Update app.py

app.py

@@ -36,7 +36,7 @@ def predict_text(params):
         return {"error": "Missing required parameters: 'texts'"}
 
     solutions = []
-    confidence_threshold = 0.5  # Define your confidence threshold
+    confidence_threshold = 0.85  # Define your confidence threshold
 
     for text, file_id in zip(texts, file_ids):
         encoding = bert_tokenizer.encode_plus(
@@ -60,7 +60,7 @@ def predict_text(params):
 
         # Get the confidence score for the predicted label
         confidence = softmax_scores[pred_label]
-
+        print(confidence)
         # If confidence is below the threshold, set answer to None
         if confidence < confidence_threshold:
             pred_label = 7  # Set to 'None' class