diff --git "a/BertTOS_V2.ipynb" "b/BertTOS_V2.ipynb" new file mode 100644--- /dev/null +++ "b/BertTOS_V2.ipynb" @@ -0,0 +1,6777 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "NAbhfWJQ90eO", + "outputId": "c949cfb8-1f4e-4868-f707-7ad6e94a7c5a" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.41.2)\n", + "Collecting datasets\n", + " Downloading datasets-2.20.0-py3-none-any.whl (547 kB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m547.8/547.8 kB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.3.0+cu121)\n", + "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages 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+ "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch)\n", + " Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n", + "Collecting nvidia-nccl-cu12==2.20.5 (from torch)\n", + " Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n", + "Collecting nvidia-nvtx-cu12==12.1.105 (from torch)\n", + " Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n", + "Requirement already satisfied: triton==2.3.0 in /usr/local/lib/python3.10/dist-packages (from torch) (2.3.0)\n", + "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch)\n", + " Downloading nvidia_nvjitlink_cu12-12.5.40-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m43.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hRequirement already satisfied: python-dateutil>=2.8.2 in 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" Found existing installation: pyarrow 14.0.2\n", + " Uninstalling pyarrow-14.0.2:\n", + " Successfully uninstalled pyarrow-14.0.2\n", + "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", + "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 16.1.0 which is incompatible.\n", + "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\n", + "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 16.1.0 which is incompatible.\u001b[0m\u001b[31m\n", + "\u001b[0mSuccessfully installed datasets-2.20.0 dill-0.3.8 multiprocess-0.70.16 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.40 nvidia-nvtx-cu12-12.1.105 pyarrow-16.1.0 requests-2.32.3 xxhash-3.4.1\n", + "Requirement already satisfied: transformers[torch] in /usr/local/lib/python3.10/dist-packages 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in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (3.3.2)\n", + "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (3.7)\n", + "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (2.0.7)\n", + "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers[torch]) (2024.6.2)\n", + "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch->transformers[torch]) (2.1.5)\n", + "Requirement already satisfied: mpmath<1.4.0,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy->torch->transformers[torch]) (1.3.0)\n", + "Installing collected packages: transformers, accelerate\n", + " Attempting uninstall: transformers\n", + " Found existing installation: transformers 4.41.2\n", + " Uninstalling transformers-4.41.2:\n", + " Successfully uninstalled transformers-4.41.2\n", + "Successfully installed accelerate-0.31.0 transformers-4.42.3\n" + ] + } + ], + "source": [ + "# Install required packages\n", + "!pip install transformers datasets torch pandas scikit-learn\n", + "!pip install transformers[torch] accelerate -U" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "I962QgRn975V" + }, + "outputs": [], + "source": [ + "from datasets import load_dataset\n", + "from transformers import BertTokenizer, BertForSequenceClassification, Trainer, TrainingArguments\n", + "from sklearn.metrics import accuracy_score, precision_recall_fscore_support\n", + "import torch\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 365, + "referenced_widgets": [ + "3aa2d2c7cab240658ec6554214ee3ad7", + "e1792986236446e7a3d848613b1c0599", + 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+ "output_type": "stream", + "text": [ + "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n", + "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", + "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3aa2d2c7cab240658ec6554214ee3ad7", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Downloading readme: 0%| | 0.00/578 [00:00\n", + " \n", + " \n", + " [1011/1011 23:38, Epoch 3/3]\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + 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30.0695000.4254190.8891570.8852820.8837290.889157

" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "TrainOutput(global_step=1011, training_loss=0.3412421460969983, metrics={'train_runtime': 1424.0162, 'train_samples_per_second': 11.33, 'train_steps_per_second': 0.71, 'total_flos': 4245071881623552.0, 'train_loss': 0.3412421460969983, 'epoch': 3.0})" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Train the model\n", + "trainer.train()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 72 + }, + "id": "M7EVSUWG-1iM", + "outputId": "d0222af0-065b-48dc-b76e-312e1aec3710" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "

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\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Validation Accuracy: 0.8891566265060241\n", + "Test Accuracy: 0.8795761078998073\n" + ] + } + ], + "source": [ + "# Evaluate the model on validation data\n", + "validation_results = trainer.evaluate(eval_dataset=validation_data)\n", + "print(f\"Validation Accuracy: {validation_results['eval_accuracy']}\")\n", + "\n", + "# Evaluate the model on test data\n", + "test_results = trainer.evaluate(eval_dataset=test_data)\n", + "print(f\"Test Accuracy: {test_results['eval_accuracy']}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "mGFMA0OY-3ic", + "outputId": "a5f7b61f-acd6-4001-e6b7-99e028a32521" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('./tos-bert-classifier-v2/tokenizer_config.json',\n", + " './tos-bert-classifier-v2/special_tokens_map.json',\n", + " './tos-bert-classifier-v2/vocab.txt',\n", + " './tos-bert-classifier-v2/added_tokens.json')" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Save the model\n", + "model.save_pretrained('./tos-bert-classifier-v2')\n", + "tokenizer.save_pretrained('./tos-bert-classifier-v2')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "SMRagCKg-5p4" + }, + "outputs": [], + "source": [ + "# Function to predict unfairness level\n", + "def predict_unfairness(text, model, tokenizer):\n", + " inputs = tokenizer(text, return_tensors=\"pt\", truncation=True, padding=True, max_length=512)\n", + "\n", + " model.eval()\n", + " with torch.no_grad():\n", + " outputs = model(**inputs)\n", + "\n", + " probabilities = torch.softmax(outputs.logits, dim=-1).squeeze()\n", + " predicted_class = torch.argmax(probabilities).item()\n", + "\n", + " inverse_label_mapping = {0: 'clearly_fair', 1: 'potentially_unfair', 2: 'clearly_unfair'}\n", + " predicted_label = inverse_label_mapping[predicted_class]\n", + "\n", + " return predicted_label, probabilities.tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "XodtsObQ-7Su", + "outputId": "1dc3cbfa-bce3-46bb-decc-951124cf6abe" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Enter a clause to classify (or 'quit' to exit): 3. We reserve the right to suspend, terminate, or restrict your access to the platform at any time and for any reason, without prior notice or explanation. This includes but is not limited to violations of our community guidelines or terms of service, as determined solely by ConnectWorld.\n", + "\n", + "Predicted unfairness level: potentially_unfair\n", + "Probabilities:\n", + "clearly_fair: 0.0293\n", + "potentially_unfair: 0.5666\n", + "clearly_unfair: 0.4042\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): You have the right to use CommunityConnect for its intended purpose of connecting with others, sharing content responsibly, and engaging in constructive dialogue. You are responsible for the content you post and must respect the rights and privacy of others.\n", + "\n", + "Predicted unfairness level: clearly_fair\n", + "Probabilities:\n", + "clearly_fair: 0.9985\n", + "potentially_unfair: 0.0008\n", + "clearly_unfair: 0.0008\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): Our community guidelines are designed to maintain a safe and inclusive environment for all users. We will enforce these guidelines consistently and fairly, taking into account the context of each situation. Users will be provided with clear explanations if their content is removed or if their account is suspended or terminated.\n", + "\n", + "Predicted unfairness level: clearly_fair\n", + "Probabilities:\n", + "clearly_fair: 0.9648\n", + "potentially_unfair: 0.0337\n", + "clearly_unfair: 0.0016\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): 6. ConnectWorld disclaims all warranties, whether express, implied, statutory, or otherwise, including but not limited to warranties of merchantability, fitness for a particular purpose, and non-infringement. We shall not be liable for any direct, indirect, incidental, special, consequential, or exemplary damages, including but not limited to loss of profits, goodwill, use, data, or other intangible losses, resulting from your use of the platform.\n", + "\n", + "Predicted unfairness level: potentially_unfair\n", + "Probabilities:\n", + "clearly_fair: 0.0053\n", + "potentially_unfair: 0.9855\n", + "clearly_unfair: 0.0092\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): By using ConnectWorld, you grant us an irrevocable, perpetual, worldwide, royalty-free license to use, reproduce, modify, adapt, publish, translate, create derivative works from, distribute, and display any content posted on the platform, including personal information and user-generated content.\n", + "\n", + "Predicted unfairness level: clearly_fair\n", + "Probabilities:\n", + "clearly_fair: 0.9986\n", + "potentially_unfair: 0.0005\n", + "clearly_unfair: 0.0009\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): Any disputes arising out of or relating to these terms or your use of the platform shall be resolved through binding arbitration administered by the ConnectWorld Arbitration Association. You waive your right to participate in class-action lawsuits or to bring claims against ConnectWorld in a court of law.\n", + "\n", + "Predicted unfairness level: potentially_unfair\n", + "Probabilities:\n", + "clearly_fair: 0.0540\n", + "potentially_unfair: 0.9402\n", + "clearly_unfair: 0.0058\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): 1. We reserve the right to change, modify, or update these terms at any time without prior notice. Your continued use of the platform constitutes acceptance of any changes made.\n", + "\n", + "Predicted unfairness level: potentially_unfair\n", + "Probabilities:\n", + "clearly_fair: 0.0083\n", + "potentially_unfair: 0.9705\n", + "clearly_unfair: 0.0211\n", + "\n", + "Enter a clause to classify (or 'quit' to exit): quit\n" + ] + } + ], + "source": [ + "# Test the model\n", + "def test_model():\n", + " model_path = './tos-bert-classifier-v2'\n", + " model = BertForSequenceClassification.from_pretrained(model_path)\n", + " tokenizer = BertTokenizer.from_pretrained(model_path)\n", + "\n", + " while True:\n", + " text = input(\"Enter a clause to classify (or 'quit' to exit): \")\n", + " if text.lower() == 'quit':\n", + " break\n", + "\n", + " predicted_label, probabilities = predict_unfairness(text, model, tokenizer)\n", + "\n", + " print(f\"\\nPredicted unfairness level: {predicted_label}\")\n", + " print(\"Probabilities:\")\n", + " for label, prob in zip(['clearly_fair', 'potentially_unfair', 'clearly_unfair'], probabilities):\n", + " print(f\"{label}: {prob:.4f}\")\n", + " print()\n", + "\n", + "if __name__ == \"__main__\":\n", + " test_model()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "wAjq8_sxFBLl" + }, + "outputs": [], + "source": [ + "# Upload to Hugging Face Hub\n", + "from huggingface_hub import HfApi, Repository\n", + "import os" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "WIXT8zm-FFh3" + }, + "outputs": [], + "source": [ + "# Set your Hugging Face token and repo name\n", + "hf_token = \"Your_HF_Token\"\n", + "repo_name = \"TOSBertV2\"\n", + "\n", + "# Initialize Hugging Face API\n", + "api = HfApi()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "84Nj-0o7FS-k" + }, + "outputs": [], + "source": [ + "# Create a new repository\n", + "repo_url = api.create_repo(\n", + " repo_id=repo_name,\n", + " token=hf_token,\n", + " private=False,\n", + " exist_ok=True\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "KNzNmdk_FWJq", + "outputId": "c7bc386c-2cdb-4d7b-cffa-56b841773f9b" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'Repository' (from 'huggingface_hub.repository') is deprecated and will be removed from version '1.0'. Please prefer the http-based alternatives instead. Given its large adoption in legacy code, the complete removal is only planned on next major release.\n", + "For more details, please read https://huggingface.co/docs/huggingface_hub/concepts/git_vs_http.\n", + " warnings.warn(warning_message, FutureWarning)\n", + "Cloning https://huggingface.co/CodeHima/TOSBertV2 into local empty directory.\n", + "WARNING:huggingface_hub.repository:Cloning https://huggingface.co/CodeHima/TOSBertV2 into local empty directory.\n" + ] + } + ], + "source": [ + "# Clone the empty repository\n", + "repo = Repository(local_dir=repo_name, clone_from=repo_url, use_auth_token=hf_token)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vzyvOG1bFZMR" + }, + "outputs": [], + "source": [ + "# Load your trained model and tokenizer\n", + "model = BertForSequenceClassification.from_pretrained('./tos-bert-classifier-v2')\n", + "tokenizer = BertTokenizer.from_pretrained('./tos-bert-classifier-v2')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "XOBehbZjFbVR", + "outputId": "4b0e5498-8bc3-4bde-8b39-9c884718a65d" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('TOSBertV2/tokenizer_config.json',\n", + " 'TOSBertV2/special_tokens_map.json',\n", + " 'TOSBertV2/vocab.txt',\n", + " 'TOSBertV2/added_tokens.json')" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Save the model and tokenizer to the cloned repository\n", + "model.save_pretrained(repo_name)\n", + "tokenizer.save_pretrained(repo_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518, + "referenced_widgets": [ + "d7a7e0725c144163b590ab15b03e0877", + "8f5323dcf42f4dedaf08947192199555", + "c08434d3bd314462aa2b8b55e8f90295", + "326cfb3f845a470f993e492006340a2d", + "4ff98f0ec703459f9b70bcc5df7c4c35", + "b43f7fa2ed5247cb8219e3924d8be4dd", + "a2f39a5699e64843a51505ac370c60d4", + "b32d61182b074e2192b392246792db89", + "ebaa6619c8de45b4b71749ba52fc470b", + "455b37ea3e224e168d08cb486993593c", + "08043aa2a956483dbb5873a8e18b6c48" + ] + }, + "id": "rTphtAwNFfP_", + "outputId": "8ee85941-c3f9-40d8-c912-a10fd2e31bc8" + }, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d7a7e0725c144163b590ab15b03e0877", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Upload file model.safetensors: 0%| | 1.00/418M [00:00 main\n", + "\n", + "WARNING:huggingface_hub.repository:remote: \u001b[33m-------------------------------------------------------------------------\u001b[0m \n", + "remote: \u001b[33mYour push was accepted, but with warnings: \u001b[0m \n", + "remote: \u001b[33m- Warning: empty or missing yaml metadata in repo card\u001b[0m \n", + "remote: \u001b[33mhelp: https://huggingface.co/docs/hub/model-cards#model-card-metadata\u001b[0m \n", + "remote: \u001b[33m-------------------------------------------------------------------------\u001b[0m \n", + "remote: \u001b[32m-------------------------------------------------------------------------\u001b[0m \n", + "remote: \u001b[32mPlease find the documentation at:\u001b[0m \n", + "remote: \u001b[32mhttps://huggingface.co/docs/hub/model-cards#model-card-metadata\u001b[0m \n", + "remote: \u001b[32m\u001b[0m \n", + "remote: \u001b[32m-------------------------------------------------------------------------\u001b[0m \n", + "To https://huggingface.co/CodeHima/TOSBertV2\n", + " 5e43a01..d02db41 main -> main\n", + "\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model successfully pushed to https://huggingface.co/TOSBertV2\n" + ] + } + ], + "source": [ + "# Add a README file\n", + "with open(os.path.join(repo_name, \"README.md\"), \"w\") as f:\n", + " f.write(\"# TOSBertV2\\n\\nThis model is trained to classify clauses in Terms of Service (ToS) documents into three unfairness levels: clearly_fair, potentially_unfair, and clearly_unfair.\")\n", + "\n", + "# Push the files to the Hugging Face Hub\n", + "repo.git_add()\n", + "repo.git_commit(\"Initial commit\")\n", + "repo.git_push()\n", + "\n", + "print(f\"Model successfully pushed to https://huggingface.co/{repo_name}\")" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "gpuType": "T4", + "provenance": [] + }, + "kernelspec": { + "display_name": "Python 3", + "name": "python3" + }, + "language_info": { + "name": "python" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "014813c1b29a4d6098e01469d981147d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": 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