mt5-base-cnn_then_norsumm
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8705
- Rouge1: 30.0222
- Rouge2: 12.8189
- Rougel: 22.7383
- Rougelsum: 26.5718
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|
| 2.5087 | 1.0 | 18 | 3.0861 | 27.0039 | 9.4951 | 19.8448 | 24.6014 |
| 2.5952 | 2.0 | 36 | 3.0623 | 28.0269 | 9.9808 | 20.5307 | 25.5142 |
| 2.6155 | 3.0 | 54 | 3.0309 | 28.7776 | 9.5968 | 20.5973 | 25.3272 |
| 2.6171 | 4.0 | 72 | 3.0298 | 28.458 | 10.1857 | 20.6671 | 25.4602 |
| 2.5156 | 5.0 | 90 | 3.0293 | 29.1667 | 11.0558 | 21.6151 | 26.3694 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
