---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: EN_mt5-base_15_wikiSQL
  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. -->

# EN_mt5-base_15_wikiSQL

This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0849
- Rouge2 Precision: 0.8692
- Rouge2 Recall: 0.7928
- Rouge2 Fmeasure: 0.8234

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.1534        | 1.0   | 4049  | 0.1157          | 0.8319           | 0.756         | 0.7858          |
| 0.1204        | 2.0   | 8098  | 0.0980          | 0.8469           | 0.7706        | 0.8011          |
| 0.1006        | 3.0   | 12147 | 0.0926          | 0.855            | 0.7775        | 0.8086          |
| 0.0892        | 4.0   | 16196 | 0.0881          | 0.8579           | 0.7811        | 0.8119          |
| 0.0809        | 5.0   | 20245 | 0.0857          | 0.8605           | 0.7839        | 0.8145          |
| 0.0725        | 6.0   | 24294 | 0.0849          | 0.8643           | 0.787         | 0.8181          |
| 0.0672        | 7.0   | 28343 | 0.0841          | 0.8662           | 0.7889        | 0.8199          |
| 0.0628        | 8.0   | 32392 | 0.0847          | 0.8657           | 0.7895        | 0.82            |
| 0.0589        | 9.0   | 36441 | 0.0835          | 0.8676           | 0.7909        | 0.8216          |
| 0.0565        | 10.0  | 40490 | 0.0839          | 0.8685           | 0.7914        | 0.8223          |
| 0.0532        | 11.0  | 44539 | 0.0837          | 0.8689           | 0.7925        | 0.8231          |
| 0.051         | 12.0  | 48588 | 0.0844          | 0.8692           | 0.7927        | 0.8233          |
| 0.0504        | 13.0  | 52637 | 0.0848          | 0.869            | 0.7924        | 0.8231          |
| 0.0485        | 14.0  | 56686 | 0.0848          | 0.869            | 0.7928        | 0.8233          |
| 0.0479        | 15.0  | 60735 | 0.0849          | 0.8692           | 0.7928        | 0.8234          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3