EN_mt5-base_10_wikiSQL
This model is a fine-tuned version of google/mt5-base on the wikisql dataset. It achieves the following results on the evaluation set:
- Loss: 0.0849
- Rouge2 Precision: 0.864
- Rouge2 Recall: 0.787
- Rouge2 Fmeasure: 0.8178
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 21
- 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 |
|---|---|---|---|---|---|---|
| 0.1677 | 1.0 | 3085 | 0.1224 | 0.8269 | 0.7506 | 0.7803 |
| 0.1287 | 2.0 | 6170 | 0.1028 | 0.8458 | 0.7673 | 0.7988 |
| 0.1086 | 3.0 | 9255 | 0.0959 | 0.8511 | 0.7727 | 0.8042 |
| 0.0965 | 4.0 | 12340 | 0.0900 | 0.8543 | 0.777 | 0.808 |
| 0.089 | 5.0 | 15425 | 0.0883 | 0.8575 | 0.7802 | 0.8111 |
| 0.0809 | 6.0 | 18510 | 0.0866 | 0.8606 | 0.7834 | 0.8143 |
| 0.0771 | 7.0 | 21595 | 0.0860 | 0.8625 | 0.7851 | 0.8161 |
| 0.0745 | 8.0 | 24680 | 0.0855 | 0.8633 | 0.7862 | 0.8171 |
| 0.0715 | 9.0 | 27765 | 0.0848 | 0.8641 | 0.7869 | 0.8178 |
| 0.0702 | 10.0 | 30850 | 0.0849 | 0.864 | 0.787 | 0.8178 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
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