Update app.py

app.py

@@ -62,17 +62,26 @@ def evaluate_model(file, name):
         if len(y_pred) != len(y_test):
             return "❌ Model output length does not match test set.", load_leaderboard()
 
-        accuracy = 100.0 * (y_pred == y_test).mean()
-        avg_time = elapsed / len(X_test)
+        accuracy = round(100.0 * (y_pred == y_test).mean(), 5)
+        avg_time = round(elapsed / len(X_test), 5)
 
         leaderboard = load_leaderboard()
+
+        # Remove existing entries for the same name
+        leaderboard = leaderboard[leaderboard["Name"] != name]
+
+        # Add new result
         new_entry = pd.DataFrame([{
             "Name": name,
-            "Accuracy": round(accuracy, 2),
-            "Avg Time (ms)": round(avg_time, 2)
+            "Accuracy": accuracy,
+            "Avg Time (ms)": avg_time
         }])
         leaderboard = pd.concat([leaderboard, new_entry], ignore_index=True)
-        leaderboard = leaderboard.sort_values(by=["Accuracy", "Avg Time (ms)"], ascending=[False, True]).reset_index(drop=True)
+
+        # Keep only the best score per name
+        leaderboard = leaderboard.sort_values(by=["Accuracy", "Avg Time (ms)"], ascending=[False, True])
+        leaderboard = leaderboard.drop_duplicates(subset=["Name"], keep="first").reset_index(drop=True)
+
         leaderboard.to_csv(LEADERBOARD_PATH, index=False)
 
         return "", leaderboard