Callbacks

Author: Sayed-Hossein-Hosseini

RhythmAttention_Hybrid_CNN_Transformer_Architecture_for_Arrhythmia_Classification.ipynb

@@ -89,10 +89,11 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 7,
+      "execution_count": 11,
       "metadata": {},
       "outputs": [],
       "source": [
+        "import os\n",
         "import pandas as pd\n",
         "import numpy as np\n",
         "import tensorflow as tf\n",
@@ -518,6 +519,52 @@
         "model = build_rhythm_attention_model()\n",
         "model.summary()"
       ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "## **Callbacks**"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "# Create a folder to save the model if it doesn't exist\n",
+        "if not os.path.exists('models'):\n",
+        "    os.makedirs('models')\n",
+        "\n",
+        "# Updated Callbacks\n",
+        "callbacks = [\n",
+        "    # 1. Early Stopping: Stop training when val_loss stops improving\n",
+        "    tf.keras.callbacks.EarlyStopping(\n",
+        "        monitor='val_loss', \n",
+        "        patience=12, \n",
+        "        restore_best_weights=True,\n",
+        "        verbose=1\n",
+        "    ),\n",
+        "    \n",
+        "    # 2. Model Checkpoint: Save the best model based on validation loss\n",
+        "    tf.keras.callbacks.ModelCheckpoint(\n",
+        "        filepath='models/RhythmAttention_best.keras', \n",
+        "        monitor='val_loss', \n",
+        "        save_best_only=True,\n",
+        "        verbose=1\n",
+        "    ),\n",
+        "    \n",
+        "    # 3. Learning Rate Scheduler: Reduce LR when learning plateaus\n",
+        "    tf.keras.callbacks.ReduceLROnPlateau(\n",
+        "        monitor='val_loss', \n",
+        "        factor=0.5, \n",
+        "        patience=6, \n",
+        "        min_lr=0.00001,\n",
+        "        verbose=1\n",
+        "    )\n",
+        "]"
+      ]
     }
   ],
   "metadata": {