| --- |
| base_model: TeeA/T5-Text2SQL-Bilingual |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: Text2SQL-Bilingual |
| 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. --> |
|
|
| # Text2SQL-Bilingual |
|
|
| This model is a fine-tuned version of [TeeA/T5-Text2SQL-Bilingual](https://huggingface.co/TeeA/T5-Text2SQL-Bilingual) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.4095 |
| - Rouge1: 0.8431 |
| - Rouge2: 0.7496 |
| - Rougel: 0.8358 |
| - Rougelsum: 0.8364 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | 1.6571 | 1.0 | 4389 | 1.5119 | 0.8292 | 0.7219 | 0.8204 | 0.8210 | |
| | 1.6181 | 2.0 | 8778 | 1.4851 | 0.8329 | 0.7293 | 0.8239 | 0.8245 | |
| | 1.6051 | 3.0 | 13167 | 1.4654 | 0.8324 | 0.7313 | 0.8243 | 0.8249 | |
| | 1.5903 | 4.0 | 17556 | 1.4522 | 0.8372 | 0.7396 | 0.8292 | 0.8298 | |
| | 1.5635 | 5.0 | 21945 | 1.4364 | 0.8399 | 0.7438 | 0.8320 | 0.8328 | |
| | 1.5304 | 6.0 | 26334 | 1.4274 | 0.8417 | 0.7455 | 0.8342 | 0.8346 | |
| | 1.5267 | 7.0 | 30723 | 1.4185 | 0.8409 | 0.7453 | 0.8336 | 0.8341 | |
| | 1.5241 | 8.0 | 35112 | 1.4129 | 0.8419 | 0.7480 | 0.8347 | 0.8354 | |
| | 1.5185 | 9.0 | 39501 | 1.4103 | 0.8431 | 0.7496 | 0.8355 | 0.8363 | |
| | 1.5174 | 10.0 | 43890 | 1.4095 | 0.8431 | 0.7496 | 0.8358 | 0.8364 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
