| | --- |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: ALL_mt5-base_10_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_10_spider_15_wikiSQL_new |
| |
|
| | This model was trained from scratch on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2575 |
| | - Rouge2 Precision: 0.6182 |
| | - Rouge2 Recall: 0.4218 |
| | - Rouge2 Fmeasure: 0.4725 |
| |
|
| | ## 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: 10 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 0.2255 | 1.0 | 1021 | 0.2284 | 0.5416 | 0.3565 | 0.4021 | |
| | | 0.1417 | 2.0 | 2042 | 0.2184 | 0.5668 | 0.3778 | 0.4244 | |
| | | 0.1087 | 3.0 | 3063 | 0.2238 | 0.5823 | 0.3944 | 0.4421 | |
| | | 0.0884 | 4.0 | 4084 | 0.2273 | 0.6072 | 0.4136 | 0.4634 | |
| | | 0.0769 | 5.0 | 5105 | 0.2393 | 0.5998 | 0.4047 | 0.4542 | |
| | | 0.0666 | 6.0 | 6126 | 0.2399 | 0.6073 | 0.4128 | 0.4625 | |
| | | 0.0592 | 7.0 | 7147 | 0.2474 | 0.6081 | 0.4128 | 0.4626 | |
| | | 0.0551 | 8.0 | 8168 | 0.2530 | 0.6145 | 0.4181 | 0.4685 | |
| | | 0.0517 | 9.0 | 9189 | 0.2527 | 0.6168 | 0.4203 | 0.4708 | |
| | | 0.0507 | 10.0 | 10210 | 0.2575 | 0.6182 | 0.4218 | 0.4725 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| |
|
