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h11>=0.16 in /usr/local/lib/python3.12/dist-packages (from httpcore==1.*->httpx<1,>=0.23.0->huggingface-hub<2.0,>=1.3.0->transformers) (0.16.0)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.17.0)\n", "Requirement already satisfied: click>=8.2.1 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface-hub<2.0,>=1.3.0->transformers) (8.3.1)\n", "Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface-hub<2.0,>=1.3.0->transformers) (1.5.4)\n", "Requirement already satisfied: rich>=12.3.0 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface-hub<2.0,>=1.3.0->transformers) (13.9.4)\n", "Requirement already satisfied: annotated-doc>=0.0.2 in /usr/local/lib/python3.12/dist-packages (from typer->huggingface-hub<2.0,>=1.3.0->transformers) (0.0.4)\n", "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.12/dist-packages (from rich>=12.3.0->typer->huggingface-hub<2.0,>=1.3.0->transformers) (4.0.0)\n", "Requirement already satisfied: 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" ] } ] } ] }