Update app.py

app.py

@@ -44,11 +44,10 @@ def predict(text):
     X = preprocess(text, tokenizer)
     pred = model.predict(X)
     probabilities = np.mean(pred, axis=0)
-    final_class = np.argmax(probabilities)
-    if final_class == 0:
-        prediction = "The string is classified as hate speech."
-    else:
+    if probabilities.tolist()[0] > 0.72:
         prediction = "The string is classified as normal speech."
+    else:
+        prediction = "The string is classified as hate speech."
     return prediction, probabilities.tolist()
 
 iface = gr.Interface(