---
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: 1.5456
- Rouge1: 0.8237
- Rouge2: 0.7136
- Rougel: 0.8142
- Rougelsum: 0.8137

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 1.891         | 1.0   | 4389  | 1.7024          | 0.8289 | 0.7133 | 0.8163 | 0.8159    |
| 1.8333        | 2.0   | 8778  | 1.6619          | 0.8220 | 0.7113 | 0.8091 | 0.8089    |
| 1.7995        | 3.0   | 13167 | 1.6317          | 0.8213 | 0.7100 | 0.8102 | 0.8098    |
| 1.7632        | 4.0   | 17556 | 1.6076          | 0.8189 | 0.7074 | 0.8081 | 0.8076    |
| 1.7368        | 5.0   | 21945 | 1.5912          | 0.8219 | 0.7107 | 0.8106 | 0.8104    |
| 1.7121        | 6.0   | 26334 | 1.5715          | 0.8177 | 0.7052 | 0.8062 | 0.8060    |
| 1.7042        | 7.0   | 30723 | 1.5595          | 0.8210 | 0.7098 | 0.8104 | 0.8103    |
| 1.688         | 8.0   | 35112 | 1.5515          | 0.8220 | 0.7111 | 0.8118 | 0.8114    |
| 1.6647        | 9.0   | 39501 | 1.5482          | 0.8236 | 0.7122 | 0.8135 | 0.8131    |
| 1.6854        | 10.0  | 43890 | 1.5456          | 0.8237 | 0.7136 | 0.8142 | 0.8137    |


### Framework versions

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