---
library_name: transformers
license: mit
base_model: vinai/bartpho-syllable
tags:
- generated_from_trainer
metrics:
- sacrebleu
model-index:
- name: BARTBana_Translation_Finetune_v0
  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_Translation_Finetune_v0

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: 2.4266
- Sacrebleu: 2.9607

## 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: 100
- eval_batch_size: 100
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.8315        | 1.0   | 429  | 0.6994          | 1.5712    |
| 0.7319        | 2.0   | 858  | 0.6374          | 2.6693    |
| 0.6676        | 3.0   | 1287 | 0.5882          | 4.0478    |
| 0.6199        | 4.0   | 1716 | 0.5549          | 4.4905    |
| 0.5912        | 5.0   | 2145 | 0.5353          | 5.0681    |
| 0.5583        | 6.0   | 2574 | 0.5219          | 5.7212    |
| 0.5488        | 7.0   | 3003 | 0.5117          | 6.1119    |
| 0.5294        | 8.0   | 3432 | 0.5052          | 5.9770    |
| 0.5227        | 9.0   | 3861 | 0.5020          | 6.2340    |
| 0.5113        | 10.0  | 4290 | 0.5011          | 6.2681    |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0