---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: EN_mt5-base_10_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_10_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: 0.864
- Rouge2 Recall: 0.787
- Rouge2 Fmeasure: 0.8178

## 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: 21
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.1677        | 1.0   | 3085  | 0.1224          | 0.8269           | 0.7506        | 0.7803          |
| 0.1287        | 2.0   | 6170  | 0.1028          | 0.8458           | 0.7673        | 0.7988          |
| 0.1086        | 3.0   | 9255  | 0.0959          | 0.8511           | 0.7727        | 0.8042          |
| 0.0965        | 4.0   | 12340 | 0.0900          | 0.8543           | 0.777         | 0.808           |
| 0.089         | 5.0   | 15425 | 0.0883          | 0.8575           | 0.7802        | 0.8111          |
| 0.0809        | 6.0   | 18510 | 0.0866          | 0.8606           | 0.7834        | 0.8143          |
| 0.0771        | 7.0   | 21595 | 0.0860          | 0.8625           | 0.7851        | 0.8161          |
| 0.0745        | 8.0   | 24680 | 0.0855          | 0.8633           | 0.7862        | 0.8171          |
| 0.0715        | 9.0   | 27765 | 0.0848          | 0.8641           | 0.7869        | 0.8178          |
| 0.0702        | 10.0  | 30850 | 0.0849          | 0.864            | 0.787         | 0.8178          |


### Framework versions

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