Update app.py

app.py

@@ -156,28 +156,33 @@ def evaluate_uploaded_json(user_file, model_name):
 
     class_accuracy = {
         cls: class_correct[cls] / class_total[cls] if class_total[cls] > 0 else 0
-        for cls in CLASS_LIST[:-5] 
-    }
+        for cls in CLASS_LIST[:-5]  
 
 
+    category_correct = {}
+    category_total = {}
+
     for category, sub_classes in CATEGORY_MAPPING.items():
-        valid_sub_classes = [cls for cls in sub_classes if cls in class_accuracy]  
-        if valid_sub_classes:
-            class_accuracy[category] = sum(class_accuracy[cls] for cls in valid_sub_classes) / len(valid_sub_classes)
+        category_correct[category] = sum(class_correct.get(sub_cls, 0) for sub_cls in sub_classes)
+        category_total[category] = sum(class_total.get(sub_cls, 0) for sub_cls in sub_classes)
+        if category_total[category] > 0:
+            class_accuracy[category] = category_correct[category] / category_total[category]
         else:
-            class_accuracy[category] = 0  
-
+            class_accuracy[category] = 0
 
-    save_class_accuracy_to_hf_dataset(model_name, class_accuracy)
 
     class_accuracy_str = "\n".join(
         [
             f"- {cls}: {class_accuracy[cls]:.2%} "
-            f"({class_correct.get(cls, 0)}/{class_total.get(cls, 0)} correct)"
+            f"({class_correct.get(cls, category_correct.get(cls, 0))}/"
+            f"{class_total.get(cls, category_total.get(cls, 0))} correct)"
             for cls in CLASS_LIST
         ]
     )
 
+
+    save_class_accuracy_to_hf_dataset(model_name, class_accuracy)
+
     return (
         f"Model: {model_name}\n"
         f"Overall Accuracy: {correct / total:.2%} ({correct}/{total} correct)\n"