---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- wikisql
model-index:
- name: t5-small-finetuned-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-small-finetuned-wikisql

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the wikisql dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1247
- Model Preparation Time: 0.0049
- Rouge1 Precision: 0.873
- Rouge1 Recall: 0.873
- Rouge1 Fmeasure: 0.873
- Rouge2 Precision: 0.7718
- Rouge2 Recall: 0.7718
- Rouge2 Fmeasure: 0.7718
- Rougel Precision: 0.86
- Rougel Recall: 0.86
- Rougel Fmeasure: 0.86

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Model Preparation Time | Rouge1 Precision | Rouge1 Recall | Rouge1 Fmeasure | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Rougel Precision | Rougel Recall | Rougel Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.1942        | 1.0   | 4049  | 0.1561          | 0.0049                 | 0.8629           | 0.8629        | 0.8629          | 0.7471           | 0.7471        | 0.7471          | 0.8471           | 0.8471        | 0.8471          |
| 0.1646        | 2.0   | 8098  | 0.1373          | 0.0049                 | 0.8697           | 0.8697        | 0.8697          | 0.763            | 0.763         | 0.763           | 0.8555           | 0.8555        | 0.8555          |
| 0.147         | 3.0   | 12147 | 0.1297          | 0.0049                 | 0.8723           | 0.8723        | 0.8723          | 0.7684           | 0.7684        | 0.7684          | 0.8588           | 0.8588        | 0.8588          |
| 0.1412        | 4.0   | 16196 | 0.1256          | 0.0049                 | 0.8725           | 0.8725        | 0.8725          | 0.7712           | 0.7712        | 0.7712          | 0.8595           | 0.8595        | 0.8595          |
| 0.14          | 5.0   | 20245 | 0.1247          | 0.0049                 | 0.873            | 0.873         | 0.873           | 0.7718           | 0.7718        | 0.7718          | 0.86             | 0.86          | 0.86            |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0