuracy: 0.9375 - lr: 0.0088\n", - "Epoch 537/540\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0488 - accuracy: 0.9880 - val_loss: 0.2034 - val_accuracy: 0.9295 - lr: 0.0088\n", - "Epoch 538/540\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0293 - accuracy: 0.9932 - val_loss: 0.5313 - val_accuracy: 0.9054 - lr: 0.0088\n", - "Epoch 539/540\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0214 - accuracy: 0.9951 - val_loss: 0.4062 - val_accuracy: 0.9183 - lr: 0.0088\n", - "Epoch 540/540\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0269 - accuracy: 0.9934 - val_loss: 0.5009 - val_accuracy: 0.9183 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9375}, \u001b[0m\u001b[0;33mloss{0.1915}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1507}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9183\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.5005\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1507172436. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m575.44 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.71 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m132.73 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [90] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m91\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 540)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 541/546\n", - "256/256 [==============================] - 79s 291ms/step - loss: 0.1381 - accuracy: 0.9539 - val_loss: 0.1409 - val_accuracy: 0.9503 - lr: 0.0088\n", - "Epoch 542/546\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0859 - accuracy: 0.9731 - val_loss: 0.1610 - val_accuracy: 0.9455 - lr: 0.0088\n", - "Epoch 543/546\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0549 - accuracy: 0.9832 - val_loss: 0.1565 - val_accuracy: 0.9471 - lr: 0.0088\n", - "Epoch 544/546\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0320 - accuracy: 0.9912 - val_loss: 0.2411 - val_accuracy: 0.9199 - lr: 0.0088\n", - "Epoch 545/546\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0251 - accuracy: 0.9944 - val_loss: 0.2242 - val_accuracy: 0.9279 - lr: 0.0088\n", - "Epoch 546/546\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0158 - accuracy: 0.9961 - val_loss: 0.3142 - val_accuracy: 0.9247 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0;33mLoading the best weights...\u001b[0m\n", - "\u001b[0;33mLoading weights from file cache\\model_SUB_checkpoint-541-0.9503.h5...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9503\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.1409\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32mImproved model loss from 0.15071724 to 0.14092456. \u001b[0m\u001b[0;96mSaving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;36mSaving full model H5 format...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.17GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m580.86 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.09 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m138.76 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [91] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m92\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 546)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 547/552\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1398 - accuracy: 0.9526 - val_loss: 0.4507 - val_accuracy: 0.9071 - lr: 0.0088\n", - "Epoch 548/552\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0904 - accuracy: 0.9714 - val_loss: 0.4890 - val_accuracy: 0.9183 - lr: 0.0088\n", - "Epoch 549/552\n", - "256/256 [==============================] - 73s 286ms/step - loss: 0.0518 - accuracy: 0.9824 - val_loss: 0.4768 - val_accuracy: 0.9199 - lr: 0.0088\n", - "Epoch 550/552\n", - "256/256 [==============================] - 73s 282ms/step - loss: 0.0311 - accuracy: 0.9912 - val_loss: 1.0640 - val_accuracy: 0.8862 - lr: 0.0088\n", - "Epoch 551/552\n", - "256/256 [==============================] - 73s 282ms/step - loss: 0.0231 - accuracy: 0.9932 - val_loss: 0.8470 - val_accuracy: 0.8974 - lr: 0.0088\n", - "Epoch 552/552\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0222 - accuracy: 0.9951 - val_loss: 0.8176 - val_accuracy: 0.9135 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9199}, \u001b[0m\u001b[0;33mloss{0.4507}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1409}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9135\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.8165\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1409245580. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m578.78 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m443.96 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m134.82 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [92] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m93\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 552)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 553/558\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1370 - accuracy: 0.9578 - val_loss: 0.4271 - val_accuracy: 0.9199 - lr: 0.0088\n", - "Epoch 554/558\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0709 - accuracy: 0.9800 - val_loss: 0.2865 - val_accuracy: 0.9247 - lr: 0.0088\n", - "Epoch 555/558\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0485 - accuracy: 0.9873 - val_loss: 0.5766 - val_accuracy: 0.8990 - lr: 0.0088\n", - "Epoch 556/558\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0308 - accuracy: 0.9934 - val_loss: 0.3557 - val_accuracy: 0.9199 - lr: 0.0088\n", - "Epoch 557/558\n", - "256/256 [==============================] - 73s 286ms/step - loss: 0.0189 - accuracy: 0.9946 - val_loss: 0.3058 - val_accuracy: 0.9343 - lr: 0.0088\n", - "Epoch 558/558\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0183 - accuracy: 0.9968 - val_loss: 0.2928 - val_accuracy: 0.9327 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9343}, \u001b[0m\u001b[0;33mloss{0.2865}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1409}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9327\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2928\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1409245580. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m576.39 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m443.67 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m132.72 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [93] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m94\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 558)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 559/564\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1468 - accuracy: 0.9463 - val_loss: 0.3421 - val_accuracy: 0.8990 - lr: 0.0088\n", - "Epoch 560/564\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0839 - accuracy: 0.9719 - val_loss: 0.3228 - val_accuracy: 0.9247 - lr: 0.0088\n", - "Epoch 561/564\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0465 - accuracy: 0.9854 - val_loss: 0.2343 - val_accuracy: 0.9231 - lr: 0.0088\n", - "Epoch 562/564\n", - "256/256 [==============================] - 72s 279ms/step - loss: 0.0293 - accuracy: 0.9902 - val_loss: 0.4216 - val_accuracy: 0.9151 - lr: 0.0088\n", - "Epoch 563/564\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0215 - accuracy: 0.9939 - val_loss: 0.3030 - val_accuracy: 0.9263 - lr: 0.0088\n", - "Epoch 564/564\n", - "256/256 [==============================] - 73s 284ms/step - loss: 0.0165 - accuracy: 0.9956 - val_loss: 0.2694 - val_accuracy: 0.9327 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9327}, \u001b[0m\u001b[0;33mloss{0.2343}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1409}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.9327\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m0.2693\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1409245580. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m574.38 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.23 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m132.15 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [94] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m95\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 564)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 565/570\n", - "256/256 [==============================] - 79s 290ms/step - loss: 0.1450 - accuracy: 0.9534 - val_loss: 0.2132 - val_accuracy: 0.9311 - lr: 0.0088\n", - "Epoch 566/570\n", - "256/256 [==============================] - 73s 285ms/step - loss: 0.0841 - accuracy: 0.9724 - val_loss: 0.2178 - val_accuracy: 0.9343 - lr: 0.0088\n", - "Epoch 567/570\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0584 - accuracy: 0.9822 - val_loss: 0.3858 - val_accuracy: 0.9167 - lr: 0.0088\n", - "Epoch 568/570\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0284 - accuracy: 0.9924 - val_loss: 0.2594 - val_accuracy: 0.9343 - lr: 0.0088\n", - "Epoch 569/570\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0303 - accuracy: 0.9917 - val_loss: 0.7569 - val_accuracy: 0.8894 - lr: 0.0088\n", - "Epoch 570/570\n", - "256/256 [==============================] - 72s 282ms/step - loss: 0.0161 - accuracy: 0.9968 - val_loss: 1.0834 - val_accuracy: 0.8910 - lr: 0.0088\n", - "\u001b[0;32mSubset training done.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mNot loading weights\u001b[0m\u001b[0;32m[\u001b[0m\u001b[0;94mBSR:\u001b[0m\u001b[0;33macc{0.9343}, \u001b[0m\u001b[0;33mloss{0.2132}\u001b[0m\u001b[0;95m|\u001b[0m\u001b[0;94mBTR:\u001b[0m\u001b[0;32macc{0.9615}, loss{0.1409}]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test acc: \u001b[0m\u001b[0;32m0.8910\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mModel Test loss: \u001b[0m\u001b[0;32m1.0829\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel accuracy did not improve from 0.9615384340. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;91mModel loss did not improve from 0.1409245580. Not saving model.\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;32m(GPU-MEM)\u001b[0m\u001b[0;36m----[free: 5.18GB, used: 18.82GB, total, 24.00GB]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(FULL): \u001b[0m\u001b[0;32m576.87 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(SUBo): \u001b[0m\u001b[0;32m442.54 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTime taken for epoch(OTHERo): \u001b[0m\u001b[0;32m134.34 \u001b[0m\u001b[0;36msec\u001b[0m\n", - "\u001b[0;36m<---------------------------------------|Epoch [95] END|--------------------------------------->\u001b[0m\n", - "\u001b[0m\n", - "\u001b[0m\u001b[0mEpoch: \u001b[0m\u001b[0;36m96\u001b[0m\u001b[0m/\u001b[0m\u001b[0;32m489 (TSEC: 570)\u001b[0m\u001b[0;34m | \u001b[0m\u001b[0;32m[Stage 2]\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mTaking a subset of \u001b[0m\u001b[0;32m[|4096|AdvSubset:True]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;33mPreparing train data...\u001b[0m\n", - "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n", - "\u001b[0;33m- Normalizing Image Data...\u001b[0m\n", - "\u001b[0m\u001b[0m\u001b[0;33mSetting training subset epoch.c to \u001b[0m\u001b[0;32m[6]\u001b[0m\u001b[0;33m...\u001b[0m\n", - "\u001b[0;32mTraining on subset...\u001b[0m\n", - "Epoch 571/576\n", - "256/256 [==============================] - 79s 289ms/step - loss: 0.1359 - accuracy: 0.9592 - val_loss: 0.8639 - val_accuracy: 0.8333 - lr: 0.0088\n", - "Epoch 572/576\n", - "256/256 [==============================] - 73s 283ms/step - loss: 0.0774 - accuracy: 0.9768 - val_loss: 0.9179 - val_accuracy: 0.8526 - lr: 0.0088\n", - "Epoch 573/576\n", - "256/256 [==============================] - 72s 281ms/step - loss: 0.0396 - accuracy: 0.9885 - val_loss: 1.5042 - val_accuracy: 0.8381 - lr: 0.0088\n", - "Epoch 574/576\n", - "256/256 [==============================] - ETA: 0s - loss: 0.0300 - accuracy: 0.9919\n", - "KeyboardInterrupt. (Training stopped)\n", - "Training done.\n", - "\n" + "\u001b[0;33m- Augmenting Image Data...\u001b[0m\n" ] } ], @@ -10404,7 +7435,7 @@ "subset_size = 4096 # subset_size: Size of each training subset. Common values: 512, 1024, 2048, 3200, 4096, 5846, 8192.\n", "Conf_batch_size_REV2 = 16 # Conf_batch_size_REV2: Batch size.\n", "RES_Train = False # RES_Train: Resume training if True.\n", - "STR_M = 0.89 # STR_M: Starting momentum.\n", + "STR_M = 0.9 # STR_M: Starting momentum.\n", "STR_LR = 0.01 # STR_LR: Starting learning rate.\n", "MAX_LR = 0.01 # MAX_LR: Maximum learning rate.\n", "DEC_LR = 0.00005 # DEC_LR: Learning rate decay.\n",