---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: google/flan-t5-small
model-index:
- name: flan-t5-small-sql
  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. -->

# flan-t5-small-sql

This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3584

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1000.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.3349        | 62.5   | 500  | 0.2107          |
| 0.1147        | 125.0  | 1000 | 0.2410          |
| 0.071         | 187.5  | 1500 | 0.2687          |
| 0.0502        | 250.0  | 2000 | 0.2901          |
| 0.0373        | 312.5  | 2500 | 0.3033          |
| 0.0301        | 375.0  | 3000 | 0.3141          |
| 0.025         | 437.5  | 3500 | 0.3235          |
| 0.0212        | 500.0  | 4000 | 0.3312          |
| 0.0187        | 562.5  | 4500 | 0.3404          |
| 0.017         | 625.0  | 5000 | 0.3371          |
| 0.0148        | 687.5  | 5500 | 0.3466          |
| 0.0139        | 750.0  | 6000 | 0.3480          |
| 0.0124        | 812.5  | 6500 | 0.3552          |
| 0.0118        | 875.0  | 7000 | 0.3594          |
| 0.0112        | 937.5  | 7500 | 0.3581          |
| 0.0106        | 1000.0 | 8000 | 0.3584          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.38.0
- Pytorch 2.1.2+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2