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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"id": "e63f42f0-e971-4017-8550-21fdcfc2de11",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (1.7.0)\n",
"Requirement already satisfied: numpy>=1.22.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.24.1)\n",
"Requirement already satisfied: scipy>=1.8.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.15.3)\n",
"Requirement already satisfied: joblib>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (1.5.1)\n",
"Requirement already satisfied: threadpoolctl>=3.1.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn) (3.6.0)\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (2.3.0)\n",
"Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from pandas) (1.24.1)\n",
"Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas) (2.8.2)\n",
"Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas) (2025.2)\n",
"Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas) (2025.2)\n",
"Requirement already satisfied: six>=1.5 in /usr/lib/python3/dist-packages (from python-dateutil>=2.8.2->pandas) (1.16.0)\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (4.67.1)\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (0.2.0)\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Looking in indexes: https://download.pytorch.org/whl/cu118\n",
"Collecting torch==2.0.1\n",
" Using cached https://download.pytorch.org/whl/cu118/torch-2.0.1%2Bcu118-cp310-cp310-linux_x86_64.whl (2267.3 MB)\n",
"Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (0.16.0+cu118)\n",
"Requirement already satisfied: torchaudio in /usr/local/lib/python3.10/dist-packages (2.1.0+cu118)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.9.0)\n",
"Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (4.4.0)\n",
"Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (1.12)\n",
"Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.0)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (3.1.2)\n",
"Requirement already satisfied: triton==2.0.0 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1) (2.0.0)\n",
"Requirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch==2.0.1) (4.0.3)\n",
"Requirement already satisfied: lit in /usr/local/lib/python3.10/dist-packages (from triton==2.0.0->torch==2.0.1) (18.1.8)\n",
"Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from torchvision) (1.24.1)\n",
"Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from torchvision) (2.31.0)\n",
"INFO: pip is looking at multiple versions of torchvision to determine which version is compatible with other requirements. This could take a while.\n",
"Collecting torchvision\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.22.1%2Bcu118-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (6.1 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.22.0%2Bcu118-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (6.1 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.21.0%2Bcu118-cp310-cp310-linux_x86_64.whl.metadata (6.1 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.20.1%2Bcu118-cp310-cp310-linux_x86_64.whl (6.5 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.20.0%2Bcu118-cp310-cp310-linux_x86_64.whl (6.5 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.19.1%2Bcu118-cp310-cp310-linux_x86_64.whl (6.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.19.0%2Bcu118-cp310-cp310-linux_x86_64.whl (6.3 MB)\n",
"INFO: pip is still looking at multiple versions of torchvision to determine which version is compatible with other requirements. This could take a while.\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.18.1%2Bcu118-cp310-cp310-linux_x86_64.whl (6.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.18.0%2Bcu118-cp310-cp310-linux_x86_64.whl (6.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.17.2%2Bcu118-cp310-cp310-linux_x86_64.whl (6.2 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.17.1%2Bcu118-cp310-cp310-linux_x86_64.whl (6.2 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.17.0%2Bcu118-cp310-cp310-linux_x86_64.whl (6.2 MB)\n",
"INFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.16.2%2Bcu118-cp310-cp310-linux_x86_64.whl (6.1 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.16.1%2Bcu118-cp310-cp310-linux_x86_64.whl (6.1 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchvision-0.15.2%2Bcu118-cp310-cp310-linux_x86_64.whl (6.1 MB)\n",
"Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.10/dist-packages (from torchvision) (9.3.0)\n",
"INFO: pip is looking at multiple versions of torchaudio to determine which version is compatible with other requirements. This could take a while.\n",
"Collecting torchaudio\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.7.1%2Bcu118-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (6.6 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.7.0%2Bcu118-cp310-cp310-manylinux_2_28_x86_64.whl.metadata (6.6 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.6.0%2Bcu118-cp310-cp310-linux_x86_64.whl.metadata (6.6 kB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.5.1%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.5.0%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.4.1%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.4.0%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
"INFO: pip is still looking at multiple versions of torchaudio to determine which version is compatible with other requirements. This could take a while.\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.3.1%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.3.0%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.2.2%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.2.1%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.2.0%2Bcu118-cp310-cp310-linux_x86_64.whl (3.3 MB)\n",
"INFO: This is taking longer than usual. You might need to provide the dependency resolver with stricter constraints to reduce runtime. See https://pip.pypa.io/warnings/backtracking for guidance. If you want to abort this run, press Ctrl + C.\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.1.2%2Bcu118-cp310-cp310-linux_x86_64.whl (3.2 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.1.1%2Bcu118-cp310-cp310-linux_x86_64.whl (3.2 MB)\n",
" Using cached https://download.pytorch.org/whl/cu118/torchaudio-2.0.2%2Bcu118-cp310-cp310-linux_x86_64.whl (4.4 MB)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.0.1) (2.1.2)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (2.1.1)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (3.4)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (1.26.13)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->torchvision) (2022.12.7)\n",
"Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.0.1) (1.3.0)\n",
"Installing collected packages: torch, torchvision, torchaudio\n",
" Attempting uninstall: torch\n",
" Found existing installation: torch 2.1.0+cu118\n",
" Uninstalling torch-2.1.0+cu118:\n",
" Successfully uninstalled torch-2.1.0+cu118\n",
" Rolling back uninstall of torch\n",
" Moving to /usr/local/bin/convert-caffe2-to-onnx\n",
" from /tmp/pip-uninstall-ior9qvf0/convert-caffe2-to-onnx\n",
" Moving to /usr/local/bin/convert-onnx-to-caffe2\n",
" from /tmp/pip-uninstall-ior9qvf0/convert-onnx-to-caffe2\n",
" Moving to /usr/local/bin/torchrun\n",
" from /tmp/pip-uninstall-ior9qvf0/torchrun\n",
" Moving to /usr/local/lib/python3.10/dist-packages/functorch/\n",
" from /usr/local/lib/python3.10/dist-packages/~unctorch\n",
" Moving to /usr/local/lib/python3.10/dist-packages/nvfuser/\n",
" from /usr/local/lib/python3.10/dist-packages/~vfuser\n",
" Moving to /usr/local/lib/python3.10/dist-packages/torch-2.1.0+cu118.dist-info/\n",
" from /usr/local/lib/python3.10/dist-packages/~orch-2.1.0+cu118.dist-info\n",
" Moving to /usr/local/lib/python3.10/dist-packages/torch/\n",
" from /usr/local/lib/python3.10/dist-packages/~orch\n",
" Moving to /usr/local/lib/python3.10/dist-packages/torchgen/\n",
" from /usr/local/lib/python3.10/dist-packages/~orchgen\n",
"\u001b[31mERROR: Could not install packages due to an OSError: [Errno 28] No space left on device\n",
"\u001b[0m\u001b[31m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n",
"Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.52.4)\n",
"Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.9.0)\n",
"Requirement already satisfied: huggingface-hub<1.0,>=0.30.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.33.0)\n",
"Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.24.1)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n",
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
"Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2024.11.6)\n",
"Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
"Requirement already satisfied: tokenizers<0.22,>=0.21 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.21.1)\n",
"Requirement already satisfied: safetensors>=0.4.3 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.5.3)\n",
"Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.67.1)\n",
"Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (2025.5.1)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (4.4.0)\n",
"Requirement already satisfied: hf-xet<2.0.0,>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.30.0->transformers) (1.1.3)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.1.1)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.4)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (1.26.13)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2022.12.7)\n",
"\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n",
"\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.3.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.1.1\u001b[0m\n",
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpython -m pip install --upgrade pip\u001b[0m\n"
]
}
],
"source": [
"!pip install scikit-learn\n",
"!pip install pandas\n",
"!pip install tqdm\n",
"!pip install sentencepiece\n",
"!pip install torch==2.0.1 torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118\n",
"!pip install --upgrade transformers"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "7db96f7b-0cd3-4710-93d8-391622e60c25",
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"import json\n",
"import pandas as pd\n",
"import torch\n",
"from torch.optim import AdamW\n",
"from torch.utils.data import Dataset, DataLoader\n",
"from torch.nn import CrossEntropyLoss\n",
"from transformers import CamembertTokenizer, CamembertForSequenceClassification, get_scheduler\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.metrics import classification_report\n",
"from tqdm import tqdm"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "338ab5df-bc6d-4f2c-8a5e-bc9bb7b658f1",
"metadata": {},
"outputs": [],
"source": [
"# ─────────────────────────────────────────────\n",
"# ⚙️ Config\n",
"# ─────────────────────────────────────────────\n",
"DEBUG = False\n",
"BATCH_SIZE = 64\n",
"EPOCHS = 3 if not DEBUG else 1\n",
"MAX_LEN = 128\n",
"LR = 2e-5\n",
"PATIENCE = 2 # pour l'early stopping"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "3ccb7df2-77fc-461b-ac1e-05f1d8be7ed0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Classes : df_labels\n",
"0 189412\n",
"1 33982\n",
"Name: count, dtype: int64\n"
]
}
],
"source": [
"# ─────────────────────────────────────────────\n",
"# 📁 Chargement du dataset\n",
"# ─────────────────────────────────────────────\n",
"df = pd.read_csv(\"jigsaw-toxic-comment-train-google-fr-cleaned.csv\")\n",
"df['comment_text'] = df['comment_text'].astype(str)\n",
"df.rename(columns={'comment_text': 'texts'}, inplace=True)\n",
"\n",
"label_cols = ['toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']\n",
"other_cols_to_drop = ['Unnamed: 0.1', 'Unnamed: 0', 'id']\n",
"cols_to_drop = label_cols + other_cols_to_drop\n",
"\n",
"df['df_labels'] = df[label_cols].max(axis=1)\n",
"df = df.drop(columns=cols_to_drop)\n",
"\n",
"# Debug : sous-échantillonnage équilibré\n",
"if DEBUG:\n",
" df_0 = df[df[\"df_labels\"] == 0].sample(500, random_state=42)\n",
" df_1 = df[df[\"df_labels\"] == 1].sample(500, random_state=42)\n",
" df = pd.concat([df_0, df_1]).sample(frac=1, random_state=42)\n",
"\n",
"print(\"Classes :\", df['df_labels'].value_counts())"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "83c4cf79-57d9-4d54-8d8f-0e4249b8a930",
"metadata": {},
"outputs": [],
"source": [
"# ─────────────────────────────────────────────\n",
"# 🔢 Dataset\n",
"# ─────────────────────────────────────────────\n",
"tokenizer = CamembertTokenizer.from_pretrained(\"camembert-base\")\n",
"\n",
"class CommentDataset(Dataset):\n",
" def __init__(self, texts, labels, tokenizer, max_len):\n",
" self.texts = texts\n",
" self.labels = labels\n",
" self.tokenizer = tokenizer\n",
" self.max_len = max_len\n",
"\n",
" def __len__(self):\n",
" return len(self.texts)\n",
"\n",
" def __getitem__(self, idx):\n",
" encoding = self.tokenizer(\n",
" self.texts[idx],\n",
" padding=\"max_length\",\n",
" truncation=True,\n",
" max_length=self.max_len,\n",
" return_tensors=\"pt\"\n",
" )\n",
" item = {key: val.squeeze() for key, val in encoding.items()}\n",
" item['labels'] = torch.tensor(self.labels[idx], dtype=torch.long)\n",
" return item\n",
"\n",
"# Split\n",
"X_train, X_val, y_train, y_val = train_test_split(df[\"texts\"].tolist(), df[\"df_labels\"].tolist(), test_size=0.2, random_state=42)\n",
"\n",
"train_dataset = CommentDataset(X_train, y_train, tokenizer, MAX_LEN)\n",
"val_dataset = CommentDataset(X_val, y_val, tokenizer, MAX_LEN)\n",
"\n",
"train_loader = DataLoader(train_dataset, batch_size=BATCH_SIZE, shuffle=True)\n",
"val_loader = DataLoader(val_dataset, batch_size=BATCH_SIZE)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "05e8419e-dbeb-42ba-b9ed-ea099e96244a",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"Some weights of CamembertForSequenceClassification were not initialized from the model checkpoint at camembert-base and are newly initialized: ['classifier.dense.bias', 'classifier.dense.weight', 'classifier.out_proj.bias', 'classifier.out_proj.weight']\n",
"You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Poids pour la loss : tensor([1.0000, 5.5739])\n"
]
}
],
"source": [
"# ─────────────────────────────────────────────\n",
"# 🧠 Modèle + loss pondérée\n",
"# ─────────────────────────────────────────────\n",
"device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
"model = CamembertForSequenceClassification.from_pretrained(\"camembert-base\", num_labels=2).to(device)\n",
"\n",
"# pondération dynamique\n",
"if DEBUG:\n",
" class_weights = torch.tensor([1.0, 1.0], dtype=torch.float)\n",
"else:\n",
" count_0 = df[df[\"df_labels\"] == 0].shape[0]\n",
" count_1 = df[df[\"df_labels\"] == 1].shape[0]\n",
" class_weights = torch.tensor([1.0, count_0 / count_1], dtype=torch.float)\n",
"\n",
"print(f\"Poids pour la loss : {class_weights}\")\n",
"loss_fn = CrossEntropyLoss(weight=class_weights.to(device))\n",
"\n",
"# Optimiseur et scheduler\n",
"optimizer = AdamW(model.parameters(), lr=LR)\n",
"scheduler = get_scheduler(\"linear\", optimizer=optimizer, num_warmup_steps=0, num_training_steps=len(train_loader) * EPOCHS)\n"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "0b181b9f-64a6-479f-b585-221a598cded6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"🌟 Epoch 1/3\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Entraînement: 100%|██████████| 2793/2793 [18:23<00:00, 2.53it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"📉 Loss moyenne : 0.5043\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Évaluation: 100%|██████████| 699/699 [01:50<00:00, 6.32it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"🎯 F1-score (weighted) : 0.8826\n",
"✅ Nouveau meilleur modèle — sauvegarde manuelle...\n",
"\n",
"🌟 Epoch 2/3\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Entraînement: 100%|██████████| 2793/2793 [18:26<00:00, 2.53it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"📉 Loss moyenne : 0.4711\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Évaluation: 100%|██████████| 699/699 [01:49<00:00, 6.39it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"🎯 F1-score (weighted) : 0.8735\n",
"⏳ EarlyStopping patience : 1/2\n",
"\n",
"🌟 Epoch 3/3\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Entraînement: 100%|██████████| 2793/2793 [18:26<00:00, 2.52it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"📉 Loss moyenne : 0.4485\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Évaluation: 100%|██████████| 699/699 [01:50<00:00, 6.35it/s]\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"🎯 F1-score (weighted) : 0.8816\n",
"⏳ EarlyStopping patience : 2/2\n",
"🛑 Arrêt anticipé — pas d'amélioration\n"
]
}
],
"source": [
"best_f1 = 0\n",
"patience_counter = 0\n",
"os.makedirs(\"outputs/model\", exist_ok=True)\n",
"\n",
"for epoch in range(EPOCHS):\n",
" print(f\"\\n🌟 Epoch {epoch + 1}/{EPOCHS}\")\n",
" model.train()\n",
" total_loss = 0\n",
"\n",
" for batch in tqdm(train_loader, desc=\"Entraînement\"):\n",
" batch = {k: v.to(device) for k, v in batch.items()}\n",
" logits = model(**batch).logits\n",
" loss = loss_fn(logits, batch[\"labels\"])\n",
" loss.backward()\n",
" optimizer.step()\n",
" scheduler.step()\n",
" optimizer.zero_grad()\n",
" total_loss += loss.item()\n",
"\n",
" avg_loss = total_loss / len(train_loader)\n",
" print(f\"📉 Loss moyenne : {avg_loss:.4f}\")\n",
"\n",
" # 🔍 Évaluation\n",
" model.eval()\n",
" y_true, y_pred = [], []\n",
" with torch.no_grad():\n",
" for batch in tqdm(val_loader, desc=\"Évaluation\"):\n",
" batch = {k: v.to(device) for k, v in batch.items()}\n",
" logits = model(**batch).logits\n",
" preds = torch.argmax(logits, dim=1)\n",
" y_true.extend(batch[\"labels\"].cpu().tolist())\n",
" y_pred.extend(preds.cpu().tolist())\n",
"\n",
" report = classification_report(y_true, y_pred, target_names=[\"Non toxique\", \"Toxique\"], output_dict=True)\n",
" f1 = report[\"weighted avg\"][\"f1-score\"]\n",
" print(f\"🎯 F1-score (weighted) : {f1:.4f}\")\n",
"\n",
" if f1 > best_f1:\n",
" best_f1 = f1\n",
" patience_counter = 0\n",
" print(\"✅ Nouveau meilleur modèle — sauvegarde manuelle...\")\n",
"\n",
" import os\n",
"\n",
" # 📂 Dossier de sauvegarde\n",
" save_dir = \"outputs/model\"\n",
" os.makedirs(save_dir, exist_ok=True)\n",
"\n",
" # 💾 Sauvegarde manuelle des poids\n",
" torch.save(model.state_dict(), os.path.join(save_dir, \"pytorch_model.bin\"))\n",
"\n",
" # 💾 Sauvegarde de la configuration du modèle\n",
" model.config.to_json_file(os.path.join(save_dir, \"config.json\"))\n",
"\n",
" # 💾 Sauvegarde du tokenizer\n",
" tokenizer.save_pretrained(save_dir)\n",
"\n",
" # 💾 Sauvegarde des métriques\n",
" with open(\"outputs/metrics.json\", \"w\") as f:\n",
" json.dump(report, f, indent=4)\n",
"\n",
" else:\n",
" patience_counter += 1\n",
" print(f\"⏳ EarlyStopping patience : {patience_counter}/{PATIENCE}\")\n",
" if patience_counter >= PATIENCE:\n",
" print(\"🛑 Arrêt anticipé — pas d'amélioration\")\n",
" break"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "ba6f2d7c-0daf-48db-96a2-33935dca1d9e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"📊 Métriques sauvegardées :\n",
"\n",
"🗂 Classe : Non toxique\n",
" 🔸 Précision : 0.9294\n",
" 🔸 Rappel : 0.9329\n",
" 🔸 F1-score : 0.9312\n",
"\n",
"🗂 Classe : Toxique\n",
" 🔸 Précision : 0.6193\n",
" 🔸 Rappel : 0.6065\n",
" 🔸 F1-score : 0.6129\n",
"\n",
"🔄 Moyennes pondérées (weighted avg) :\n",
" ✅ Précision : 0.8821\n",
" ✅ Rappel : 0.8831\n",
" ✅ F1-score : 0.8826\n"
]
}
],
"source": [
"import json\n",
"import os\n",
"\n",
"# 📁 Chemin du fichier de métriques\n",
"metrics_path = \"outputs/metrics.json\"\n",
"\n",
"# ✅ Vérifie l'existence du fichier\n",
"if os.path.exists(metrics_path):\n",
" with open(metrics_path, \"r\") as f:\n",
" metrics = json.load(f)\n",
"\n",
" print(\"📊 Métriques sauvegardées :\\n\")\n",
" for label in [\"Non toxique\", \"Toxique\"]:\n",
" print(f\"🗂 Classe : {label}\")\n",
" print(f\" 🔸 Précision : {metrics[label]['precision']:.4f}\")\n",
" print(f\" 🔸 Rappel : {metrics[label]['recall']:.4f}\")\n",
" print(f\" 🔸 F1-score : {metrics[label]['f1-score']:.4f}\\n\")\n",
"\n",
" print(\"🔄 Moyennes pondérées (weighted avg) :\")\n",
" print(f\" ✅ Précision : {metrics['weighted avg']['precision']:.4f}\")\n",
" print(f\" ✅ Rappel : {metrics['weighted avg']['recall']:.4f}\")\n",
" print(f\" ✅ F1-score : {metrics['weighted avg']['f1-score']:.4f}\")\n",
"else:\n",
" print(\"❌ Aucune métrique trouvée dans outputs/metrics.json\")"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|