{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Training a causal language model from scratch (PyTorch)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Install the Transformers, Datasets, and Evaluate libraries to run this notebook." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#!pip install datasets evaluate transformers[sentencepiece]\n", "#!pip install accelerate\n", "# To run the training on TPU, you will need to uncomment the following line:\n", "# !pip install cloud-tpu-client==0.10 torch==1.9.0 https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.9-cp37-cp37m-linux_x86_64.whl\n", "#!apt install git-lfs" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting datasets\n", " Downloading datasets-2.19.0-py3-none-any.whl.metadata (19 kB)\n", "Collecting evaluate\n", " Downloading evaluate-0.4.2-py3-none-any.whl.metadata (9.3 kB)\n", "Collecting transformers\n", " Downloading transformers-4.40.1-py3-none-any.whl.metadata (137 kB)\n", " ---------------------------------------- 0.0/138.0 kB ? 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xxhash-3.4.1-cp311-cp311-win_amd64.whl (29 kB)\n", "Downloading aiosignal-1.3.1-py3-none-any.whl (7.6 kB)\n", "Downloading frozenlist-1.4.1-cp311-cp311-win_amd64.whl (50 kB)\n", " ---------------------------------------- 0.0/50.5 kB ? eta -:--:--\n", " ---------------------------------------- 50.5/50.5 kB 1.3 MB/s eta 0:00:00\n", "Downloading multidict-6.0.5-cp311-cp311-win_amd64.whl (28 kB)\n", "Downloading yarl-1.9.4-cp311-cp311-win_amd64.whl (76 kB)\n", " ---------------------------------------- 0.0/76.7 kB ? eta -:--:--\n", " -------------------------- ------------- 51.2/76.7 kB 1.3 MB/s eta 0:00:01\n", " ---------------------------------------- 76.7/76.7 kB 1.4 MB/s eta 0:00:00\n", "Installing collected packages: xxhash, safetensors, regex, pyarrow-hotfix, pyarrow, multidict, fsspec, frozenlist, dill, yarl, multiprocess, huggingface-hub, aiosignal, tokenizers, aiohttp, accelerate, transformers, datasets, evaluate\n", " Attempting uninstall: fsspec\n", " Found existing installation: fsspec 2023.4.0\n", " Uninstalling fsspec-2023.4.0:\n", " Successfully uninstalled fsspec-2023.4.0\n", " Attempting uninstall: dill\n", " Found existing installation: dill 0.3.7\n", " Uninstalling dill-0.3.7:\n", " Successfully uninstalled dill-0.3.7\n", "Successfully installed accelerate-0.29.3 aiohttp-3.9.5 aiosignal-1.3.1 datasets-2.19.0 dill-0.3.8 evaluate-0.4.2 frozenlist-1.4.1 fsspec-2024.3.1 huggingface-hub-0.22.2 multidict-6.0.5 multiprocess-0.70.16 pyarrow-16.0.0 pyarrow-hotfix-0.6 regex-2024.4.28 safetensors-0.4.3 tokenizers-0.19.1 transformers-4.40.1 xxhash-3.4.1 yarl-1.9.4\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "DEPRECATION: Loading egg at c:\\users\\rayja\\anaconda3\\envs\\python3117\\lib\\site-packages\\hls4ml-0.0.0-py3.11.egg is deprecated. pip 24.3 will enforce this behaviour change. A possible replacement is to use pip for package installation.. Discussion can be found at https://github.com/pypa/pip/issues/12330\n", "DEPRECATION: Loading egg at c:\\users\\rayja\\anaconda3\\envs\\python3117\\lib\\site-packages\\tensorflow_model_optimization-0.7.5-py3.11.egg is deprecated. pip 24.3 will enforce this behaviour change. A possible replacement is to use pip for package installation.. Discussion can be found at https://github.com/pypa/pip/issues/12330\n" ] } ], "source": [ "#!pip install datasets evaluate transformers accelerate" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You will need to setup git, adapt your email and name in the following cell." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "!git config --global user.email \"kugelblitz.ee05@gmail.com\"\n", "!git config --global user.name \"ChiRuiChen\"" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You will also need to be logged in to the Hugging Face Hub. Execute the following and enter your credentials." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "45c30c485fd04d77aca1b0f20c58dbf3", "version_major": 2, "version_minor": 0 }, "text/plain": [ "VBox(children=(HTML(value='
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StepTraining LossValidation Loss
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "TrainOutput(global_step=10836, training_loss=2.265032030727292, metrics={'train_runtime': 6527.3649, 'train_samples_per_second': 212.493, 'train_steps_per_second': 1.66, 'total_flos': 4.530258543063859e+16, 'train_loss': 2.265032030727292, 'epoch': 0.9999884645110683})" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trainer.train()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "4982ae767c704171b82c5dd69a6a0496", "version_major": 2, "version_minor": 0 }, "text/plain": [ "model.safetensors: 0%| | 0.00/327M [00:00