update model save logic

utils.py

@@ -227,7 +227,7 @@ def get_update(data_year):
     model_score = float(data.split()[-1])
     MSE =  np.sqrt(mean_squared_error(y_test, model_RFR.predict(X_test)))
 
-    if mean_squared_error(y_test, model_RFR.predict(X_test)) > model_score:
+    if MSE < model_score:
         pickle.dump(model_RFR, open('model.sav', 'wb'))
         f = open("model.log", "w")
         f.write(f'model_score = {MSE}')