| from transformers import DistilBertForSequenceClassification, Trainer | |
| from train import train_model | |
| def evaluate(): | |
| # In a real pipeline, we'd load the saved model | |
| trainer, test_dataset = train_model() | |
| results = trainer.evaluate() | |
| print(results) | |
| with open('results.txt', 'w') as f: | |
| f.write(str(results)) | |
| if __name__ == '__main__': | |
| evaluate() | |