added the final_model weight and evaluation pipeline

NN_evaluation.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "459d08f0-b6d6-4062-8e60-d3349ae86cce",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "huggingface/tokenizers: The current process just got forked, after parallelism has already been used. Disabling parallelism to avoid deadlocks...\n",
+      "To disable this warning, you can either:\n",
+      "\t- Avoid using `tokenizers` before the fork if possible\n",
+      "\t- Explicitly set the environment variable TOKENIZERS_PARALLELISM=(true | false)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.com\n",
+      "Requirement already satisfied: FlagEmbedding in /opt/conda/lib/python3.11/site-packages (1.3.3)\n",
+      "Requirement already satisfied: torch>=1.6.0 in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (2.2.2+cu121)\n",
+      "Requirement already satisfied: transformers==4.44.2 in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (4.44.2)\n",
+      "Requirement already satisfied: datasets==2.19.0 in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (2.19.0)\n",
+      "Requirement already satisfied: accelerate>=0.20.1 in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (1.2.0)\n",
+      "Requirement already satisfied: sentence-transformers in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (3.3.1)\n",
+      "Requirement already satisfied: peft in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (0.14.0)\n",
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+      "Requirement already satisfied: sentencepiece in /opt/conda/lib/python3.11/site-packages (from FlagEmbedding) (0.2.0)\n",
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+      "Requirement already satisfied: numpy>=1.17 in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (1.26.4)\n",
+      "Requirement already satisfied: pyarrow>=12.0.0 in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (15.0.2)\n",
+      "Requirement already satisfied: pyarrow-hotfix in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (0.6)\n",
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+      "Requirement already satisfied: pandas in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (2.2.2)\n",
+      "Requirement already satisfied: requests>=2.19.0 in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (2.31.0)\n",
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+      "Requirement already satisfied: multiprocess in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (0.70.16)\n",
+      "Requirement already satisfied: fsspec<=2024.3.1,>=2023.1.0 in /opt/conda/lib/python3.11/site-packages (from fsspec[http]<=2024.3.1,>=2023.1.0->datasets==2.19.0->FlagEmbedding) (2024.3.1)\n",
+      "Requirement already satisfied: aiohttp in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (3.11.10)\n",
+      "Requirement already satisfied: huggingface-hub>=0.21.2 in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (0.26.5)\n",
+      "Requirement already satisfied: packaging in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (24.0)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /opt/conda/lib/python3.11/site-packages (from datasets==2.19.0->FlagEmbedding) (6.0.1)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /opt/conda/lib/python3.11/site-packages (from transformers==4.44.2->FlagEmbedding) (2024.11.6)\n",
+      "Requirement already satisfied: safetensors>=0.4.1 in /opt/conda/lib/python3.11/site-packages (from transformers==4.44.2->FlagEmbedding) (0.4.5)\n",
+      "Requirement already satisfied: tokenizers<0.20,>=0.19 in /opt/conda/lib/python3.11/site-packages (from transformers==4.44.2->FlagEmbedding) (0.19.1)\n",
+      "Requirement already satisfied: psutil in /opt/conda/lib/python3.11/site-packages (from accelerate>=0.20.1->FlagEmbedding) (5.9.8)\n",
+      "Requirement already satisfied: typing-extensions>=4.8.0 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (4.11.0)\n",
+      "Requirement already satisfied: sympy in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (1.12)\n",
+      "Requirement already satisfied: networkx in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (3.3)\n",
+      "Requirement already satisfied: jinja2 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (3.1.3)\n",
+      "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.105)\n",
+      "Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (8.9.2.26)\n",
+      "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.3.1)\n",
+      "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (11.0.2.54)\n",
+      "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (10.3.2.106)\n",
+      "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (11.4.5.107)\n",
+      "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.0.106)\n",
+      "Requirement already satisfied: nvidia-nccl-cu12==2.19.3 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (2.19.3)\n",
+      "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (12.1.105)\n",
+      "Requirement already satisfied: triton==2.2.0 in /opt/conda/lib/python3.11/site-packages (from torch>=1.6.0->FlagEmbedding) (2.2.0)\n",
+      "Requirement already satisfied: nvidia-nvjitlink-cu12 in /opt/conda/lib/python3.11/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.6.0->FlagEmbedding) (12.4.127)\n",
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+      "Requirement already satisfied: scipy in /opt/conda/lib/python3.11/site-packages (from sentence-transformers->FlagEmbedding) (1.13.0)\n",
+      "Requirement already satisfied: Pillow in /opt/conda/lib/python3.11/site-packages (from sentence-transformers->FlagEmbedding) (10.3.0)\n",
+      "Requirement already satisfied: soupsieve>1.2 in /opt/conda/lib/python3.11/site-packages (from beautifulsoup4>=4.4.1->ir-datasets->FlagEmbedding) (2.5)\n",
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+      "Requirement already satisfied: joblib>=1.2.0 in /opt/conda/lib/python3.11/site-packages (from scikit-learn->sentence-transformers->FlagEmbedding) (1.4.0)\n",
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+      "Requirement already satisfied: mpmath>=0.19 in /opt/conda/lib/python3.11/site-packages (from sympy->torch>=1.6.0->FlagEmbedding) (1.3.0)\n",
+      "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.11/site-packages (from python-dateutil>=2.8.2->pandas->datasets==2.19.0->FlagEmbedding) (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"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3cb658d3527149008a6d17938370142d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Fetching 30 files:   0%|          | 0/30 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Encoding titles...\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "You're using a XLMRobertaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Processed 20/20 titles\n",
+      "Test Accuracy: 0.9000\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import pandas as pd\n",
+    "from sklearn.metrics import accuracy_score\n",
+    "from torch.utils.data import DataLoader, TensorDataset\n",
+    "!pip install -U FlagEmbedding\n",
+    "from FlagEmbedding import BGEM3FlagModel\n",
+    "import torch.nn as nn\n",
+    "model = BGEM3FlagModel('BAAI/bge-m3')\n",
+    "\n",
+    "\n",
+    "# Define paths\n",
+    "test_data_path = \"/home/jovyan/work/test_data_random_subset.csv\"\n",
+    "model_weights_path = \"/home/jovyan/work/model_weights/final_model.pth\"\n",
+    "\n",
+    "data = data = pd.read_csv(test_data_path)\n",
+    "titles = data['title'].tolist()\n",
+    "labels = data['labels'].tolist()\n",
+    "\n",
+    "batch_size = 32\n",
+    "embeddings = []\n",
+    "\n",
+    "print('Encoding titles...')\n",
+    "for i in range(0, len(titles), batch_size):\n",
+    "    batch = titles[i:i + batch_size]\n",
+    "    batch_embeddings = model.encode(batch, batch_size=batch_size, max_length=512)['dense_vecs']\n",
+    "    embeddings.extend(batch_embeddings)\n",
+    "    print(f\"Processed {i + len(batch)}/{len(titles)} titles\")\n",
+    "\n",
+    "embeddings_df = pd.DataFrame(embeddings)\n",
+    "embeddings_df['label'] = labels\n",
+    "\n",
+    "X_test = torch.FloatTensor(embeddings_df.iloc[:, :-1].values)  # Features\n",
+    "y_test = torch.FloatTensor(embeddings_df.iloc[:, -1].values).view(-1, 1)  # Labels\n",
+    "\n",
+    "# Create DataLoader for the test dataset\n",
+    "test_dataset = TensorDataset(X_test, y_test)\n",
+    "test_loader = DataLoader(test_dataset, batch_size=32, shuffle=False)\n",
+    "\n",
+    "# Define the model architecture\n",
+    "class EmbeddingMLPClassifier(nn.Module):\n",
+    "    def __init__(self,\n",
+    "                 input_dim=1024,\n",
+    "                 hidden_layers=[512, 256, 128],\n",
+    "                 dropout_rate=0.2,\n",
+    "                 device=None):\n",
+    "        super(EmbeddingMLPClassifier, self).__init__()\n",
+    "        self.device = device or torch.device('cpu')  # Force CPU usage\n",
+    "\n",
+    "        layers = []\n",
+    "        prev_dim = input_dim\n",
+    "        for hidden_dim in hidden_layers:\n",
+    "            layers.extend([\n",
+    "                nn.Linear(prev_dim, hidden_dim),\n",
+    "                nn.BatchNorm1d(hidden_dim),\n",
+    "                nn.ReLU(),\n",
+    "                nn.Dropout(dropout_rate)\n",
+    "            ])\n",
+    "            prev_dim = hidden_dim\n",
+    "\n",
+    "        layers.append(nn.Linear(prev_dim, 1))\n",
+    "        layers.append(nn.Sigmoid())\n",
+    "\n",
+    "        self.model = nn.Sequential(*layers)\n",
+    "        self.to(self.device)\n",
+    "\n",
+    "    def forward(self, x):\n",
+    "        return self.model(x)\n",
+    "\n",
+    "# Load the saved model\n",
+    "device = torch.device('cpu')  # Force evaluation on CPU\n",
+    "model = EmbeddingMLPClassifier(input_dim=X_test.shape[1], device=device)\n",
+    "model.load_state_dict(torch.load(model_weights_path, map_location=device))  # Map weights to CPU\n",
+    "model.eval()\n",
+    "\n",
+    "# Evaluate the model on the test set\n",
+    "test_preds, test_labels = [], []\n",
+    "\n",
+    "with torch.no_grad():\n",
+    "    for batch_X, batch_y in test_loader:\n",
+    "        batch_X = batch_X.to(device)  # Ensure data is on CPU\n",
+    "        batch_y = batch_y.to(device)\n",
+    "\n",
+    "        outputs = model(batch_X)\n",
+    "        preds = (outputs > 0.5).float()\n",
+    "\n",
+    "        test_preds.extend(preds.cpu().numpy())\n",
+    "        test_labels.extend(batch_y.cpu().numpy())\n",
+    "\n",
+    "# Calculate accuracy\n",
+    "test_accuracy = accuracy_score(test_labels, test_preds)\n",
+    "print(f\"Test Accuracy: {test_accuracy:.4f}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e2869985-46ac-4a07-a13d-c11e01ef9ec4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "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": "3.11.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

final_model.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:de1266abb692bcdb1e6ceb8462ffa0a29be5921d7bbeaf11ffe6f265e6750db8
+size 2778685