---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: t5-base-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. -->

# t5-base-wikisql

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0822
- Rouge2 Precision: 0.8552
- Rouge2 Recall: 0.7632
- Rouge2 Fmeasure: 0.7994

## 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: 100
- eval_batch_size: 100
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.3772        | 1.0   | 648  | 0.1194          | 0.8164           | 0.7266        | 0.7619          |
| 0.1367        | 2.0   | 1296 | 0.1029          | 0.8322           | 0.7413        | 0.777           |
| 0.1184        | 3.0   | 1944 | 0.0960          | 0.839            | 0.7477        | 0.7837          |
| 0.0999        | 4.0   | 2592 | 0.0920          | 0.8447           | 0.7527        | 0.789           |
| 0.0943        | 5.0   | 3240 | 0.0884          | 0.8473           | 0.7549        | 0.7913          |
| 0.0886        | 6.0   | 3888 | 0.0868          | 0.8494           | 0.7568        | 0.7933          |
| 0.0821        | 7.0   | 4536 | 0.0852          | 0.8516           | 0.7588        | 0.7954          |
| 0.0792        | 8.0   | 5184 | 0.0845          | 0.8534           | 0.7605        | 0.7971          |
| 0.0765        | 9.0   | 5832 | 0.0836          | 0.8539           | 0.7622        | 0.7983          |
| 0.0741        | 10.0  | 6480 | 0.0825          | 0.8536           | 0.7616        | 0.7978          |
| 0.0708        | 11.0  | 7128 | 0.0827          | 0.8548           | 0.7625        | 0.7989          |
| 0.0693        | 12.0  | 7776 | 0.0822          | 0.8547           | 0.7629        | 0.799           |
| 0.0686        | 13.0  | 8424 | 0.0822          | 0.855            | 0.7631        | 0.7993          |
| 0.0672        | 14.0  | 9072 | 0.0823          | 0.8553           | 0.7633        | 0.7995          |
| 0.0664        | 15.0  | 9720 | 0.0822          | 0.8552           | 0.7632        | 0.7994          |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.1
- Datasets 2.14.7
- Tokenizers 0.13.3