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---
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
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