deve

app.py

@@ -46,6 +46,8 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             result = {k: round(v * 100, 4) for k, v in result.items()}
             prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in preds]
             result["gen_len"] = np.mean(prediction_lens)
+            accuracy = accuracy_score(decoded_labels, decoded_preds)
+            result["accuracy"] = round(accuracy * 100, 4)            
             return result
         
         login(api_key.strip())
@@ -222,7 +224,7 @@ def fine_tune_model(model, dataset_name, hub_id, api_key, num_epochs, batch_size
             train_dataset=train_set['train'], 
             eval_dataset=train_set['validation'], 
             compute_metrics=compute_metrics,
-            #data_collator=data_collator,
+            sdata_collator=data_collator,
             #processing_class=tokenizer,
         )