Update app.py

app.py

@@ -15,9 +15,8 @@ def predict_sentiment(text):
     input_ids = tf.constant(bert_tokenizer.encode(text, add_special_tokens=True))[None, :]  # Menambahkan token khusus [CLS] dan [SEP]
     logits = bert_model(input_ids)[0]
     probabilities = tf.nn.softmax(logits, axis=1)
-    sentiment = tf.argmax(probabilities, axis=1)
-    return sentiment.numpy()[0]
-
+     sentiment_score, sentiment_label = probabilities.numpy()[0]
+    return sentiment_score, sentiment_label
 
 # Judul aplikasi
 st.title('Prediksi Sentimen menggunakan BERT')
@@ -30,8 +29,8 @@ if st.button('Prediksi'):
     if text.strip() == '':
         st.warning('Masukkan teks terlebih dahulu.')
     else:
-        sentiment = predict_sentiment(text)
-        if sentiment == 0:
-            st.error('Sentimen: Negatif')
+        sentiment_score, sentiment_label = predict_sentiment(text)
+        if sentiment_label == 0:
+            st.error(f'Sentimen: Negatif, Skor: {sentiment_score:.2f}')
         else:
-            st.success('Sentimen: Positif')
+            st.success(f'Sentimen: Positif, Skor: {sentiment_score:.2f}')