---
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    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2