ALL_mt5-base_15_wikiSQL_sch
This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0585
- Rouge2 Precision: 0.8836
- Rouge2 Recall: 0.8038
- Rouge2 Fmeasure: 0.8358
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: 5e-05
- train_batch_size: 15
- eval_batch_size: 15
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.0796 | 1.0 | 8637 | 0.0675 | 0.8604 | 0.78 | 0.8122 |
| 0.0683 | 2.0 | 17274 | 0.0617 | 0.8681 | 0.7878 | 0.8199 |
| 0.0587 | 3.0 | 25911 | 0.0593 | 0.8733 | 0.7924 | 0.8248 |
| 0.0527 | 4.0 | 34548 | 0.0579 | 0.8776 | 0.795 | 0.8282 |
| 0.0478 | 5.0 | 43185 | 0.0573 | 0.8788 | 0.7981 | 0.8305 |
| 0.0453 | 6.0 | 51822 | 0.0571 | 0.8806 | 0.7999 | 0.8323 |
| 0.043 | 7.0 | 60459 | 0.0571 | 0.8816 | 0.8008 | 0.8333 |
| 0.0399 | 8.0 | 69096 | 0.0570 | 0.881 | 0.8006 | 0.8329 |
| 0.0389 | 9.0 | 77733 | 0.0573 | 0.8823 | 0.8019 | 0.8343 |
| 0.0363 | 10.0 | 86370 | 0.0573 | 0.8828 | 0.8025 | 0.8347 |
| 0.0366 | 11.0 | 95007 | 0.0580 | 0.8835 | 0.8028 | 0.8352 |
| 0.0333 | 12.0 | 103644 | 0.0579 | 0.8836 | 0.8032 | 0.8355 |
| 0.0325 | 13.0 | 112281 | 0.0581 | 0.8833 | 0.8036 | 0.8356 |
| 0.0327 | 14.0 | 120918 | 0.0585 | 0.8839 | 0.8039 | 0.836 |
| 0.0306 | 15.0 | 129555 | 0.0585 | 0.8836 | 0.8038 | 0.8358 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.1