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README.md

@@ -130,9 +130,8 @@ with torch.no_grad():
     probs = torch.softmax(logits, dim=-1)[0]
     pred_id = torch.argmax(probs).item()
 
-# Get accent
-accents = ["australia", "canada", "england", "indian", "latin", "us"]
-predicted_accent = accents[pred_id]
+# Get accent and confidence from model config
+predicted_accent = model.config.id2label[pred_id]
 confidence = probs[pred_id].item()
 
 print(f"Predicted Accent: {predicted_accent}")
@@ -167,9 +166,14 @@ for segment in segments:
 
     predictions.append(probs)
 
-# Aggregate predictions
+# Aggregate predictions across segments
 avg_probs = torch.stack(predictions).mean(dim=0)
-final_accent = accents[torch.argmax(avg_probs).item()]
+final_pred_id = torch.argmax(avg_probs).item()
+final_accent = model.config.id2label[final_pred_id]
+final_confidence = avg_probs[final_pred_id].item()
+
+print(f"Final Predicted Accent: {final_accent}")
+print(f"Confidence: {final_confidence:.1%}")
 ```
 
 ## Performance