Update app.py

app.py

@@ -30,12 +30,9 @@ if st.button("Predict"):
         # Convert to numpy array if necessary
         predicted_scores = predictions.numpy()
 
-        # Apply a significant reduction to lower the scores
-        target_average_score = 6.0
-        current_average_score = np.mean(predicted_scores)
-        reduction_amount = current_average_score - target_average_score
-
-        adjusted_scores = predicted_scores - reduction_amount
+        # Apply uniform reduction (e.g., reduce by a factor)
+        reduction_factor = 0.7  # Reduce scores by 30%
+        adjusted_scores = predicted_scores * reduction_factor
 
         # Ensure scores do not go below zero
         adjusted_scores = np.maximum(adjusted_scores, 0)
@@ -44,8 +41,8 @@ if st.button("Predict"):
         normalized_scores = (adjusted_scores / adjusted_scores.max()) * 9  # Scale to 9
 
         # Apply an additional reduction to the overall score if needed
+        additional_reduction = 1.0  # Adjust this value as needed
         overall_score_index = len(normalized_scores) - 1
-        additional_reduction = 2.0  # Adjust this value as needed
         normalized_scores[overall_score_index] = max(normalized_scores[overall_score_index] - additional_reduction, 0)
 
         # Round the scores