diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index cae78bbbe..5008f2cdd 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -403,10 +403,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 53,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Test Performance Metrics:\n",
+      "{'neg_log_loss': 0.3248655516773495, 'roc_auc': np.float64(0.9101514010597728), 'accuracy': 0.8592486436687481, 'balanced_accuracy': np.float64(0.7513226869137615)}\n"
+     ]
+    }
+   ],
+   "source": [
+    "model_pipeline.fit(X_train, Y_train)\n",
+    "Y_pred_proba = model_pipeline.predict_proba(X_test)\n",
+    "\n",
+    "# Calculating the required metrics\n",
+    "test_metrics = {\n",
+    "    'neg_log_loss': log_loss(Y_test, Y_pred_proba),\n",
+    "    'roc_auc': roc_auc_score(Y_test, Y_pred_proba[:, 1]),\n",
+    "    'accuracy': accuracy_score(Y_test, model_pipeline.predict(X_test)),\n",
+    "    'balanced_accuracy': balanced_accuracy_score(Y_test, model_pipeline.predict(X_test))\n",
+    "}\n",
+    "\n",
+    "# Displaying the test metrics as a dictionary\n",
+    "print(\"Test Performance Metrics:\")\n",
+    "print(test_metrics)"
+   ]
   },
   {
    "cell_type": "markdown",