mt5-small-finetuned-books-summarization
This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.4465
- Rouge1: 10.6276
- Rouge2: 3.4285
- Rougel: 10.246
- Rougelsum: 10.2954
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 11.2862 | 1.0 | 1209 | 4.1148 | 6.5572 | 1.4127 | 6.3533 | 6.3795 |
| 5.2609 | 2.0 | 2418 | 3.5019 | 10.6861 | 3.0623 | 10.2926 | 10.2771 |
| 4.7793 | 3.0 | 3627 | 3.4465 | 10.6276 | 3.4285 | 10.246 | 10.2954 |
Framework versions
- Transformers 5.15.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.22.2