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base_model: VietAI/vit5-large
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BaViT5_v2
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. -->
# BaViT5_v2
This model is a fine-tuned version of [VietAI/vit5-large](https://huggingface.co/VietAI/vit5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4562
- Sacrebleu: 15.4902
## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.5323 | 1.0 | 2966 | 0.4843 | 10.8807 |
| 0.4426 | 2.0 | 5932 | 0.4266 | 13.2481 |
| 0.3629 | 3.0 | 8898 | 0.4084 | 14.2709 |
| 0.3321 | 4.0 | 11864 | 0.4032 | 14.8016 |
| 0.286 | 5.0 | 14830 | 0.4061 | 15.1102 |
| 0.2528 | 6.0 | 17796 | 0.4160 | 15.2808 |
| 0.2235 | 7.0 | 20762 | 0.4270 | 15.4345 |
| 0.2018 | 8.0 | 23728 | 0.4400 | 15.4360 |
| 0.1856 | 9.0 | 26694 | 0.4562 | 15.4902 |
| 0.1639 | 10.0 | 29660 | 0.4705 | 15.4167 |
| 0.1565 | 11.0 | 32626 | 0.4886 | 15.4478 |
| 0.1392 | 12.0 | 35592 | 0.5035 | 15.4189 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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