| --- |
| library_name: transformers |
| license: mit |
| base_model: IAmSkyDra/BARTBana |
| tags: |
| - generated_from_trainer |
| metrics: |
| - sacrebleu |
| model-index: |
| - name: BARTBana_Translation_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. --> |
|
|
| # BARTBana_Translation_v2 |
|
|
| This model is a fine-tuned version of [IAmSkyDra/BARTBana](https://huggingface.co/IAmSkyDra/BARTBana) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4520 |
| - Sacrebleu: 11.7352 |
|
|
| ## 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: 15 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Sacrebleu | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:| |
| | 0.695 | 1.0 | 742 | 0.6021 | 6.3321 | |
| | 0.5976 | 2.0 | 1484 | 0.5291 | 8.6429 | |
| | 0.5171 | 3.0 | 2226 | 0.4958 | 9.7101 | |
| | 0.4919 | 4.0 | 2968 | 0.4781 | 10.3323 | |
| | 0.4556 | 5.0 | 3710 | 0.4680 | 10.7812 | |
| | 0.4387 | 6.0 | 4452 | 0.4577 | 10.8965 | |
| | 0.4095 | 7.0 | 5194 | 0.4538 | 11.1963 | |
| | 0.3924 | 8.0 | 5936 | 0.4499 | 11.2119 | |
| | 0.3815 | 9.0 | 6678 | 0.4486 | 11.4155 | |
| | 0.3647 | 10.0 | 7420 | 0.4468 | 11.4443 | |
| | 0.3525 | 11.0 | 8162 | 0.4479 | 11.5941 | |
| | 0.3435 | 12.0 | 8904 | 0.4489 | 11.5933 | |
| | 0.3349 | 13.0 | 9646 | 0.4500 | 11.7211 | |
| | 0.3289 | 14.0 | 10388 | 0.4508 | 11.7113 | |
| | 0.3202 | 15.0 | 11130 | 0.4520 | 11.7352 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.48.0 |
| - Pytorch 2.5.1+cu124 |
| - Datasets 3.2.0 |
| - Tokenizers 0.21.0 |
|
|
