---
base_model: IAmSkyDra/BARTBana_v4
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BARTBana_Translation_Replace_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_Replace_v0

This model is a fine-tuned version of [IAmSkyDra/BARTBana_v4](https://huggingface.co/IAmSkyDra/BARTBana_v4) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0029
- Sacrebleu: 20.9762

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|
| 0.0673        | 1.0   | 5881  | 0.0335          | 17.7815   |
| 0.0401        | 2.0   | 11762 | 0.0124          | 19.8597   |
| 0.0218        | 3.0   | 17643 | 0.0067          | 20.5145   |
| 0.0141        | 4.0   | 23524 | 0.0046          | 20.7775   |
| 0.0096        | 5.0   | 29405 | 0.0039          | 20.8673   |
| 0.007         | 6.0   | 35286 | 0.0035          | 20.9294   |
| 0.0051        | 7.0   | 41167 | 0.0032          | 20.9362   |
| 0.0043        | 8.0   | 47048 | 0.0031          | 20.9635   |
| 0.0032        | 9.0   | 52929 | 0.0030          | 20.9887   |
| 0.0028        | 10.0  | 58810 | 0.0029          | 20.9762   |


### Framework versions

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