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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "464f59f6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Collecting accelerate\n",
" Downloading accelerate-0.29.3-py3-none-any.whl (297 kB)\n",
"\u001b[K |████████████████████████████████| 297 kB 3.7 MB/s eta 0:00:01\n",
"\u001b[?25hRequirement already satisfied: pyyaml in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/pyyaml/5.4.1/lib/python3.9/site-packages (from accelerate) (5.4.1)\n",
"Requirement already satisfied: numpy>=1.17 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/MPI/gcc/11.2.0/openmpi/4.1.1/scipy-bundle/2021.10/lib/python3.9/site-packages (from accelerate) (1.21.3)\n",
"Requirement already satisfied: psutil in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from accelerate) (5.8.0)\n",
"Requirement already satisfied: huggingface-hub in ./.local/lib/python3.9/site-packages (from accelerate) (0.22.2)\n",
"Requirement already satisfied: torch>=1.10.0 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/MPI/gcc/11.2.0/openmpi/4.1.1/pytorch/1.13.1-CUDA-11.8.0/lib/python3.9/site-packages (from accelerate) (1.13.1)\n",
"Requirement already satisfied: safetensors>=0.3.1 in ./.local/lib/python3.9/site-packages (from accelerate) (0.4.3)\n",
"Requirement already satisfied: packaging>=20.0 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from accelerate) (20.9)\n",
"Requirement already satisfied: pyparsing>=2.0.2 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from packaging>=20.0->accelerate) (2.4.7)\n",
"Requirement already satisfied: typing_extensions in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/typing-extensions/4.3.0/lib/python3.9/site-packages (from torch>=1.10.0->accelerate) (4.3.0)\n",
"Requirement already satisfied: tqdm>=4.42.1 in ./.local/lib/python3.9/site-packages (from huggingface-hub->accelerate) (4.66.2)\n",
"Requirement already satisfied: filelock in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from huggingface-hub->accelerate) (3.0.12)\n",
"Requirement already satisfied: fsspec>=2023.5.0 in ./.local/lib/python3.9/site-packages (from huggingface-hub->accelerate) (2024.3.1)\n",
"Requirement already satisfied: requests in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from huggingface-hub->accelerate) (2.26.0)\n",
"Requirement already satisfied: idna<4,>=2.5 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (3.2)\n",
"Requirement already satisfied: charset-normalizer~=2.0.0 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (2.0.4)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (2021.5.30)\n",
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->huggingface-hub->accelerate) (1.26.6)\n",
"Installing collected packages: accelerate\n",
"\u001b[33m WARNING: The scripts accelerate, accelerate-config, accelerate-estimate-memory and accelerate-launch are installed in '/user/bhanucha/.local/bin' which is not on PATH.\n",
" Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.\u001b[0m\n",
"Successfully installed accelerate-0.29.3\n",
"\u001b[33mWARNING: You are using pip version 21.2.2; however, version 24.0 is available.\n",
"You should consider upgrading via the '/cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"pip install accelerate"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "008ef190",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Requirement already satisfied: transformers in ./.local/lib/python3.9/site-packages (4.40.0)\n",
"Requirement already satisfied: pyyaml>=5.1 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/pyyaml/5.4.1/lib/python3.9/site-packages (from transformers) (5.4.1)\n",
"Requirement already satisfied: regex!=2019.12.17 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from transformers) (2021.8.3)\n",
"Requirement already satisfied: requests in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from transformers) (2.26.0)\n",
"Requirement already satisfied: safetensors>=0.4.1 in ./.local/lib/python3.9/site-packages (from transformers) (0.4.3)\n",
"Requirement already satisfied: numpy>=1.17 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/MPI/gcc/11.2.0/openmpi/4.1.1/scipy-bundle/2021.10/lib/python3.9/site-packages (from transformers) (1.21.3)\n",
"Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in ./.local/lib/python3.9/site-packages (from transformers) (0.22.2)\n",
"Requirement already satisfied: tqdm>=4.27 in ./.local/lib/python3.9/site-packages (from transformers) (4.66.2)\n",
"Requirement already satisfied: tokenizers<0.20,>=0.19 in ./.local/lib/python3.9/site-packages (from transformers) (0.19.1)\n",
"Requirement already satisfied: filelock in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from transformers) (3.0.12)\n",
"Requirement already satisfied: packaging>=20.0 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from transformers) (20.9)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/typing-extensions/4.3.0/lib/python3.9/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.3.0)\n",
"Requirement already satisfied: fsspec>=2023.5.0 in ./.local/lib/python3.9/site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2024.3.1)\n",
"Requirement already satisfied: pyparsing>=2.0.2 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from packaging>=20.0->transformers) (2.4.7)\n",
"Requirement already satisfied: idna<4,>=2.5 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->transformers) (3.2)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->transformers) (2021.5.30)\n",
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->transformers) (1.26.6)\n",
"Requirement already satisfied: charset-normalizer~=2.0.0 in /cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/lib/python3.9/site-packages (from requests->transformers) (2.0.4)\n",
"\u001b[33mWARNING: You are using pip version 21.2.2; however, version 24.0 is available.\n",
"You should consider upgrading via the '/cvmfs/soft.ccr.buffalo.edu/versions/2023.01/easybuild/software/avx512/Compiler/gcccore/11.2.0/python/3.9.6/bin/python -m pip install --upgrade pip' command.\u001b[0m\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"pip install transformers"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "1be7c37e",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"2024-04-21 23:00:27.918259: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX512_VNNI AVX512_BF16 AVX_VNNI AMX_TILE AMX_INT8 AMX_BF16\n",
"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
"2024-04-21 23:00:33.682894: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n"
]
}
],
"source": [
"from transformers import BartTokenizer, BartForConditionalGeneration\n",
"import torch\n",
"from torch.utils.data import DataLoader, TensorDataset, random_split\n",
"from transformers import Trainer, TrainingArguments\n",
"from torch.utils.data import Dataset, DataLoader, random_split"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "976e0258",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Sun Apr 21 23:00:40 2024 \r\n",
"+-----------------------------------------------------------------------------+\r\n",
"| NVIDIA-SMI 525.89.02 Driver Version: 525.89.02 CUDA Version: 12.0 |\r\n",
"|-------------------------------+----------------------+----------------------+\r\n",
"| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |\r\n",
"| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |\r\n",
"| | | MIG M. |\r\n",
"|===============================+======================+======================|\r\n",
"| 0 NVIDIA H100 PCIe On | 00000000:B5:00.0 Off | 0 |\r\n",
"| N/A 39C P0 52W / 350W | 0MiB / 81559MiB | 0% Default |\r\n",
"| | | Disabled |\r\n",
"+-------------------------------+----------------------+----------------------+\r\n",
" \r\n",
"+-----------------------------------------------------------------------------+\r\n",
"| Processes: |\r\n",
"| GPU GI CI PID Type Process name GPU Memory |\r\n",
"| ID ID Usage |\r\n",
"|=============================================================================|\r\n",
"| No running processes found |\r\n",
"+-----------------------------------------------------------------------------+\r\n"
]
}
],
"source": [
"!nvidia-smi\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c1bd2d96",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import numpy as np\n",
"import gc"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "4ab4a4db",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['logs', 'logsh', 'results', 'resultsh', 'train_data_v2.npy']"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.listdir('/projects/academic/courses/cse676s24/bhanucha')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "c23d50ec",
"metadata": {},
"outputs": [],
"source": [
"train_data_path = '/projects/academic/courses/cse676s24/bhanucha/train_data_v2.npy'\n",
"train_data = np.load(train_data_path, mmap_mode='r')"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "2baa2aeb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Data type: <class 'numpy.memmap'>\n",
"Data shape: (1405634, 512)\n",
"Contents of the array: [[ 0 48539 35 22 134 740 4 10523 6515 6219 4696 1297\n",
" 22 134 73 176 740 4 27805 1070 5803 1297 22 134\n",
" 73 176 26141 4 21857 1297 22 134 73 176 740 4\n",
" 3187 15092 36 26512 1253 45894 22 176 255 39596 4 9050\n",
" 50 31417 27323 1297 22 246 112 73 176 740 4 10970\n",
" 1836 30274 7666 31729 113 13497 35 440 12 387 5113 14208\n",
" 41200 38490 35 22 1121 10 2016 132 12 45252 8929 12560\n",
" 6 3344 6219 4696 6 15092 6 27805 1070 5803 8 9050\n",
" 50 31417 27323 45863 22 5320 853 81 4761 2859 454 12652\n",
" 26054 70 81 299 45863 22 387 14189 8 14351 195 728\n",
" 55 4 4624 160 2859 45863 22 5320 853 11 21857 8\n",
" 25629 131 3344 157 45863 22 36949 132 37031 6 1874 8\n",
" 3989 88 389 28255 15 19957 2225 45863 22 7939 1413 454\n",
" 933 6 59 389 728 72 2 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1 1 1 1 1\n",
" 1 1 1 1 1 1 1 1]]\n"
]
}
],
"source": [
"print(\"Data type:\", type(train_data))\n",
"print(\"Data shape:\", train_data.shape)\n",
"if isinstance(train_data, np.ndarray) and train_data.dtype.names is not None:\n",
" print(\"Data field names:\", train_data.dtype.names)\n",
"else:\n",
" print(\"Contents of the array:\", train_data[:1])"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "000b31cb",
"metadata": {},
"outputs": [],
"source": [
"class TokenizedDataset(Dataset):\n",
" def __init__(self, numpy_data):\n",
" self.input_ids = torch.tensor(numpy_data, dtype=torch.long)\n",
" self.attention_mask = (self.input_ids != 1).long()\n",
"\n",
" # Assuming labels are the same as input_ids for an autoencoding task\n",
" # If different, you would need to adjust this\n",
" self.labels = torch.tensor(numpy_data, dtype=torch.long)\n",
"\n",
" def __len__(self):\n",
" return len(self.input_ids)\n",
" \n",
" def __getitem__(self, idx):\n",
" return {\n",
" 'input_ids': self.input_ids[idx],\n",
" 'attention_mask': self.attention_mask[idx],\n",
" 'labels': self.labels[idx] # This line is critical\n",
" }\n",
"\n",
" \n",
"dataset = TokenizedDataset(train_data)\n",
"\n",
"# Split the dataset into training and validation sets\n",
"train_size = int(0.9 * len(dataset))\n",
"val_size = len(dataset) - train_size\n",
"train_dataset, val_dataset = random_split(dataset, [train_size, val_size])\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "28a80ef5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# train_data = None\n",
"dataset = None\n",
"gc.collect() "
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "127736dc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Using GPU: NVIDIA H100 PCIe\n"
]
}
],
"source": [
"# Check GPU availability\n",
"if torch.cuda.is_available():\n",
" device = torch.device(\"cuda\")\n",
" print(\"Using GPU:\", torch.cuda.get_device_name(0))\n",
"else:\n",
" device = torch.device(\"cpu\")\n",
" print(\"GPU not available, using CPU instead.\")"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b794f649",
"metadata": {},
"outputs": [],
"source": [
"model_checkpoint = \"facebook/bart-base\"\n",
"model = BartForConditionalGeneration.from_pretrained(model_checkpoint)\n"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "b426b6b2",
"metadata": {},
"outputs": [],
"source": [
"\n",
"training_args = TrainingArguments(\n",
" output_dir='/projects/academic/courses/cse676s24/bhanucha/results',\n",
" num_train_epochs=1,\n",
"# per_device_train_batch_size=16,\n",
" per_device_eval_batch_size=8,\n",
" warmup_steps=500,\n",
" weight_decay=0.01,\n",
" logging_dir='/projects/academic/courses/cse676s24/bhanucha/logs',\n",
" logging_steps=10000,\n",
" evaluation_strategy=\"epoch\",\n",
" save_strategy=\"steps\", \n",
" save_steps=100000, \n",
" save_total_limit=2, \n",
" per_device_train_batch_size=4, \n",
" gradient_accumulation_steps=2, \n",
" fp16=True,\n",
")\n",
"\n",
"trainer = Trainer(\n",
" model=model,\n",
" args=training_args,\n",
" train_dataset=train_dataset,\n",
" eval_dataset=val_dataset\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "22d08365",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
" <div>\n",
" \n",
" <progress value='158134' max='158134' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" [158134/158134 4:40:32, Epoch 1/1]\n",
" </div>\n",
" <table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: left;\">\n",
" <th>Epoch</th>\n",
" <th>Training Loss</th>\n",
" <th>Validation Loss</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>1</td>\n",
" <td>0.000000</td>\n",
" <td>0.000001</td>\n",
" </tr>\n",
" </tbody>\n",
"</table><p>"
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"text": [
"Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
"Non-default generation parameters: {'early_stopping': True, 'num_beams': 4, 'no_repeat_ngram_size': 3, 'forced_bos_token_id': 0, 'forced_eos_token_id': 2}\n"
]
},
{
"data": {
"text/plain": [
"TrainOutput(global_step=158134, training_loss=0.005809515866546127, metrics={'train_runtime': 16834.5077, 'train_samples_per_second': 75.147, 'train_steps_per_second': 9.393, 'total_flos': 3.856796506128384e+17, 'train_loss': 0.005809515866546127, 'epoch': 1.0})"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trainer.train()\n"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "e5012aa5",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
"Non-default generation parameters: {'early_stopping': True, 'num_beams': 4, 'no_repeat_ngram_size': 3, 'forced_bos_token_id': 0, 'forced_eos_token_id': 2}\n"
]
}
],
"source": [
"model.save_pretrained('/projects/academic/courses/cse676s24/bhanucha/saved_model')\n"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "a1dcb25d",
"metadata": {},
"outputs": [
{
"data": {
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" <progress value='158134' max='158134' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
" [158134/158134 4:38:50, Epoch 1/1]\n",
" </div>\n",
" <table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: left;\">\n",
" <th>Epoch</th>\n",
" <th>Training Loss</th>\n",
" <th>Validation Loss</th>\n",
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"text": [
"Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
"Non-default generation parameters: {'early_stopping': True, 'num_beams': 4, 'no_repeat_ngram_size': 3, 'forced_bos_token_id': 0, 'forced_eos_token_id': 2}\n"
]
},
{
"data": {
"text/plain": [
"TrainOutput(global_step=158134, training_loss=0.00010101553865172577, metrics={'train_runtime': 16730.7583, 'train_samples_per_second': 75.613, 'train_steps_per_second': 9.452, 'total_flos': 3.86710105227264e+17, 'train_loss': 0.00010101553865172577, 'epoch': 1.0})"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"trainer.train()\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "576bdaa6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'eval_loss': 1.690886506366951e-06}\n"
]
}
],
"source": [
"evaluation_results = trainer.evaluate()\n",
"print(evaluation_results)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "c82c318f",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
"Non-default generation parameters: {'early_stopping': True, 'num_beams': 4, 'no_repeat_ngram_size': 3, 'forced_bos_token_id': 0, 'forced_eos_token_id': 2}\n"
]
}
],
"source": [
"model.save_pretrained('/projects/academic/courses/cse676s24/bhanucha/saved_model2')"
]
}
],
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"display_name": "Python 3 (ipykernel)",
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|