---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: t5-base-finetune-thai-to-romanized
  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-finetune-thai-to-romanized

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.5823
- Rouge1: 0.0533
- Rouge2: 0.0
- Rougel: 0.0543
- Rougelsum: 0.0541
- Gen Len: 11.3346

## 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: 2e-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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 6.2299        | 1.0   | 1500  | 6.0909          | 0.0    | 0.0    | 0.0    | 0.0       | 12.4211 |
| 6.0799        | 2.0   | 3000  | 5.9716          | 0.0058 | 0.0    | 0.006  | 0.0062    | 11.1185 |
| 5.9595        | 3.0   | 4500  | 5.9016          | 0.0081 | 0.0    | 0.0082 | 0.008     | 12.1465 |
| 5.8423        | 4.0   | 6000  | 5.7665          | 0.0364 | 0.0017 | 0.0367 | 0.0365    | 11.6982 |
| 5.7915        | 5.0   | 7500  | 5.7470          | 0.0441 | 0.0013 | 0.0445 | 0.0442    | 10.7897 |
| 5.7114        | 6.0   | 9000  | 5.6844          | 0.0472 | 0.0013 | 0.0476 | 0.0478    | 10.5441 |
| 5.6555        | 7.0   | 10500 | 5.6416          | 0.0549 | 0.0013 | 0.0552 | 0.0552    | 11.1098 |
| 5.6362        | 8.0   | 12000 | 5.6036          | 0.0493 | 0.0013 | 0.0501 | 0.0498    | 12.7922 |
| 5.5941        | 9.0   | 13500 | 5.5895          | 0.0535 | 0.0    | 0.0544 | 0.0542    | 11.5989 |
| 5.569         | 10.0  | 15000 | 5.5823          | 0.0533 | 0.0    | 0.0543 | 0.0541    | 11.3346 |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2