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pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer->huggingface-hub<2.0,>=1.3.0->transformers) (2.19.2)\n", + "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.12/dist-packages (from markdown-it-py>=2.2.0->rich>=12.3.0->typer->huggingface-hub<2.0,>=1.3.0->transformers) (0.1.2)\n" + ] + } + ], + "source": [ + "!pip install transformers datasets torch scikit-learn" + ] + }, + { + "cell_type": "code", + "source": [ + "from datasets import load_dataset\n", + "\n", + "dataset = load_dataset(\"codeparrot/codecomplex\")\n", + "print(dataset)\n", + "print(dataset['train'][0])" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 393, + "referenced_widgets": [ + "2391cf5abfc74a0684079a73d7ce67fb", + "ea675a461fb649ac982085336d55424d", + "6157da59fea54341b8e86188037a8156", + "02bee4d4339944c78a45f6f15e5eb86a", + "fc29d6c33018463d97a715b897437476", + "372d1f16594f492fbde7df62ac21a471", + "181e1402921d4452b7c2a9e55ab2bc6c", + "aed838c551c64755993c36763257a7da", + "1e863882bb4e4969a30e6add125b22c2", + "f2d709f43f7b4feaa8fdc40df034f69d", + "f62096b376c14890a219f849db8f7b9a", + "b26363101dc4468cbe452dd0b6e5d8e7", + "8af14713fe4942c3a4cbb53cf23c7477", + "c6f0713719dd4808a82629f57cdff090", + "b976e9de0f304c20a5e62553375a58b6", + "6f65c68f6cb244a28463c9e956ef94cb", + "2c649e76652149ac8ef495cd44217a77", + "6a1cdd657af245019ef1476540dd22dd", + "1fc61b5c1272434fa6d9dea98d4912f3", + "a3639e8d35cf43ea9671483cb74223e8", + "d8bbff6df5e14b27a9e0c3703df19f1f", + "9d94db6fa0c1480ea8a524ab115e1793", + "7cb59e5a5621417a9faa78a01a9420cb", + "77932a80386b4ca6ba48bd54fc9876ed", + "8ff0e630fb224fc6ab85e42c1badb1dd", + "a52c5e4c0e2c4a19bc84d0b1cb4854cd", + "43fde801fd2143ac9c530fd6beab281f", + "9c841458973f47e08fdf1986a1b54219", + "ca929a4e790a46478100b249788fbada", + "cbf92cb52ef5491e8f82cb6f20937e8c", + "baa21d69483b4560861bdcf58c2d502e", + "17dd5072f6e24341b01a18dd07e4c2d3", + "791e68efb70b4b7386be4cae074b0cb5" + ] + }, + "id": "WjbXMfocJFzq", + "outputId": "3d64a982-ad83-4ed2-d09a-ace8da0f32c9" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.12/dist-packages/huggingface_hub/utils/_auth.py:94: 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" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "README.md: 0.00B [00:00, ?B/s]" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "2391cf5abfc74a0684079a73d7ce67fb" + } + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n", + "WARNING:huggingface_hub.utils._http:Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "data.jsonl: 0%| | 0.00/14.0M [00:00 best_accuracy:\n", + " best_accuracy = test_acc\n", + " torch.save(model.state_dict(), \"best_model.pt\")\n", + " print(f\"✅ Best model saved! Accuracy: {best_accuracy*100:.2f}%\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "jfG8_jmKK0H0", + "outputId": "c6540fad-432e-4bb3-b9e4-24b81c337528" + }, + "execution_count": null, + "outputs": [ + { + "metadata": { + "tags": null + }, + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "🔄 Epoch 1/3\n" + ] + }, + { + "metadata": { + "tags": null + }, + "name": "stderr", + "output_type": "stream", + "text": [ + "Training: 100%|██████████| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "metadata": { + "tags": null + }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Loss: 1.5116 | Train Acc: 40.44% | Test Acc: 66.59%\n", + "✅ Best model saved! Accuracy: 66.59%\n", + "\n", + "🔄 Epoch 2/3\n" + ] + }, + { + "metadata": { + "tags": null + }, + "name": "stderr", + "output_type": "stream", + "text": [ + "Training: 100%|██████████| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.87it/s]\n" + ] + }, + { + "metadata": { + "tags": null + }, + "name": "stdout", + "output_type": "stream", + "text": [ + "Loss: 0.7873 | Train Acc: 73.87% | Test Acc: 76.55%\n", + "✅ Best model saved! Accuracy: 76.55%\n", + "\n", + "🔄 Epoch 3/3\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|��█████████| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.5529 | Train Acc: 82.18% | Test Acc: 78.76%\n", + "✅ Best model saved! Accuracy: 78.76%\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Train 2 more epochs\n", + "for epoch in range(2):\n", + " print(f\"\\n🔄 Epoch {epoch+4}/5\")\n", + " train_loss, train_acc = train_epoch(model, train_loader, optimizer, scheduler, device)\n", + " test_acc = evaluate(model, test_loader, device)\n", + "\n", + " print(f\"Loss: {train_loss:.4f} | Train Acc: {train_acc*100:.2f}% | Test Acc: {test_acc*100:.2f}%\")\n", + "\n", + " if test_acc > best_accuracy:\n", + " best_accuracy = test_acc\n", + " torch.save(model.state_dict(), \"best_model.pt\")\n", + " print(f\"✅ Best model saved! Accuracy: {best_accuracy*100:.2f}%\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "IWKXLIjnP5Au", + "outputId": "9c2373f2-fcdb-4889-b485-3cd80fa20077" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "🔄 Epoch 4/5\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|██████████| 226/226 [06:15<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.4857 | Train Acc: 84.83% | Test Acc: 78.76%\n", + "\n", + "🔄 Epoch 5/5\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|██████████| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.4846 | Train Acc: 84.64% | Test Acc: 78.76%\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "from google.colab import drive\n", + "drive.mount('/content/drive')" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "7UTghGmCYkOP", + "outputId": "49e0b4df-6c3b-4039-defe-e95614fc76dd" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Mounted at /content/drive\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import shutil\n", + "\n", + "# Copy files to Google Drive\n", + "shutil.copy(\"best_model.pt\", \"/content/drive/MyDrive/best_model.pt\")\n", + "shutil.copy(\"label_encoder.pkl\", \"/content/drive/MyDrive/label_encoder.pkl\")\n", + "\n", + "print(\"✅ Files saved to Google Drive!\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "TDsZ4Kj9Yxgv", + "outputId": "82ba03f5-c6ec-493e-c716-eb7f718ddbd6" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "✅ Files saved to Google Drive!\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Test the model directly in Colab\n", + "test_codes = [\n", + " \"public int findMax(int[] arr) { int max = arr[0]; for (int i = 1; i < arr.length; i++) { if (arr[i] > max) max = arr[i]; } return max; }\",\n", + " \"return arr[0];\",\n", + " \"for(int i=0;i best_accuracy:\n", + " best_accuracy = test_acc\n", + " torch.save(model.state_dict(), \"best_model.pt\")\n", + " print(f\"✅ Best model saved! Accuracy: {best_accuracy*100:.2f}%\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "5AumIlrksXNK", + "outputId": "d7f22d59-9cbc-4e43-ec57-83d5d41dc641" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Class weights: tensor([6.8233, 7.5283, 6.2999, 7.3091, 6.7217, 7.5283, 6.9707],\n", + " device='cuda:0')\n", + "\n", + "🔄 Epoch 1/3\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|██████████| 226/226 [06:17<00:00, 1.67s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.4659 | Train Acc: 84.94% | Test Acc: 80.42%\n", + "✅ Best model saved! Accuracy: 80.42%\n", + "\n", + "🔄 Epoch 2/3\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|█████████��| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.3850 | Train Acc: 87.49% | Test Acc: 81.19%\n", + "✅ Best model saved! Accuracy: 81.19%\n", + "\n", + "🔄 Epoch 3/3\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "Training: 100%|██████████| 226/226 [06:14<00:00, 1.66s/it]\n", + "Evaluating: 100%|██████████| 57/57 [00:30<00:00, 1.88it/s]\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Loss: 0.3405 | Train Acc: 89.40% | Test Acc: 81.64%\n", + "✅ Best model saved! Accuracy: 81.64%\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import shutil\n", + "shutil.copy(\"best_model.pt\", \"/content/drive/MyDrive/best_model.pt\")\n", + "print(\"✅ Saved to Google Drive!\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "RmMzxsFDxoTk", + "outputId": "52efc137-7183-4b45-911a-77cadd1ed165" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "✅ Saved to Google Drive!\n" + ] + } + ] + } + ] +} \ No newline at end of file