---
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