fine-tuning-phi-on-t4-2-gpu.ipynb

{"cells":[{"source":"<a href=\"https://www.kaggle.com/code/ashishkumarak/fine-tuning-phi-2-on-t4-gpu-hf-push-w-b-tracking?scriptVersionId=176861661\" target=\"_blank\"><img align=\"left\" alt=\"Kaggle\" title=\"Open in Kaggle\" src=\"https://kaggle.com/static/images/open-in-kaggle.svg\"></a>","metadata":{},"cell_type":"markdown"},{"cell_type":"markdown","id":"f6ca864e","metadata":{"papermill":{"duration":0.062558,"end_time":"2024-05-10T15:22:04.335958","exception":false,"start_time":"2024-05-10T15:22:04.2734","status":"completed"},"tags":[]},"source":["<p><img src=\"https://i.ytimg.com/vi/9fVb_pbVUC0/maxresdefault.jpg\" height=\"700\" width=\"700\" style=\"object-fit: cover;\"></p>\n","<p style=\"text-align:justify;\">\n","</p>  "]},{"cell_type":"markdown","id":"69849594","metadata":{"papermill":{"duration":0.05861,"end_time":"2024-05-10T15:22:04.455348","exception":false,"start_time":"2024-05-10T15:22:04.396738","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 120%;\n","    background-color: #F2FEFF;\n","    border-radius: 3px;\n","    font-color :  #581845  ;        \n","    border: 1px solid #FF5733 ;\">  \n","Installing and importing Required Libraries"]},{"cell_type":"code","execution_count":1,"id":"228fdb92","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:22:04.577908Z","iopub.status.busy":"2024-05-10T15:22:04.577576Z","iopub.status.idle":"2024-05-10T15:29:00.066709Z","shell.execute_reply":"2024-05-10T15:29:00.06543Z"},"id":"fNZZilUV_L4r","outputId":"31a2fa06-284f-411a-f439-0e8f949bfaf8","papermill":{"duration":415.615643,"end_time":"2024-05-10T15:29:00.13059","exception":false,"start_time":"2024-05-10T15:22:04.514947","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["49.4 s ± 163 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"]}],"source":["%%timeit\n","%%capture\n","%pip install -U -q bitsandbytes\n","%pip install -U -q transformers\n","%pip install -U -q peft\n","%pip install -U -q accelerate"]},{"cell_type":"code","execution_count":2,"id":"12c21511","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:29:00.257142Z","iopub.status.busy":"2024-05-10T15:29:00.255969Z","iopub.status.idle":"2024-05-10T15:32:40.549786Z","shell.execute_reply":"2024-05-10T15:32:40.548729Z"},"papermill":{"duration":220.416298,"end_time":"2024-05-10T15:32:40.611244","exception":false,"start_time":"2024-05-10T15:29:00.194946","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["27.2 s ± 60.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n"]}],"source":["%%timeit\n","%%capture\n","%pip uninstall datasets -y -q\n","%pip install -q datasets==2.16.0\n","%pip install -U -q trl "]},{"cell_type":"code","execution_count":3,"id":"11ff98da","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:32:40.779746Z","iopub.status.busy":"2024-05-10T15:32:40.778987Z","iopub.status.idle":"2024-05-10T15:33:03.185621Z","shell.execute_reply":"2024-05-10T15:33:03.184653Z"},"id":"VLzgZ14X_rMs","papermill":{"duration":22.515665,"end_time":"2024-05-10T15:33:03.188075","exception":false,"start_time":"2024-05-10T15:32:40.67241","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["2024-05-10 15:32:50.676877: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n","2024-05-10 15:32:50.676974: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n","2024-05-10 15:32:50.841123: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n"]}],"source":["from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig ,HfArgumentParser,TrainingArguments,pipeline\n","from peft import LoraConfig, PeftModel, prepare_model_for_kbit_training, get_peft_model\n","import os,torch, wandb\n","from datasets import load_dataset\n","from trl import SFTTrainer"]},{"attachments":{"4ddaad21-b659-4c15-8631-580294cb3e3a.png":{"image/png":"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"}},"cell_type":"markdown","id":"5f967dd4","metadata":{"papermill":{"duration":0.061362,"end_time":"2024-05-10T15:33:03.311306","exception":false,"start_time":"2024-05-10T15:33:03.249944","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 105%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">  \n","\n","Setting up the : \n","1. HuggingFace Token for uploading the fine tuned adapter\n","2. Weights and Biases Token for tracking the training metrics\n","    \n","To get the HuggingFace token :\n","1. Sign up and login to your HuggingFace account and go to https://huggingface.co/settings/tokens\n","\n","To get the Wandb token :\n","1. Sign up and login to your HuggingFace account and go to https://wandb.ai/authorize\n","\n","Add them in Kaggle : \n","1. Click on the Add-ons in Kaggle top menu : \n","    \n","![Screenshot 2024-03-20 at 10.36.34 PM.png](attachment:4ddaad21-b659-4c15-8631-580294cb3e3a.png)\n","\n","2. In the drop-down menu, choose `Secrets`\n","3. In the `Secrets` Tab, add both the tokens and attach them to the notebook \n","    \n","![Screenshot 2024-03-20 at 10.42.01 PM.png](attachment:8894edd9-b188-45c0-a140-93d535c3f8f3.png)\n","\n","The Settings are ready to be used!"]},{"cell_type":"markdown","id":"038caaac","metadata":{"papermill":{"duration":0.058768,"end_time":"2024-05-10T15:33:03.430036","exception":false,"start_time":"2024-05-10T15:33:03.371268","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 105%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\"> \n","    \n","Pass the names you assigned in the `Secrets` tab here in the `get_secret` below "]},{"cell_type":"code","execution_count":4,"id":"f7234fdc","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:03.552091Z","iopub.status.busy":"2024-05-10T15:33:03.55141Z","iopub.status.idle":"2024-05-10T15:33:03.716579Z","shell.execute_reply":"2024-05-10T15:33:03.715618Z"},"papermill":{"duration":0.228611,"end_time":"2024-05-10T15:33:03.718783","exception":false,"start_time":"2024-05-10T15:33:03.490172","status":"completed"},"tags":[]},"outputs":[],"source":["from kaggle_secrets import UserSecretsClient\n","user_secrets = UserSecretsClient()\n","secret_wandb = user_secrets.get_secret(\"WANDBTOKEN\")"]},{"cell_type":"code","execution_count":5,"id":"c7e53f71","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:03.845563Z","iopub.status.busy":"2024-05-10T15:33:03.844997Z","iopub.status.idle":"2024-05-10T15:33:05.46652Z","shell.execute_reply":"2024-05-10T15:33:05.465398Z"},"id":"f9oI6bPHzpDW","outputId":"07b4bb79-e35e-43a9-c0a9-fabbb4ac2721","papermill":{"duration":1.686866,"end_time":"2024-05-10T15:33:05.468801","exception":false,"start_time":"2024-05-10T15:33:03.781935","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["Token has not been saved to git credential helper. Pass `add_to_git_credential=True` if you want to set the git credential as well.\r\n","Token is valid (permission: write).\r\n","Your token has been saved to /root/.cache/huggingface/token\r\n","Login successful\r\n"]}],"source":["secret_hf = user_secrets.get_secret(\"HFTOKEN\")\n","# Logging in to huggingface using cli\n","!huggingface-cli login --token $secret_hf"]},{"cell_type":"markdown","id":"de8a8889","metadata":{"papermill":{"duration":0.060913,"end_time":"2024-05-10T15:33:05.590544","exception":false,"start_time":"2024-05-10T15:33:05.529631","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 105%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","    \n","In the Projects section of Weights and Biases, you'll see your project by the name as assigned to the `project` variable below :"]},{"cell_type":"code","execution_count":6,"id":"7764f78f","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:05.712883Z","iopub.status.busy":"2024-05-10T15:33:05.7125Z","iopub.status.idle":"2024-05-10T15:33:23.111196Z","shell.execute_reply":"2024-05-10T15:33:23.110174Z"},"id":"na9CAoHC5gM9","papermill":{"duration":17.463236,"end_time":"2024-05-10T15:33:23.113763","exception":false,"start_time":"2024-05-10T15:33:05.650527","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["\u001b[34m\u001b[1mwandb\u001b[0m: W&B API key is configured. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n","\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m If you're specifying your api key in code, ensure this code is not shared publicly.\n","\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[33mWARNING\u001b[0m Consider setting the WANDB_API_KEY environment variable, or running `wandb login` from the command line.\n","\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n","\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mashish28082002-ak\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n","\u001b[34m\u001b[1mwandb\u001b[0m: wandb version 0.17.0 is available!  To upgrade, please run:\n","\u001b[34m\u001b[1mwandb\u001b[0m:  $ pip install wandb --upgrade\n","\u001b[34m\u001b[1mwandb\u001b[0m: Tracking run with wandb version 0.16.6\n","\u001b[34m\u001b[1mwandb\u001b[0m: Run data is saved locally in \u001b[35m\u001b[1m/kaggle/working/wandb/run-20240510_153306-hg2i00yr\u001b[0m\n","\u001b[34m\u001b[1mwandb\u001b[0m: Run \u001b[1m`wandb offline`\u001b[0m to turn off syncing.\n","\u001b[34m\u001b[1mwandb\u001b[0m: Syncing run \u001b[33mjolly-water-13\u001b[0m\n","\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at \u001b[34m\u001b[4mhttps://wandb.ai/ashish28082002-ak/Fine%20tuning%20phi%202B%28FULL%20T4%2A2%29\u001b[0m\n","\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run at \u001b[34m\u001b[4mhttps://wandb.ai/ashish28082002-ak/Fine%20tuning%20phi%202B%28FULL%20T4%2A2%29/runs/hg2i00yr\u001b[0m\n"]}],"source":["# Monitering the LLM\n","wandb.login(key = secret_wandb)\n","run = wandb.init(\n","    project='Fine tuning phi 2B(FULL T4*2)', \n","    job_type=\"training\", \n","    anonymous=\"allow\"\n",")"]},{"cell_type":"markdown","id":"d6adb9d9","metadata":{"papermill":{"duration":0.065131,"end_time":"2024-05-10T15:33:23.244686","exception":false,"start_time":"2024-05-10T15:33:23.179555","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","    \n","Dataset Under Use :\n","    \n","- Here I'm using a dataset containing abstract and titles of different research papers, which had very high numbers of reads\n","- Intent is to use abstracts [of similar domain] during inference,  to produce 'catchy' titles that may/can maximise the reads of the paper with that abstract"]},{"cell_type":"code","execution_count":7,"id":"93bdd818","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:23.37248Z","iopub.status.busy":"2024-05-10T15:33:23.372144Z","iopub.status.idle":"2024-05-10T15:33:25.804932Z","shell.execute_reply":"2024-05-10T15:33:25.803897Z"},"papermill":{"duration":2.498646,"end_time":"2024-05-10T15:33:25.807503","exception":false,"start_time":"2024-05-10T15:33:23.308857","status":"completed"},"tags":[]},"outputs":[],"source":["from datasets import load_dataset\n","import pandas as pd    \n","train_dataset = pd.read_json(path_or_buf='/kaggle/input/astrollama-files/train_classic_factor.jsonl', lines=True)\n","eval_dataset =pd.read_json(path_or_buf='/kaggle/input/astrollama-files/eval_classic_factor.jsonl', lines=True)"]},{"cell_type":"code","execution_count":8,"id":"686c126b","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:25.936794Z","iopub.status.busy":"2024-05-10T15:33:25.936468Z","iopub.status.idle":"2024-05-10T15:33:26.082883Z","shell.execute_reply":"2024-05-10T15:33:26.082051Z"},"papermill":{"duration":0.212616,"end_time":"2024-05-10T15:33:26.084973","exception":false,"start_time":"2024-05-10T15:33:25.872357","status":"completed"},"tags":[]},"outputs":[],"source":["train_dataset['output'] = train_dataset['output'].str.replace(r\"\\['|'\\]\", \"\", regex=True)\n","eval_dataset['output'] = eval_dataset['output'].str.replace(r\"\\['|'\\]\", \"\", regex=True)"]},{"cell_type":"markdown","id":"823c8f03","metadata":{"papermill":{"duration":0.064083,"end_time":"2024-05-10T15:33:26.21401","exception":false,"start_time":"2024-05-10T15:33:26.149927","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Using the Prompt Template as mentioned here : https://huggingface.co/microsoft/phi-2#qa-format"]},{"cell_type":"code","execution_count":9,"id":"24b46743","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:26.346765Z","iopub.status.busy":"2024-05-10T15:33:26.3464Z","iopub.status.idle":"2024-05-10T15:33:26.396665Z","shell.execute_reply":"2024-05-10T15:33:26.395919Z"},"papermill":{"duration":0.117612,"end_time":"2024-05-10T15:33:26.398787","exception":false,"start_time":"2024-05-10T15:33:26.281175","status":"completed"},"tags":[]},"outputs":[],"source":["from datasets import Dataset\n","train_dataset = Dataset.from_pandas(train_dataset[1:200])\n","eval_dataset = Dataset.from_pandas(eval_dataset[1:200])\n","def formatting_func(example):\n","    text = f\"Instruct: {example['input']}\\nOutput: {example['output']}\"\n","    return text"]},{"cell_type":"markdown","id":"ab8a61d4","metadata":{"papermill":{"duration":0.063565,"end_time":"2024-05-10T15:33:26.528605","exception":false,"start_time":"2024-05-10T15:33:26.46504","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Loading the 8-bit quantised model. You can try without quantization as well"]},{"cell_type":"code","execution_count":10,"id":"54b10b0d","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:33:26.656172Z","iopub.status.busy":"2024-05-10T15:33:26.655331Z","iopub.status.idle":"2024-05-10T15:34:52.625581Z","shell.execute_reply":"2024-05-10T15:34:52.624403Z"},"id":"StJKGiDDHzdk","outputId":"871214ba-6c30-4ecf-ac68-550f296b7ef6","papermill":{"duration":86.036627,"end_time":"2024-05-10T15:34:52.627694","exception":false,"start_time":"2024-05-10T15:33:26.591067","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"5cf608902e7e40fa83e38b158a40cac2","version_major":2,"version_minor":0},"text/plain":["Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"]}],"source":["base_model = \"/kaggle/input/phi/transformers/2/1\"\n","\n","bnb_config = BitsAndBytesConfig(  \n","    load_in_8bit= True,\n","    bnb_4bit_quant_type= \"nf4\",\n","    bnb_4bit_compute_dtype= torch.bfloat16,\n","    bnb_4bit_use_double_quant= True,\n",")\n","model = AutoModelForCausalLM.from_pretrained(\n","        base_model,\n","        quantization_config=bnb_config,\n","        device_map=\"auto\",\n","        trust_remote_code=True,\n",")\n","model.config.use_cache = False #Uses less memory during training, need to be set to True during inference\n","model.config.pretraining_tp = 1\n","model.gradient_checkpointing_enable()\n","\n","# Loading tokenizer\n","tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)\n","# tokenizer.padding_side = 'right'\n","# tokenizer.pad_token = tokenizer.eos_token\n","# tokenizer.add_eos_token = True\n"]},{"cell_type":"code","execution_count":11,"id":"fe1eb863","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:52.755893Z","iopub.status.busy":"2024-05-10T15:34:52.755143Z","iopub.status.idle":"2024-05-10T15:34:53.040814Z","shell.execute_reply":"2024-05-10T15:34:53.039917Z"},"papermill":{"duration":0.351771,"end_time":"2024-05-10T15:34:53.042792","exception":false,"start_time":"2024-05-10T15:34:52.691021","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["50"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["import gc\n","gc.collect()"]},{"cell_type":"code","execution_count":12,"id":"aa04367a","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:53.181539Z","iopub.status.busy":"2024-05-10T15:34:53.18058Z","iopub.status.idle":"2024-05-10T15:34:53.185663Z","shell.execute_reply":"2024-05-10T15:34:53.184625Z"},"papermill":{"duration":0.079267,"end_time":"2024-05-10T15:34:53.187717","exception":false,"start_time":"2024-05-10T15:34:53.10845","status":"completed"},"tags":[]},"outputs":[],"source":["def generate_and_tokenize_prompt(prompt):\n","    return tokenizer(formatting_func(prompt))"]},{"cell_type":"markdown","id":"61ab1c0f","metadata":{"papermill":{"duration":0.072264,"end_time":"2024-05-10T15:34:53.331029","exception":false,"start_time":"2024-05-10T15:34:53.258765","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Mapping the dataset as per the prompt template and the respective tokenizer"]},{"cell_type":"code","execution_count":13,"id":"0a03873f","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:53.462599Z","iopub.status.busy":"2024-05-10T15:34:53.462225Z","iopub.status.idle":"2024-05-10T15:34:54.038348Z","shell.execute_reply":"2024-05-10T15:34:54.037434Z"},"papermill":{"duration":0.644263,"end_time":"2024-05-10T15:34:54.040812","exception":false,"start_time":"2024-05-10T15:34:53.396549","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"4d129b24849e4efb947d3e427040b96a","version_major":2,"version_minor":0},"text/plain":["Map:   0%|          | 0/199 [00:00<?, ? examples/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"b687e44de80d402a8e9ae613d0d291a0","version_major":2,"version_minor":0},"text/plain":["Map:   0%|          | 0/199 [00:00<?, ? examples/s]"]},"metadata":{},"output_type":"display_data"}],"source":["tokenized_train_dataset = train_dataset.map(generate_and_tokenize_prompt)\n","tokenized_val_dataset = eval_dataset.map(generate_and_tokenize_prompt)"]},{"cell_type":"code","execution_count":14,"id":"bbe97fb2","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:54.170685Z","iopub.status.busy":"2024-05-10T15:34:54.170354Z","iopub.status.idle":"2024-05-10T15:34:54.178907Z","shell.execute_reply":"2024-05-10T15:34:54.177932Z"},"papermill":{"duration":0.076646,"end_time":"2024-05-10T15:34:54.181177","exception":false,"start_time":"2024-05-10T15:34:54.104531","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["PhiForCausalLM(\n","  (model): PhiModel(\n","    (embed_tokens): Embedding(51200, 2560)\n","    (embed_dropout): Dropout(p=0.0, inplace=False)\n","    (layers): ModuleList(\n","      (0-31): 32 x PhiDecoderLayer(\n","        (self_attn): PhiAttention(\n","          (q_proj): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","          (k_proj): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","          (v_proj): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","          (dense): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","          (rotary_emb): PhiRotaryEmbedding()\n","        )\n","        (mlp): PhiMLP(\n","          (activation_fn): NewGELUActivation()\n","          (fc1): Linear8bitLt(in_features=2560, out_features=10240, bias=True)\n","          (fc2): Linear8bitLt(in_features=10240, out_features=2560, bias=True)\n","        )\n","        (input_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n","        (resid_dropout): Dropout(p=0.1, inplace=False)\n","      )\n","    )\n","    (final_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n","  )\n","  (lm_head): Linear(in_features=2560, out_features=51200, bias=True)\n",")\n"]}],"source":["print(model)"]},{"cell_type":"markdown","id":"d068ffd5","metadata":{"papermill":{"duration":0.064422,"end_time":"2024-05-10T15:34:54.310956","exception":false,"start_time":"2024-05-10T15:34:54.246534","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Preparing the model for QLoRA fine tuning"]},{"cell_type":"code","execution_count":15,"id":"280fff04","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:54.443007Z","iopub.status.busy":"2024-05-10T15:34:54.442416Z","iopub.status.idle":"2024-05-10T15:34:55.408087Z","shell.execute_reply":"2024-05-10T15:34:55.407152Z"},"id":"DZoClwHcPTqQ","papermill":{"duration":1.032451,"end_time":"2024-05-10T15:34:55.410261","exception":false,"start_time":"2024-05-10T15:34:54.37781","status":"completed"},"tags":[]},"outputs":[{"name":"stdout","output_type":"stream","text":["trainable params: 62,914,560 || all params: 2,842,598,400 || trainable%: 2.21327641639424\n"]}],"source":["\n","model = prepare_model_for_kbit_training(model)\n","peft_config = LoraConfig(\n","    r=128,\n","    lora_alpha=16,\n","    target_modules=[\"k_proj\", \"q_proj\", \"v_proj\"],\n","    lora_dropout=0.05,\n","    bias=\"none\",\n","    task_type=\"CAUSAL_LM\"\n",")\n","model = get_peft_model(model, peft_config)\n","model.print_trainable_parameters()"]},{"cell_type":"markdown","id":"6b8c22d0","metadata":{"papermill":{"duration":0.064319,"end_time":"2024-05-10T15:34:55.538953","exception":false,"start_time":"2024-05-10T15:34:55.474634","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Creating a path to save checkpoints(if any)"]},{"cell_type":"code","execution_count":16,"id":"ca6f2eff","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:55.668102Z","iopub.status.busy":"2024-05-10T15:34:55.667269Z","iopub.status.idle":"2024-05-10T15:34:55.672285Z","shell.execute_reply":"2024-05-10T15:34:55.671361Z"},"papermill":{"duration":0.072023,"end_time":"2024-05-10T15:34:55.674271","exception":false,"start_time":"2024-05-10T15:34:55.602248","status":"completed"},"tags":[]},"outputs":[],"source":["run_name = 'astrophi' \n","output_dir = \"./\" + run_name"]},{"cell_type":"markdown","id":"ded2cc83","metadata":{"papermill":{"duration":0.063068,"end_time":"2024-05-10T15:34:55.801408","exception":false,"start_time":"2024-05-10T15:34:55.73834","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","If you have more than one gpu, below commands ensure parallelization during training"]},{"cell_type":"code","execution_count":17,"id":"8093b2b4","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:55.930952Z","iopub.status.busy":"2024-05-10T15:34:55.930228Z","iopub.status.idle":"2024-05-10T15:34:55.934861Z","shell.execute_reply":"2024-05-10T15:34:55.934029Z"},"papermill":{"duration":0.071687,"end_time":"2024-05-10T15:34:55.936732","exception":false,"start_time":"2024-05-10T15:34:55.865045","status":"completed"},"tags":[]},"outputs":[],"source":["if torch.cuda.device_count() > 1: # If more than 1 GPU\n","    model.is_parallelizable = True\n","    model.model_parallel = True"]},{"cell_type":"markdown","id":"30836a60","metadata":{"papermill":{"duration":0.064393,"end_time":"2024-05-10T15:34:56.064869","exception":false,"start_time":"2024-05-10T15:34:56.000476","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 110%;\n","    background-color: #F2FEFF;\n","    border-radius: 5px;\n","    font-color :  #581845  ;                           \n","    border: 1px solid #FF5733 ;\">\n","\n","Removing any unwanted cache in VRAM and cleaning memory if any unassigned variables "]},{"cell_type":"code","execution_count":18,"id":"c9f9f154","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:56.195377Z","iopub.status.busy":"2024-05-10T15:34:56.195048Z","iopub.status.idle":"2024-05-10T15:34:56.499761Z","shell.execute_reply":"2024-05-10T15:34:56.498838Z"},"papermill":{"duration":0.37418,"end_time":"2024-05-10T15:34:56.501831","exception":false,"start_time":"2024-05-10T15:34:56.127651","status":"completed"},"tags":[]},"outputs":[{"data":{"text/plain":["0"]},"execution_count":18,"metadata":{},"output_type":"execute_result"}],"source":["torch.cuda.empty_cache()\n","\n","import gc\n","gc.collect()"]},{"cell_type":"code","execution_count":19,"id":"39be92c4","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:56.634018Z","iopub.status.busy":"2024-05-10T15:34:56.633681Z","iopub.status.idle":"2024-05-10T15:34:56.638051Z","shell.execute_reply":"2024-05-10T15:34:56.637146Z"},"papermill":{"duration":0.072981,"end_time":"2024-05-10T15:34:56.640091","exception":false,"start_time":"2024-05-10T15:34:56.56711","status":"completed"},"tags":[]},"outputs":[],"source":["tokenizer.pad_token = tokenizer.eos_token"]},{"cell_type":"code","execution_count":20,"id":"fd5f922c","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:34:56.769342Z","iopub.status.busy":"2024-05-10T15:34:56.768721Z","iopub.status.idle":"2024-05-10T15:39:48.908792Z","shell.execute_reply":"2024-05-10T15:39:48.907745Z"},"papermill":{"duration":292.206808,"end_time":"2024-05-10T15:39:48.911211","exception":false,"start_time":"2024-05-10T15:34:56.704403","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.10/site-packages/torch/utils/checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.\n","  warnings.warn(\n","/opt/conda/lib/python3.10/site-packages/bitsandbytes/autograd/_functions.py:316: UserWarning: MatMul8bitLt: inputs will be cast from torch.float32 to float16 during quantization\n","  warnings.warn(f\"MatMul8bitLt: inputs will be cast from {A.dtype} to float16 during quantization\")\n"]},{"data":{"text/html":["\n","    <div>\n","      \n","      <progress value='199' max='199' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [199/199 04:48, Epoch 1/1]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>1</td>\n","      <td>2.491900</td>\n","    </tr>\n","    <tr>\n","      <td>2</td>\n","      <td>3.473200</td>\n","    </tr>\n","    <tr>\n","      <td>3</td>\n","      <td>3.287700</td>\n","    </tr>\n","    <tr>\n","      <td>4</td>\n","      <td>2.651400</td>\n","    </tr>\n","    <tr>\n","      <td>5</td>\n","      <td>2.972800</td>\n","    </tr>\n","    <tr>\n","      <td>6</td>\n","      <td>2.925700</td>\n","    </tr>\n","    <tr>\n","      <td>7</td>\n","      <td>2.528400</td>\n","    </tr>\n","    <tr>\n","      <td>8</td>\n","      <td>3.292200</td>\n","    </tr>\n","    <tr>\n","      <td>9</td>\n","      <td>2.801600</td>\n","    </tr>\n","    <tr>\n","      <td>10</td>\n","      <td>3.019400</td>\n","    </tr>\n","    <tr>\n","      <td>11</td>\n","      <td>2.625700</td>\n","    </tr>\n","    <tr>\n","      <td>12</td>\n","      <td>2.231400</td>\n","    </tr>\n","    <tr>\n","      <td>13</td>\n","      <td>2.498600</td>\n","    </tr>\n","    <tr>\n","      <td>14</td>\n","      <td>2.751900</td>\n","    </tr>\n","    <tr>\n","      <td>15</td>\n","      <td>2.301800</td>\n","    </tr>\n","    <tr>\n","      <td>16</td>\n","      <td>2.452700</td>\n","    </tr>\n","    <tr>\n","      <td>17</td>\n","      <td>2.846500</td>\n","    </tr>\n","    <tr>\n","      <td>18</td>\n","      <td>2.184000</td>\n","    </tr>\n","    <tr>\n","      <td>19</td>\n","      <td>2.455800</td>\n","    </tr>\n","    <tr>\n","      <td>20</td>\n","      <td>2.238500</td>\n","    </tr>\n","    <tr>\n","      <td>21</td>\n","      <td>3.139500</td>\n","    </tr>\n","    <tr>\n","      <td>22</td>\n","      <td>3.228200</td>\n","    </tr>\n","    <tr>\n","      <td>23</td>\n","      <td>3.012000</td>\n","    </tr>\n","    <tr>\n","      <td>24</td>\n","      <td>2.777300</td>\n","    </tr>\n","    <tr>\n","      <td>25</td>\n","      <td>3.127200</td>\n","    </tr>\n","    <tr>\n","      <td>26</td>\n","      <td>2.933400</td>\n","    </tr>\n","    <tr>\n","      <td>27</td>\n","      <td>3.092900</td>\n","    </tr>\n","    <tr>\n","      <td>28</td>\n","      <td>2.817600</td>\n","    </tr>\n","    <tr>\n","      <td>29</td>\n","      <td>2.567400</td>\n","    </tr>\n","    <tr>\n","      <td>30</td>\n","      <td>2.850900</td>\n","    </tr>\n","    <tr>\n","      <td>31</td>\n","      <td>2.385700</td>\n","    </tr>\n","    <tr>\n","      <td>32</td>\n","      <td>2.852700</td>\n","    </tr>\n","    <tr>\n","      <td>33</td>\n","      <td>2.658200</td>\n","    </tr>\n","    <tr>\n","      <td>34</td>\n","      <td>2.611300</td>\n","    </tr>\n","    <tr>\n","      <td>35</td>\n","      <td>3.235000</td>\n","    </tr>\n","    <tr>\n","      <td>36</td>\n","      <td>2.771000</td>\n","    </tr>\n","    <tr>\n","      <td>37</td>\n","      <td>2.919800</td>\n","    </tr>\n","    <tr>\n","      <td>38</td>\n","      <td>3.101900</td>\n","    </tr>\n","    <tr>\n","      <td>39</td>\n","      <td>2.651400</td>\n","    </tr>\n","    <tr>\n","      <td>40</td>\n","      <td>2.701500</td>\n","    </tr>\n","    <tr>\n","      <td>41</td>\n","      <td>2.388000</td>\n","    </tr>\n","    <tr>\n","      <td>42</td>\n","      <td>2.094100</td>\n","    </tr>\n","    <tr>\n","      <td>43</td>\n","      <td>3.208600</td>\n","    </tr>\n","    <tr>\n","      <td>44</td>\n","      <td>2.483900</td>\n","    </tr>\n","    <tr>\n","      <td>45</td>\n","      <td>2.629300</td>\n","    </tr>\n","    <tr>\n","      <td>46</td>\n","      <td>2.369300</td>\n","    </tr>\n","    <tr>\n","      <td>47</td>\n","      <td>2.478100</td>\n","    </tr>\n","    <tr>\n","      <td>48</td>\n","      <td>2.203800</td>\n","    </tr>\n","    <tr>\n","      <td>49</td>\n","      <td>2.308900</td>\n","    </tr>\n","    <tr>\n","      <td>50</td>\n","      <td>2.450100</td>\n","    </tr>\n","    <tr>\n","      <td>51</td>\n","      <td>2.807500</td>\n","    </tr>\n","    <tr>\n","      <td>52</td>\n","      <td>3.071400</td>\n","    </tr>\n","    <tr>\n","      <td>53</td>\n","      <td>2.294100</td>\n","    </tr>\n","    <tr>\n","      <td>54</td>\n","      <td>2.555400</td>\n","    </tr>\n","    <tr>\n","      <td>55</td>\n","      <td>1.928700</td>\n","    </tr>\n","    <tr>\n","      <td>56</td>\n","      <td>2.434500</td>\n","    </tr>\n","    <tr>\n","      <td>57</td>\n","      <td>3.344200</td>\n","    </tr>\n","    <tr>\n","      <td>58</td>\n","      <td>3.068800</td>\n","    </tr>\n","    <tr>\n","      <td>59</td>\n","      <td>3.150000</td>\n","    </tr>\n","    <tr>\n","      <td>60</td>\n","      <td>2.470400</td>\n","    </tr>\n","    <tr>\n","      <td>61</td>\n","      <td>2.705800</td>\n","    </tr>\n","    <tr>\n","      <td>62</td>\n","      <td>2.521500</td>\n","    </tr>\n","    <tr>\n","      <td>63</td>\n","      <td>2.922200</td>\n","    </tr>\n","    <tr>\n","      <td>64</td>\n","      <td>2.694700</td>\n","    </tr>\n","    <tr>\n","      <td>65</td>\n","      <td>2.563700</td>\n","    </tr>\n","    <tr>\n","      <td>66</td>\n","      <td>2.344800</td>\n","    </tr>\n","    <tr>\n","      <td>67</td>\n","      <td>2.525200</td>\n","    </tr>\n","    <tr>\n","      <td>68</td>\n","      <td>3.124500</td>\n","    </tr>\n","    <tr>\n","      <td>69</td>\n","      <td>2.337600</td>\n","    </tr>\n","    <tr>\n","      <td>70</td>\n","      <td>2.562700</td>\n","    </tr>\n","    <tr>\n","      <td>71</td>\n","      <td>3.093900</td>\n","    </tr>\n","    <tr>\n","      <td>72</td>\n","      <td>2.933200</td>\n","    </tr>\n","    <tr>\n","      <td>73</td>\n","      <td>2.772900</td>\n","    </tr>\n","    <tr>\n","      <td>74</td>\n","      <td>2.664700</td>\n","    </tr>\n","    <tr>\n","      <td>75</td>\n","      <td>3.011700</td>\n","    </tr>\n","    <tr>\n","      <td>76</td>\n","      <td>2.664400</td>\n","    </tr>\n","    <tr>\n","      <td>77</td>\n","      <td>2.991600</td>\n","    </tr>\n","    <tr>\n","      <td>78</td>\n","      <td>3.207000</td>\n","    </tr>\n","    <tr>\n","      <td>79</td>\n","      <td>2.859800</td>\n","    </tr>\n","    <tr>\n","      <td>80</td>\n","      <td>3.001500</td>\n","    </tr>\n","    <tr>\n","      <td>81</td>\n","      <td>2.679600</td>\n","    </tr>\n","    <tr>\n","      <td>82</td>\n","      <td>2.858000</td>\n","    </tr>\n","    <tr>\n","      <td>83</td>\n","      <td>2.995000</td>\n","    </tr>\n","    <tr>\n","      <td>84</td>\n","      <td>2.495200</td>\n","    </tr>\n","    <tr>\n","      <td>85</td>\n","      <td>2.277400</td>\n","    </tr>\n","    <tr>\n","      <td>86</td>\n","      <td>2.544000</td>\n","    </tr>\n","    <tr>\n","      <td>87</td>\n","      <td>3.182400</td>\n","    </tr>\n","    <tr>\n","      <td>88</td>\n","      <td>2.338300</td>\n","    </tr>\n","    <tr>\n","      <td>89</td>\n","      <td>2.604300</td>\n","    </tr>\n","    <tr>\n","      <td>90</td>\n","      <td>2.275300</td>\n","    </tr>\n","    <tr>\n","      <td>91</td>\n","      <td>2.264100</td>\n","    </tr>\n","    <tr>\n","      <td>92</td>\n","      <td>2.570700</td>\n","    </tr>\n","    <tr>\n","      <td>93</td>\n","      <td>2.484000</td>\n","    </tr>\n","    <tr>\n","      <td>94</td>\n","      <td>2.873400</td>\n","    </tr>\n","    <tr>\n","      <td>95</td>\n","      <td>2.837700</td>\n","    </tr>\n","    <tr>\n","      <td>96</td>\n","      <td>2.638700</td>\n","    </tr>\n","    <tr>\n","      <td>97</td>\n","      <td>2.581200</td>\n","    </tr>\n","    <tr>\n","      <td>98</td>\n","      <td>2.293200</td>\n","    </tr>\n","    <tr>\n","      <td>99</td>\n","      <td>1.862500</td>\n","    </tr>\n","    <tr>\n","      <td>100</td>\n","      <td>3.068100</td>\n","    </tr>\n","    <tr>\n","      <td>101</td>\n","      <td>2.735700</td>\n","    </tr>\n","    <tr>\n","      <td>102</td>\n","      <td>2.443300</td>\n","    </tr>\n","    <tr>\n","      <td>103</td>\n","      <td>3.174300</td>\n","    </tr>\n","    <tr>\n","      <td>104</td>\n","      <td>1.950200</td>\n","    </tr>\n","    <tr>\n","      <td>105</td>\n","      <td>2.498000</td>\n","    </tr>\n","    <tr>\n","      <td>106</td>\n","      <td>2.324700</td>\n","    </tr>\n","    <tr>\n","      <td>107</td>\n","      <td>2.755300</td>\n","    </tr>\n","    <tr>\n","      <td>108</td>\n","      <td>2.447800</td>\n","    </tr>\n","    <tr>\n","      <td>109</td>\n","      <td>2.628700</td>\n","    </tr>\n","    <tr>\n","      <td>110</td>\n","      <td>3.297400</td>\n","    </tr>\n","    <tr>\n","      <td>111</td>\n","      <td>2.439000</td>\n","    </tr>\n","    <tr>\n","      <td>112</td>\n","      <td>2.423400</td>\n","    </tr>\n","    <tr>\n","      <td>113</td>\n","      <td>2.785900</td>\n","    </tr>\n","    <tr>\n","      <td>114</td>\n","      <td>2.450400</td>\n","    </tr>\n","    <tr>\n","      <td>115</td>\n","      <td>2.535100</td>\n","    </tr>\n","    <tr>\n","      <td>116</td>\n","      <td>2.283600</td>\n","    </tr>\n","    <tr>\n","      <td>117</td>\n","      <td>2.601300</td>\n","    </tr>\n","    <tr>\n","      <td>118</td>\n","      <td>3.051100</td>\n","    </tr>\n","    <tr>\n","      <td>119</td>\n","      <td>2.686300</td>\n","    </tr>\n","    <tr>\n","      <td>120</td>\n","      <td>1.744900</td>\n","    </tr>\n","    <tr>\n","      <td>121</td>\n","      <td>2.177700</td>\n","    </tr>\n","    <tr>\n","      <td>122</td>\n","      <td>2.452900</td>\n","    </tr>\n","    <tr>\n","      <td>123</td>\n","      <td>2.408600</td>\n","    </tr>\n","    <tr>\n","      <td>124</td>\n","      <td>2.866600</td>\n","    </tr>\n","    <tr>\n","      <td>125</td>\n","      <td>2.181600</td>\n","    </tr>\n","    <tr>\n","      <td>126</td>\n","      <td>2.525500</td>\n","    </tr>\n","    <tr>\n","      <td>127</td>\n","      <td>2.269100</td>\n","    </tr>\n","    <tr>\n","      <td>128</td>\n","      <td>2.670300</td>\n","    </tr>\n","    <tr>\n","      <td>129</td>\n","      <td>2.516300</td>\n","    </tr>\n","    <tr>\n","      <td>130</td>\n","      <td>2.132500</td>\n","    </tr>\n","    <tr>\n","      <td>131</td>\n","      <td>2.312600</td>\n","    </tr>\n","    <tr>\n","      <td>132</td>\n","      <td>3.773400</td>\n","    </tr>\n","    <tr>\n","      <td>133</td>\n","      <td>2.710800</td>\n","    </tr>\n","    <tr>\n","      <td>134</td>\n","      <td>2.416600</td>\n","    </tr>\n","    <tr>\n","      <td>135</td>\n","      <td>2.821700</td>\n","    </tr>\n","    <tr>\n","      <td>136</td>\n","      <td>2.318300</td>\n","    </tr>\n","    <tr>\n","      <td>137</td>\n","      <td>2.750900</td>\n","    </tr>\n","    <tr>\n","      <td>138</td>\n","      <td>2.409900</td>\n","    </tr>\n","    <tr>\n","      <td>139</td>\n","      <td>3.033800</td>\n","    </tr>\n","    <tr>\n","      <td>140</td>\n","      <td>2.341100</td>\n","    </tr>\n","    <tr>\n","      <td>141</td>\n","      <td>2.705400</td>\n","    </tr>\n","    <tr>\n","      <td>142</td>\n","      <td>2.318000</td>\n","    </tr>\n","    <tr>\n","      <td>143</td>\n","      <td>2.679600</td>\n","    </tr>\n","    <tr>\n","      <td>144</td>\n","      <td>2.230000</td>\n","    </tr>\n","    <tr>\n","      <td>145</td>\n","      <td>3.241100</td>\n","    </tr>\n","    <tr>\n","      <td>146</td>\n","      <td>2.851600</td>\n","    </tr>\n","    <tr>\n","      <td>147</td>\n","      <td>2.778000</td>\n","    </tr>\n","    <tr>\n","      <td>148</td>\n","      <td>2.642700</td>\n","    </tr>\n","    <tr>\n","      <td>149</td>\n","      <td>2.345500</td>\n","    </tr>\n","    <tr>\n","      <td>150</td>\n","      <td>2.923400</td>\n","    </tr>\n","    <tr>\n","      <td>151</td>\n","      <td>2.937400</td>\n","    </tr>\n","    <tr>\n","      <td>152</td>\n","      <td>2.186900</td>\n","    </tr>\n","    <tr>\n","      <td>153</td>\n","      <td>2.844100</td>\n","    </tr>\n","    <tr>\n","      <td>154</td>\n","      <td>2.995200</td>\n","    </tr>\n","    <tr>\n","      <td>155</td>\n","      <td>2.362600</td>\n","    </tr>\n","    <tr>\n","      <td>156</td>\n","      <td>1.894100</td>\n","    </tr>\n","    <tr>\n","      <td>157</td>\n","      <td>2.905300</td>\n","    </tr>\n","    <tr>\n","      <td>158</td>\n","      <td>3.056800</td>\n","    </tr>\n","    <tr>\n","      <td>159</td>\n","      <td>2.204800</td>\n","    </tr>\n","    <tr>\n","      <td>160</td>\n","      <td>2.101100</td>\n","    </tr>\n","    <tr>\n","      <td>161</td>\n","      <td>3.171800</td>\n","    </tr>\n","    <tr>\n","      <td>162</td>\n","      <td>2.456700</td>\n","    </tr>\n","    <tr>\n","      <td>163</td>\n","      <td>3.232600</td>\n","    </tr>\n","    <tr>\n","      <td>164</td>\n","      <td>2.523900</td>\n","    </tr>\n","    <tr>\n","      <td>165</td>\n","      <td>3.152800</td>\n","    </tr>\n","    <tr>\n","      <td>166</td>\n","      <td>2.256200</td>\n","    </tr>\n","    <tr>\n","      <td>167</td>\n","      <td>2.177200</td>\n","    </tr>\n","    <tr>\n","      <td>168</td>\n","      <td>2.467200</td>\n","    </tr>\n","    <tr>\n","      <td>169</td>\n","      <td>3.225100</td>\n","    </tr>\n","    <tr>\n","      <td>170</td>\n","      <td>2.491000</td>\n","    </tr>\n","    <tr>\n","      <td>171</td>\n","      <td>2.642900</td>\n","    </tr>\n","    <tr>\n","      <td>172</td>\n","      <td>2.674700</td>\n","    </tr>\n","    <tr>\n","      <td>173</td>\n","      <td>2.880300</td>\n","    </tr>\n","    <tr>\n","      <td>174</td>\n","      <td>2.309500</td>\n","    </tr>\n","    <tr>\n","      <td>175</td>\n","      <td>2.242700</td>\n","    </tr>\n","    <tr>\n","      <td>176</td>\n","      <td>2.410000</td>\n","    </tr>\n","    <tr>\n","      <td>177</td>\n","      <td>2.948700</td>\n","    </tr>\n","    <tr>\n","      <td>178</td>\n","      <td>3.383400</td>\n","    </tr>\n","    <tr>\n","      <td>179</td>\n","      <td>2.363800</td>\n","    </tr>\n","    <tr>\n","      <td>180</td>\n","      <td>2.286900</td>\n","    </tr>\n","    <tr>\n","      <td>181</td>\n","      <td>2.416400</td>\n","    </tr>\n","    <tr>\n","      <td>182</td>\n","      <td>2.507900</td>\n","    </tr>\n","    <tr>\n","      <td>183</td>\n","      <td>2.395200</td>\n","    </tr>\n","    <tr>\n","      <td>184</td>\n","      <td>2.313300</td>\n","    </tr>\n","    <tr>\n","      <td>185</td>\n","      <td>2.528200</td>\n","    </tr>\n","    <tr>\n","      <td>186</td>\n","      <td>2.025400</td>\n","    </tr>\n","    <tr>\n","      <td>187</td>\n","      <td>3.374900</td>\n","    </tr>\n","    <tr>\n","      <td>188</td>\n","      <td>2.620400</td>\n","    </tr>\n","    <tr>\n","      <td>189</td>\n","      <td>2.625400</td>\n","    </tr>\n","    <tr>\n","      <td>190</td>\n","      <td>2.678600</td>\n","    </tr>\n","    <tr>\n","      <td>191</td>\n","      <td>2.672800</td>\n","    </tr>\n","    <tr>\n","      <td>192</td>\n","      <td>2.112500</td>\n","    </tr>\n","    <tr>\n","      <td>193</td>\n","      <td>2.838300</td>\n","    </tr>\n","    <tr>\n","      <td>194</td>\n","      <td>2.273400</td>\n","    </tr>\n","    <tr>\n","      <td>195</td>\n","      <td>2.643200</td>\n","    </tr>\n","    <tr>\n","      <td>196</td>\n","      <td>2.436500</td>\n","    </tr>\n","    <tr>\n","      <td>197</td>\n","      <td>3.148200</td>\n","    </tr>\n","    <tr>\n","      <td>198</td>\n","      <td>3.391700</td>\n","    </tr>\n","    <tr>\n","      <td>199</td>\n","      <td>2.910200</td>\n","    </tr>\n","  </tbody>\n","</table><p>"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"}],"source":["import transformers\n","from datetime import datetime\n","\n","\n","\n","trainer = transformers.Trainer(\n","    model=model,\n","    train_dataset=tokenized_train_dataset,\n","    eval_dataset=tokenized_val_dataset,\n","    args=transformers.TrainingArguments(\n","        output_dir=output_dir,\n","        warmup_steps=1,\n","        per_device_train_batch_size=1,\n","        gradient_accumulation_steps=1,\n","        num_train_epochs=1,\n","        learning_rate=2.5e-4, # Want a small lr for finetuning\n","       fp16=True,\n","        optim=\"paged_adamw_8bit\",\n","        logging_steps=1,              # When to start reporting loss\n","        logging_dir=\"./logs\",        # Directory for storing logs\n","        eval_steps=10,               # Evaluate every step\n","        do_eval=True,                # Perform evaluation at the end of training\n","        report_to=\"wandb\",      \n","#         run_name=f\"{run_name}-{datetime.now().strftime('%Y-%m-%d-%H-%M')}\"          # Name of the W&B run (optional)\n","    ),\n","    data_collator=transformers.DataCollatorForLanguageModeling(tokenizer, mlm=False),\n",")\n","\n","model.config.use_cache = False  # silence the warnings. Please re-enable for inference!\n","\n","try : \n","    trainer.train()\n","except RuntimeError as e:\n","    print(e)\n","    if \"CUDA out of memory\" in str(e):\n","        print(\"CUDA out of memory error. Trying to handle.\")\n","        print(f'Original Error : {e}')"]},{"cell_type":"code","execution_count":21,"id":"d2ed8d85","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:39:49.046309Z","iopub.status.busy":"2024-05-10T15:39:49.045551Z","iopub.status.idle":"2024-05-10T15:39:55.501316Z","shell.execute_reply":"2024-05-10T15:39:55.500434Z"},"id":"nKgZBEGVS5a2","papermill":{"duration":6.524193,"end_time":"2024-05-10T15:39:55.50336","exception":false,"start_time":"2024-05-10T15:39:48.979167","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["/opt/conda/lib/python3.10/site-packages/peft/utils/save_and_load.py:154: UserWarning: Could not find a config file in /kaggle/input/phi/transformers/2/1 - will assume that the vocabulary was not modified.\n","  warnings.warn(\n","\u001b[34m\u001b[1mwandb\u001b[0m:                                                                                \n","\u001b[34m\u001b[1mwandb\u001b[0m: \n","\u001b[34m\u001b[1mwandb\u001b[0m: Run history:\n","\u001b[34m\u001b[1mwandb\u001b[0m:         train/epoch ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\n","\u001b[34m\u001b[1mwandb\u001b[0m:   train/global_step ▁▁▁▁▂▂▂▂▂▃▃▃▃▃▃▄▄▄▄▄▅▅▅▅▅▅▆▆▆▆▆▇▇▇▇▇▇███\n","\u001b[34m\u001b[1mwandb\u001b[0m:     train/grad_norm ▁▁▁▅▃▄▃█▄▅▅▃▂▄▅▃▃▃▃▂▃▂▄▃▄▃▇▃▄▄▄▂▃▃▃▄▄▃▃▅\n","\u001b[34m\u001b[1mwandb\u001b[0m: train/learning_rate ████▇▇▇▇▇▆▆▆▆▆▆▅▅▅▅▅▄▄▄▄▄▄▃▃▃▃▃▃▂▂▂▂▂▁▁▁\n","\u001b[34m\u001b[1mwandb\u001b[0m:          train/loss ▇▅▂▃▆▅▅▄▂▃▅▃▃▃▅▄▅▃▄▄▃▃▃▂▃▃█▃▃▅▂▁▃▂▄▃▃▁▂▇\n","\u001b[34m\u001b[1mwandb\u001b[0m: \n","\u001b[34m\u001b[1mwandb\u001b[0m: Run summary:\n","\u001b[34m\u001b[1mwandb\u001b[0m:               total_flos 968795844403200.0\n","\u001b[34m\u001b[1mwandb\u001b[0m:              train/epoch 1.0\n","\u001b[34m\u001b[1mwandb\u001b[0m:        train/global_step 199\n","\u001b[34m\u001b[1mwandb\u001b[0m:          train/grad_norm 0.25999\n","\u001b[34m\u001b[1mwandb\u001b[0m:      train/learning_rate 0.0\n","\u001b[34m\u001b[1mwandb\u001b[0m:               train/loss 2.9102\n","\u001b[34m\u001b[1mwandb\u001b[0m:               train_loss 2.65423\n","\u001b[34m\u001b[1mwandb\u001b[0m:            train_runtime 291.7627\n","\u001b[34m\u001b[1mwandb\u001b[0m: train_samples_per_second 0.682\n","\u001b[34m\u001b[1mwandb\u001b[0m:   train_steps_per_second 0.682\n","\u001b[34m\u001b[1mwandb\u001b[0m: \n","\u001b[34m\u001b[1mwandb\u001b[0m: 🚀 View run \u001b[33mjolly-water-13\u001b[0m at: \u001b[34m\u001b[4mhttps://wandb.ai/ashish28082002-ak/Fine%20tuning%20phi%202B%28FULL%20T4%2A2%29/runs/hg2i00yr\u001b[0m\n","\u001b[34m\u001b[1mwandb\u001b[0m: ⭐️ View project at: \u001b[34m\u001b[4mhttps://wandb.ai/ashish28082002-ak/Fine%20tuning%20phi%202B%28FULL%20T4%2A2%29\u001b[0m\n","\u001b[34m\u001b[1mwandb\u001b[0m: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)\n","\u001b[34m\u001b[1mwandb\u001b[0m: Find logs at: \u001b[35m\u001b[1m./wandb/run-20240510_153306-hg2i00yr/logs\u001b[0m\n"]},{"data":{"text/plain":["PeftModelForCausalLM(\n","  (base_model): LoraModel(\n","    (model): PhiForCausalLM(\n","      (model): PhiModel(\n","        (embed_tokens): Embedding(51200, 2560)\n","        (embed_dropout): Dropout(p=0.0, inplace=False)\n","        (layers): ModuleList(\n","          (0-31): 32 x PhiDecoderLayer(\n","            (self_attn): PhiAttention(\n","              (q_proj): lora.Linear8bitLt(\n","                (base_layer): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","                (lora_dropout): ModuleDict(\n","                  (default): Dropout(p=0.05, inplace=False)\n","                )\n","                (lora_A): ModuleDict(\n","                  (default): Linear(in_features=2560, out_features=128, bias=False)\n","                )\n","                (lora_B): ModuleDict(\n","                  (default): Linear(in_features=128, out_features=2560, bias=False)\n","                )\n","                (lora_embedding_A): ParameterDict()\n","                (lora_embedding_B): ParameterDict()\n","              )\n","              (k_proj): lora.Linear8bitLt(\n","                (base_layer): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","                (lora_dropout): ModuleDict(\n","                  (default): Dropout(p=0.05, inplace=False)\n","                )\n","                (lora_A): ModuleDict(\n","                  (default): Linear(in_features=2560, out_features=128, bias=False)\n","                )\n","                (lora_B): ModuleDict(\n","                  (default): Linear(in_features=128, out_features=2560, bias=False)\n","                )\n","                (lora_embedding_A): ParameterDict()\n","                (lora_embedding_B): ParameterDict()\n","              )\n","              (v_proj): lora.Linear8bitLt(\n","                (base_layer): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","                (lora_dropout): ModuleDict(\n","                  (default): Dropout(p=0.05, inplace=False)\n","                )\n","                (lora_A): ModuleDict(\n","                  (default): Linear(in_features=2560, out_features=128, bias=False)\n","                )\n","                (lora_B): ModuleDict(\n","                  (default): Linear(in_features=128, out_features=2560, bias=False)\n","                )\n","                (lora_embedding_A): ParameterDict()\n","                (lora_embedding_B): ParameterDict()\n","              )\n","              (dense): Linear8bitLt(in_features=2560, out_features=2560, bias=True)\n","              (rotary_emb): PhiRotaryEmbedding()\n","            )\n","            (mlp): PhiMLP(\n","              (activation_fn): NewGELUActivation()\n","              (fc1): Linear8bitLt(in_features=2560, out_features=10240, bias=True)\n","              (fc2): Linear8bitLt(in_features=10240, out_features=2560, bias=True)\n","            )\n","            (input_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n","            (resid_dropout): Dropout(p=0.1, inplace=False)\n","          )\n","        )\n","        (final_layernorm): LayerNorm((2560,), eps=1e-05, elementwise_affine=True)\n","      )\n","      (lm_head): Linear(in_features=2560, out_features=51200, bias=True)\n","    )\n","  )\n",")"]},"execution_count":21,"metadata":{},"output_type":"execute_result"}],"source":["# Save the fine-tuned model \n","trainer.model.save_pretrained('phi2')\n","#Close the wandb tracking for this process\n","wandb.finish()\n","# Set the cache to True for Inference\n","model.config.use_cache = True\n","model.eval()"]},{"cell_type":"markdown","id":"ae70d784","metadata":{"papermill":{"duration":0.067033,"end_time":"2024-05-10T15:39:55.640213","exception":false,"start_time":"2024-05-10T15:39:55.57318","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 120%;\n","    background-color: #F2FEFF;\n","    border-radius: 3px;\n","    font-color :  #581845  ;        \n","    border: 1px solid #FF5733 ;\">  \n","Push the adapter and tokenizer to HuggingFace"]},{"cell_type":"code","execution_count":22,"id":"cd6a7f78","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:39:55.776721Z","iopub.status.busy":"2024-05-10T15:39:55.776063Z","iopub.status.idle":"2024-05-10T15:40:04.688203Z","shell.execute_reply":"2024-05-10T15:40:04.687414Z"},"papermill":{"duration":8.982208,"end_time":"2024-05-10T15:40:04.690354","exception":false,"start_time":"2024-05-10T15:39:55.708146","status":"completed"},"tags":[]},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"e3a017b9f5ec4f7d81a5074fccc9591e","version_major":2,"version_minor":0},"text/plain":["README.md:   0%|          | 0.00/5.18k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bf288867652048b4886f2943efba77f7","version_major":2,"version_minor":0},"text/plain":["adapter_model.safetensors:   0%|          | 0.00/252M [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"}],"source":["try:\n","    trainer.model.push_to_hub('phi2', use_temp_dir=False)\n","    tokenizer.push_to_hub('phi2')\n","except error as e:\n","    print(\"An exception occurred\")"]},{"cell_type":"markdown","id":"f33a6b07","metadata":{"papermill":{"duration":0.067489,"end_time":"2024-05-10T15:40:04.828043","exception":false,"start_time":"2024-05-10T15:40:04.760554","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 120%;\n","    background-color: #F2FEFF;\n","    border-radius: 3px;\n","    font-color :  #581845  ;        \n","    border: 1px solid #FF5733 ;\">  \n","Inference using the adapter uploaded on HuggingFace "]},{"cell_type":"code","execution_count":23,"id":"7a3d00af","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:40:04.962086Z","iopub.status.busy":"2024-05-10T15:40:04.961427Z","iopub.status.idle":"2024-05-10T15:40:06.022116Z","shell.execute_reply":"2024-05-10T15:40:06.021129Z"},"papermill":{"duration":1.129746,"end_time":"2024-05-10T15:40:06.024415","exception":false,"start_time":"2024-05-10T15:40:04.894669","status":"completed"},"tags":[]},"outputs":[],"source":["from peft import PeftModel, PeftConfig\n","\n","model = PeftModel.from_pretrained(model, \"phi2\")\n"]},{"cell_type":"code","execution_count":24,"id":"06f24999","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:40:06.159136Z","iopub.status.busy":"2024-05-10T15:40:06.158821Z","iopub.status.idle":"2024-05-10T15:40:06.163856Z","shell.execute_reply":"2024-05-10T15:40:06.163037Z"},"papermill":{"duration":0.074609,"end_time":"2024-05-10T15:40:06.165727","exception":false,"start_time":"2024-05-10T15:40:06.091118","status":"completed"},"tags":[]},"outputs":[],"source":["eval_prompt  = 'Diabetes is now one of the major public health challenges, globally. Prolonged diabetes leads to various diabetic microvascular complications (DMCs) like retinopathy, nephropathy, and neuropathy. Multiple factors are likely to be involved in predisposing diabetic individuals to complications. Early detection or diagnosis is essential in developing strategies to reduce the risk factors and management costs of these diabetic complications. In this study, we employed Raman Spectroscopy (RS) to analyse the plasma samples of diabetes patients without and with DMCs along with the plasma samples of healthy subjects. Spectral comparisons revealed decrease in protein content in Diabetes group and further subsequent decrease in proteins in DMC groups when compared with control group, which corroborates with the fact that there exists increased secretion of proteins in urine and corresponding decreased protein content in their blood in case of diabetic individuals. Among all study groups, it was noted that 75% of control spectra show correct classification, while spectral misclassification is high amongst the subjects with Diabetes and DMCs. Interestingly, very few Diabetes and DMC plasma spectra are misclassified as control spectra. Findings demonstrate that 70% of the Diabetes subjects without complications can be correctly identified from diabetes with complications. Further, investigations could also attempt to explore the use of serum instead of plasma to reduce the spectral misclassifications as one of the abundant constituents namely clotting factors could be avoided. The outcome of RS study may be imminent for the early detection or diagnosis of DMCs.'"]},{"cell_type":"code","execution_count":25,"id":"6cbb6310","metadata":{"execution":{"iopub.execute_input":"2024-05-10T15:40:06.300315Z","iopub.status.busy":"2024-05-10T15:40:06.299755Z","iopub.status.idle":"2024-05-10T15:40:16.049397Z","shell.execute_reply":"2024-05-10T15:40:16.048182Z"},"id":"L7vHP41ITQPb","papermill":{"duration":9.819843,"end_time":"2024-05-10T15:40:16.051446","exception":false,"start_time":"2024-05-10T15:40:06.231603","status":"completed"},"tags":[]},"outputs":[{"name":"stderr","output_type":"stream","text":["The model 'PeftModelForCausalLM' is not supported for summarization. Supported models are ['BartForConditionalGeneration', 'BigBirdPegasusForConditionalGeneration', 'BlenderbotForConditionalGeneration', 'BlenderbotSmallForConditionalGeneration', 'EncoderDecoderModel', 'FSMTForConditionalGeneration', 'GPTSanJapaneseForConditionalGeneration', 'LEDForConditionalGeneration', 'LongT5ForConditionalGeneration', 'M2M100ForConditionalGeneration', 'MarianMTModel', 'MBartForConditionalGeneration', 'MT5ForConditionalGeneration', 'MvpForConditionalGeneration', 'NllbMoeForConditionalGeneration', 'PegasusForConditionalGeneration', 'PegasusXForConditionalGeneration', 'PLBartForConditionalGeneration', 'ProphetNetForConditionalGeneration', 'SeamlessM4TForTextToText', 'SeamlessM4Tv2ForTextToText', 'SwitchTransformersForConditionalGeneration', 'T5ForConditionalGeneration', 'UMT5ForConditionalGeneration', 'XLMProphetNetForConditionalGeneration'].\n"]},{"name":"stdout","output_type":"stream","text":["\n","The study used Raman Spectroscopy (RS) to analyze the plasma samples of diabetes patients with and without diabetic microvascular complications (DMCs) and healthy subjects. The results showed that the protein content in the plasma of diabetes patients\n"]}],"source":["pipe = pipeline(task=\"summarization\", model=model, tokenizer=tokenizer,  max_new_tokens=50)\n","result = pipe(f\"Instruct: {eval_prompt}\\n Output: \")\n","print(result[0]['summary_text'].split(\"\\n Output: \")[1])"]},{"cell_type":"markdown","id":"9d9b04d6","metadata":{"papermill":{"duration":0.066235,"end_time":"2024-05-10T15:40:16.185883","exception":false,"start_time":"2024-05-10T15:40:16.119648","status":"completed"},"tags":[]},"source":["<div class=\"anchor\" id=\"top\" style=\"\n","    margin-right: auto; \n","    margin-left: auto;\n","    padding: 10px;\n","   font-size : 120%;\n","    background-color: #F2FEFF;\n","    border-radius: 3px;\n","    font-color :  #581845  ;        \n","    border: 1px solid #FF5733 ;\">  \n","\n","The model can perform better on increasing the number of data points being used for fine tuning"]},{"cell_type":"code","execution_count":null,"id":"e112f80d","metadata":{"papermill":{"duration":0.067181,"end_time":"2024-05-10T15:40:16.319271","exception":false,"start_time":"2024-05-10T15:40:16.25209","status":"completed"},"tags":[]},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"eaf38a99","metadata":{"papermill":{"duration":0.065707,"end_time":"2024-05-10T15:40:16.45125","exception":false,"start_time":"2024-05-10T15:40:16.385543","status":"completed"},"tags":[]},"outputs":[],"source":[]}],"metadata":{"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"datasetId":4286707,"sourceId":7376909,"sourceType":"datasetVersion"},{"modelInstanceId":8658,"sourceId":10716,"sourceType":"modelInstanceVersion"}],"isGpuEnabled":true,"isInternetEnabled":true,"language":"python","sourceType":"notebook"},"kernelspec":{"display_name":"Python 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