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---
base_model: IAmSkyDra/BARTBana_v4
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BARTBana_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. -->
# BARTBana_Translation_Finetune_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: 0.4295
- Sacrebleu: 7.5050
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.6831 | 1.0 | 468 | 0.5818 | 3.2556 |
| 0.566 | 2.0 | 936 | 0.5188 | 4.6548 |
| 0.5127 | 3.0 | 1404 | 0.4878 | 5.3508 |
| 0.4804 | 4.0 | 1872 | 0.4683 | 5.8657 |
| 0.4558 | 5.0 | 2340 | 0.4551 | 6.2975 |
| 0.433 | 6.0 | 2808 | 0.4450 | 6.4311 |
| 0.4146 | 7.0 | 3276 | 0.4420 | 6.7296 |
| 0.3969 | 8.0 | 3744 | 0.4365 | 6.9791 |
| 0.3911 | 9.0 | 4212 | 0.4332 | 7.1487 |
| 0.3742 | 10.0 | 4680 | 0.4302 | 7.2803 |
| 0.3686 | 11.0 | 5148 | 0.4292 | 7.3851 |
| 0.3568 | 12.0 | 5616 | 0.4296 | 7.4003 |
| 0.3505 | 13.0 | 6084 | 0.4292 | 7.4202 |
| 0.3503 | 14.0 | 6552 | 0.4289 | 7.4984 |
| 0.3453 | 15.0 | 7020 | 0.4295 | 7.5050 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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