mt5-small-mlsum
This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container. For more information look at:
- 🤗 Transformers Documentation: Amazon SageMaker
- Example Notebooks
- Amazon SageMaker documentation for Hugging Face
- Python SDK SageMaker documentation for Hugging Face
- Deep Learning Container
Hyperparameters
{ "dataset_config": "es", "dataset_name": "mlsum", "do_eval": true, "do_predict": true, "do_train": true, "fp16": true, "max_target_length": 64, "model_name_or_path": "google/mt5-small", "num_train_epochs": 10, "output_dir": "/opt/ml/checkpoints", "per_device_eval_batch_size": 4, "per_device_train_batch_size": 4, "predict_with_generate": true, "sagemaker_container_log_level": 20, "sagemaker_program": "run_summarization.py", "save_strategy": "epoch", "seed": 7, "summary_column": "summary", "text_column": "text" }
Usage
Results
| key | value |
|---|---|
| eval_rouge1 | 26.4352 |
| eval_rouge2 | 8.9293 |
| eval_rougeL | 21.2622 |
| eval_rougeLsum | 21.5518 |
| test_rouge1 | 26.0756 |
| test_rouge2 | 8.4669 |
| test_rougeL | 20.8167 |
| test_rougeLsum | 21.0822 |