| | --- |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: ALL_mt5-base_15_spider_10_wikiSQL_sch |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # ALL_mt5-base_15_spider_10_wikiSQL_sch |
| |
|
| | This model was trained from scratch on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.4214 |
| | - Rouge2 Precision: 0.5797 |
| | - Rouge2 Recall: 0.4033 |
| | - Rouge2 Fmeasure: 0.4501 |
| |
|
| | ## 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: 19 |
| | - eval_batch_size: 16 |
| | - 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 0.498 | 1.0 | 912 | 0.3136 | 0.4916 | 0.3236 | 0.366 | |
| | | 0.1561 | 2.0 | 1824 | 0.3188 | 0.541 | 0.3749 | 0.4171 | |
| | | 0.1091 | 3.0 | 2736 | 0.3287 | 0.5457 | 0.3776 | 0.4213 | |
| | | 0.0831 | 4.0 | 3648 | 0.3423 | 0.5544 | 0.3834 | 0.4277 | |
| | | 0.0686 | 5.0 | 4560 | 0.3493 | 0.559 | 0.3831 | 0.4282 | |
| | | 0.0616 | 6.0 | 5472 | 0.3660 | 0.5718 | 0.3992 | 0.4448 | |
| | | 0.0524 | 7.0 | 6384 | 0.3725 | 0.555 | 0.3883 | 0.4322 | |
| | | 0.0469 | 8.0 | 7296 | 0.3804 | 0.5867 | 0.4075 | 0.4551 | |
| | | 0.0416 | 9.0 | 8208 | 0.3889 | 0.5725 | 0.3972 | 0.4432 | |
| | | 0.0382 | 10.0 | 9120 | 0.4028 | 0.575 | 0.3991 | 0.4455 | |
| | | 0.0352 | 11.0 | 10032 | 0.4027 | 0.5754 | 0.3992 | 0.4458 | |
| | | 0.0337 | 12.0 | 10944 | 0.4161 | 0.5769 | 0.4015 | 0.4482 | |
| | | 0.0322 | 13.0 | 11856 | 0.4168 | 0.5803 | 0.4021 | 0.4493 | |
| | | 0.0304 | 14.0 | 12768 | 0.4203 | 0.5783 | 0.4018 | 0.4487 | |
| | | 0.0298 | 15.0 | 13680 | 0.4214 | 0.5797 | 0.4033 | 0.4501 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| |
|
