---
base_model: vinai/bartpho-syllable
library_name: transformers
license: mit
tags:
- generated_from_trainer
model-index:
- name: BARTBana_Before
  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. -->

# BARTBana_Before

This model is a fine-tuned version of [vinai/bartpho-syllable](https://huggingface.co/vinai/bartpho-syllable) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4830

## 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: 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: 15.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.2274        | 1.0   | 677   | 3.7284          |
| 3.8195        | 2.0   | 1354  | 2.6138          |
| 2.5688        | 3.0   | 2031  | 2.2841          |
| 2.3493        | 4.0   | 2708  | 2.0703          |
| 2.187         | 5.0   | 3385  | 1.9266          |
| 1.9879        | 6.0   | 4062  | 1.8244          |
| 1.9203        | 7.0   | 4739  | 1.7417          |
| 1.8537        | 8.0   | 5416  | 1.6667          |
| 1.7535        | 9.0   | 6093  | 1.6369          |
| 1.7223        | 10.0  | 6770  | 1.6014          |
| 1.6815        | 11.0  | 7447  | 1.5564          |
| 1.6334        | 12.0  | 8124  | 1.5452          |
| 1.6219        | 13.0  | 8801  | 1.5036          |
| 1.589         | 14.0  | 9478  | 1.5131          |
| 1.5717        | 15.0  | 10155 | 1.5005          |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0