scores, not percentages

app.py

@@ -14,7 +14,7 @@ def classify_emotion(text):
     # Initialize a dictionary with all emotions and a default score of 0
     emotion_scores = {emotion: 0.0 for emotion in ALL_EMOTIONS}
     
-    # Update the dictionary with the scores returned by the model
+    # Update the dictionary with the raw scores returned by the model
     for item in predictions:
         emotion_scores[item["label"]] = item["score"]
     
@@ -28,14 +28,14 @@ gr.Interface(
         label="Input Text",
         lines=4
     ),
-    outputs=gr.Label(label="Emotion Probabilities"),  # Use gr.Label for a cleaner interface
-    title="CMACHINES | Emotion Detection with DistilBERT",
-    description="This app uses the DistilBERT model fine-tuned for emotion detection. Enter a piece of text to analyze its emotional content!",
+    outputs=gr.Label(label="Emotion Raw Scores"),  # Update label to reflect raw scores
+    title="CMACHINES | motion Detection with DistilBERT (Raw Scores)",
+    description="This app uses the DistilBERT model fine-tuned for emotion detection. Enter a piece of text to analyze its emotional content with raw scores!",
     examples=[
-        "I like you. I love you. Sometime I hate you too.",
-        "I am so happy to see you!",
+        "I like you. I love you. Sometimes I hate you.",
         "I'm really angry about what happened.",
         "The sunset was absolutely beautiful today.",
-        "I'm worried about the upcoming exam."
+        "I'm worried about the upcoming exam.",
+        "Fear is the mind-killer. I will face my fear."
     ]
 ).launch()