Update app.py

app.py

@@ -95,15 +95,7 @@ def evaluate_model_with_report(val_loader):
 def generate_performance_metrics():
     model.eval()  # Set model to evaluation mode
     
-    y_pred = []
-    
-    with torch.no_grad():
-        for email in X_test:
-            inputs = tokenizer(email, padding=True, truncation=True, max_length=128, return_tensors="pt")
-            outputs = model(**inputs)
-            prediction = torch.argmax(outputs.logits, dim=1).item()
-            y_pred.append(prediction)
-    
+    y_pred = [] 
     accuracy = accuracy_score(y_test, y_pred)
     report = classification_report(y_test, y_pred, output_dict=True)