Update app.py

app.py

@@ -38,14 +38,17 @@ iface.launch()
 
 # Evaluate the model
 model.eval()
+print("model.eval ", model.eval())
 with torch.no_grad():
     outputs = model(input_ids=input_ids, attention_mask=attention_mask)
+    print("outputs ", outputs)
 
 # Convert predicted token IDs back to text
 predicted_text = tokenizer.batch_decode(outputs.logits.argmax(dim=-1), skip_special_tokens=True)
 
 # Get ground truth labels from the dataset
 labels = dataset["audio"]  # Replace "labels" with the appropriate key in your dataset
+print("labels are ", labels)
 
 # Compute WER
 wer_score = wer(labels, predicted_text)