| | --- |
| | 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: 0.6352 |
| | - Rouge1: 0.8954 |
| | - Rouge2: 0.8464 |
| | - Rougel: 0.8923 |
| | - Rougelsum: 0.8922 |
| |
|
| | ## 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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:| |
| | | 0.8096 | 1.0 | 4389 | 0.6355 | 0.8975 | 0.8473 | 0.8940 | 0.8941 | |
| | | 0.7862 | 2.0 | 8778 | 0.6368 | 0.8972 | 0.8489 | 0.8938 | 0.8939 | |
| | | 0.7791 | 3.0 | 13167 | 0.6368 | 0.8963 | 0.8469 | 0.8927 | 0.8925 | |
| | | 0.7792 | 4.0 | 17556 | 0.6369 | 0.8954 | 0.8464 | 0.8919 | 0.8917 | |
| | | 0.7859 | 5.0 | 21945 | 0.6356 | 0.8949 | 0.8448 | 0.8914 | 0.8912 | |
| | | 0.7812 | 6.0 | 26334 | 0.6354 | 0.8962 | 0.8468 | 0.8928 | 0.8928 | |
| | | 0.7813 | 7.0 | 30723 | 0.6359 | 0.8950 | 0.8451 | 0.8916 | 0.8913 | |
| | | 0.7695 | 8.0 | 35112 | 0.6356 | 0.8947 | 0.8458 | 0.8916 | 0.8915 | |
| | | 0.7842 | 9.0 | 39501 | 0.6350 | 0.8950 | 0.8463 | 0.8920 | 0.8918 | |
| | | 0.7724 | 10.0 | 43890 | 0.6352 | 0.8954 | 0.8464 | 0.8923 | 0.8922 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.38.2 |
| | - Pytorch 2.2.1+cu121 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
| |
|
