---
base_model: google-t5/t5-small
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: ft-t5-small-on-airlineDB
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhuangc19/cs5740-sp24-assignment-4-Marcozc19/runs/gcggsyfe)
# ft-t5-small-on-airlineDB

This model is a fine-tuned version of [google t5-small](https://huggingface.co/google t5-small) on the custom airlineDB dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0992
- Sql Em: 0.0815
- Record Em: 0.1996
- Record F1: 0.1996

## 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: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sql Em | Record Em | Record F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:---------:|
| 0.1751        | 1.0   | 1057 | 0.0992          | 0.0815 | 0.1996    | 0.1996    |


### Framework versions

- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1