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---
base_model: vinai/bartpho-syllable
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BART_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. -->
# BART_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: 0.4390
- Sacrebleu: 6.4288
## 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.7274 | 1.0 | 468 | 0.6396 | 1.4512 |
| 0.628 | 2.0 | 936 | 0.5901 | 2.1680 |
| 0.5744 | 3.0 | 1404 | 0.5431 | 3.0785 |
| 0.5348 | 4.0 | 1872 | 0.5141 | 3.9172 |
| 0.5044 | 5.0 | 2340 | 0.4905 | 4.3428 |
| 0.4773 | 6.0 | 2808 | 0.4758 | 4.8562 |
| 0.4575 | 7.0 | 3276 | 0.4647 | 5.2799 |
| 0.4372 | 8.0 | 3744 | 0.4572 | 5.5700 |
| 0.429 | 9.0 | 4212 | 0.4499 | 5.8456 |
| 0.4118 | 10.0 | 4680 | 0.4455 | 6.0842 |
| 0.4056 | 11.0 | 5148 | 0.4424 | 6.2403 |
| 0.3924 | 12.0 | 5616 | 0.4403 | 6.2796 |
| 0.3858 | 13.0 | 6084 | 0.4396 | 6.3191 |
| 0.386 | 14.0 | 6552 | 0.4389 | 6.4120 |
| 0.3809 | 15.0 | 7020 | 0.4390 | 6.4288 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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