Fix

app.py

@@ -52,7 +52,8 @@ def classify_text(test_text, selected_model):
         return dict(zip(categories, map(float,probabilities)))
     elif selected_model == 'Model 3':
         models = [f_30_40_model, f_40_55_model, m_30_40_model, m_40_55_model]
-        performance_labels = []
+        predicted_labels = []
+        performance_labels = ['Lite god', 'Nokså god', 'God']
         inputs = tokenizer(test_text, return_tensors="pt")
 
         for model in models:
@@ -62,12 +63,8 @@ def classify_text(test_text, selected_model):
                 probabilities = torch.softmax(logits, dim=1)
             
             predicted_class = torch.argmax(probabilities, dim=1).item()
-            performance_labels = ['Lite god', 'Nokså god', 'God']
             predicted_performance = performance_labels[predicted_class]
-            
-            class_labels = model.config.id2label
-            predicted_label = class_labels[predicted_class]
-            performance_labels.append(predicted_label)
+            predicted_labels.append(predicted_performance)
 
         return dict(zip(categories, map(float,performance_labels)))