deve

app.py

@@ -98,7 +98,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
                 max_length=max_length,  # Set to None for dynamic padding
                 truncation=True,
                 padding='max_length',
-                #return_tensors='pt', 
+                return_tensors='pt', 
             )
         
             # Setup the decoder input IDs (shifted right)
@@ -108,7 +108,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
                 truncation=True,
                 padding='max_length',
                 #text_target=examples['target'],
-                #return_tensors='pt', 
+                return_tensors='pt', 
             )
             #labels["input_ids"] = [
              #   [(l if l != tokenizer.pad_token_id else -100) for l in label] for label in labels["input_ids"]
@@ -211,7 +211,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
         valid_set = dataset['validation'].map(tokenize_function, batched=True)
         
         print(train_set['labels'])
-
+        print(train_set.keys())
         print('DONE')