Update app.py

app.py

@@ -26,10 +26,10 @@ def predict_sentiment(text):
     scores = output[0][0].detach().numpy()
     scores = softmax(scores)
 
-    # Get sentiment labels and scores
+    # Get sentiment labels and scores (formatted to 4 decimal places)
     ranking = np.argsort(scores)[::-1]
     output_text = "\n".join(
-        [f"{config.id2label[ranking[i]]}: {float(scores[ranking[i]])}" for i in range(scores.shape[0])]
+        [f"{config.id2label[ranking[i]]}: {float(scores[ranking[i]]):.4f}" for i in range(scores.shape[0])]
     )
     
     return output_text