Update README.md

README.md

@@ -70,7 +70,7 @@ def predict(path, sampling_rate):
         logits = model(**inputs).logits
 
     scores = F.softmax(logits, dim=1).detach().cpu().numpy()[0]
-    outputs = [{"Emotion": config.id2label[i], "Score": f"{round(score * 100, 3):.1f}%"} for i, score in enumerate(scores)]
+    outputs = [{"Label": config.id2label[i], "Score": f"{round(score * 100, 3):.1f}%"} for i, score in enumerate(scores)]
     return outputs
 ```
 
@@ -86,7 +86,7 @@ outputs = predict(path, sampling_rate)
 {'Label': 'Happiness', 'Score': '0.0%'},
 {'Label': 'Neutral', 'Score': '0.0%'},
 {'Label': 'Sadness', 'Score': '99.9%'},
-{'Label': 'Surprise', 'Score': '0.0%'}]
+{'Label': 'Surprise', 'Score': '0.0%'}
 ]
 ```