---
base_model: IAmSkyDra/BARTBana_v5
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BARTBana_Translation_v5
  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_v5

This model is a fine-tuned version of [IAmSkyDra/BARTBana_v5](https://huggingface.co/IAmSkyDra/BARTBana_v5) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5493
- Sacrebleu: 8.2109

## 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: 64
- eval_batch_size: 64
- 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Sacrebleu |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.8112        | 1.0   | 742   | 0.7198          | 1.9252    |
| 0.7466        | 2.0   | 1484  | 0.6679          | 3.0362    |
| 0.6719        | 3.0   | 2226  | 0.6347          | 4.1068    |
| 0.6522        | 4.0   | 2968  | 0.6128          | 4.9362    |
| 0.6111        | 5.0   | 3710  | 0.5966          | 5.4351    |
| 0.5941        | 6.0   | 4452  | 0.5835          | 5.9868    |
| 0.5613        | 7.0   | 5194  | 0.5753          | 6.4039    |
| 0.5428        | 8.0   | 5936  | 0.5684          | 6.6599    |
| 0.5315        | 9.0   | 6678  | 0.5607          | 6.8644    |
| 0.5132        | 10.0  | 7420  | 0.5572          | 7.1633    |
| 0.4958        | 11.0  | 8162  | 0.5534          | 7.2500    |
| 0.4849        | 12.0  | 8904  | 0.5544          | 7.5064    |
| 0.4731        | 13.0  | 9646  | 0.5502          | 7.6249    |
| 0.4624        | 14.0  | 10388 | 0.5508          | 7.5880    |
| 0.4482        | 15.0  | 11130 | 0.5503          | 7.7981    |
| 0.4434        | 16.0  | 11872 | 0.5488          | 7.9009    |
| 0.43          | 17.0  | 12614 | 0.5488          | 7.8955    |
| 0.425         | 18.0  | 13356 | 0.5500          | 8.0053    |
| 0.4177        | 19.0  | 14098 | 0.5460          | 8.1097    |
| 0.4121        | 20.0  | 14840 | 0.5489          | 8.0999    |
| 0.4124        | 21.0  | 15582 | 0.5498          | 8.1294    |
| 0.4046        | 22.0  | 16324 | 0.5492          | 8.2079    |
| 0.4011        | 23.0  | 17066 | 0.5493          | 8.2109    |
| 0.4049        | 24.0  | 17808 | 0.5511          | 8.1965    |
| 0.3964        | 25.0  | 18550 | 0.5513          | 8.1733    |


### Framework versions

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