---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-finetuned-acbsql
  results: []
metrics:
- rouge
pipeline_tag: text2text-generation
---

<!-- 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-acbsql

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the ACB SQL dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0699
- Rouge2 Precision: 0.6901
- Rouge2 Recall: 0.2546
- Rouge2 Fmeasure: 0.3639

## 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: 8
- eval_batch_size: 8
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 0.7623        | 1.0   | 155  | 0.3883          | 0.3621           | 0.1411        | 0.1985          |
| 0.3774        | 2.0   | 310  | 0.2040          | 0.5116           | 0.1845        | 0.2672          |
| 0.2693        | 3.0   | 465  | 0.1461          | 0.5462           | 0.1958        | 0.2847          |
| 0.2129        | 4.0   | 620  | 0.1147          | 0.5799           | 0.2135        | 0.3067          |
| 0.1807        | 5.0   | 775  | 0.0948          | 0.6145           | 0.2264        | 0.3242          |
| 0.1441        | 6.0   | 930  | 0.0847          | 0.6158           | 0.2298        | 0.3284          |
| 0.1361        | 7.0   | 1085 | 0.0785          | 0.6389           | 0.2358        | 0.3371          |
| 0.1268        | 8.0   | 1240 | 0.0733          | 0.6867           | 0.254         | 0.3628          |
| 0.1259        | 9.0   | 1395 | 0.0709          | 0.6875           | 0.2538        | 0.3626          |
| 0.1199        | 10.0  | 1550 | 0.0699          | 0.6901           | 0.2546        | 0.3639          |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3