Logs

app.py

@@ -131,6 +131,7 @@ def evaluate_model(model, dataloader, device):
 
             # Forward pass to get logits
             outputs = model(input_ids, attention_mask=attention_mask)
+
             logits = outputs.logits
 
             # Get predictions
@@ -150,6 +151,10 @@ def evaluate_model(model, dataloader, device):
     print("evaluate_model sizes")
     print(len(all_preds))
     print(len(all_labels))
+    print(id2label(all_preds[0]))
+    print(id2label(all_labels[0]))
+    print(id2label(all_preds[1]))
+    print(id2label(all_labels[1]))
     all_preds = np.asarray(all_preds, dtype=np.float32)
     all_labels = np.asarray(all_labels, dtype=np.float32)
     accuracy = accuracy_score(all_labels, all_preds)