| | --- |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: ALL_mt5-base_15_spider_15_wikiSQL_new |
| | 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_15_wikiSQL_new |
| |
|
| | This model was trained from scratch on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0160 |
| | - Rouge2 Precision: 0.9066 |
| | - Rouge2 Recall: 0.6077 |
| | - Rouge2 Fmeasure: 0.6916 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 0.3243 | 1.0 | 1021 | 0.1423 | 0.6057 | 0.3898 | 0.4466 | |
| | | 0.1428 | 2.0 | 2042 | 0.0864 | 0.7175 | 0.4822 | 0.5453 | |
| | | 0.1071 | 3.0 | 3063 | 0.0644 | 0.7701 | 0.5183 | 0.5867 | |
| | | 0.0845 | 4.0 | 4084 | 0.0517 | 0.798 | 0.5398 | 0.611 | |
| | | 0.0723 | 5.0 | 5105 | 0.0417 | 0.8294 | 0.5584 | 0.6336 | |
| | | 0.0612 | 6.0 | 6126 | 0.0349 | 0.8411 | 0.5623 | 0.6394 | |
| | | 0.0528 | 7.0 | 7147 | 0.0302 | 0.853 | 0.5731 | 0.6514 | |
| | | 0.0475 | 8.0 | 8168 | 0.0254 | 0.8734 | 0.5842 | 0.6649 | |
| | | 0.0427 | 9.0 | 9189 | 0.0227 | 0.8855 | 0.5943 | 0.6757 | |
| | | 0.0398 | 10.0 | 10210 | 0.0208 | 0.8901 | 0.5965 | 0.6787 | |
| | | 0.0362 | 11.0 | 11231 | 0.0190 | 0.8943 | 0.5986 | 0.6815 | |
| | | 0.0343 | 12.0 | 12252 | 0.0178 | 0.9024 | 0.6045 | 0.6882 | |
| | | 0.0329 | 13.0 | 13273 | 0.0170 | 0.9075 | 0.6075 | 0.692 | |
| | | 0.0316 | 14.0 | 14294 | 0.0162 | 0.9081 | 0.6092 | 0.6935 | |
| | | 0.031 | 15.0 | 15315 | 0.0160 | 0.9066 | 0.6077 | 0.6916 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| |
|
