File size: 2,091 Bytes
407607f 3317ef3 407607f 3317ef3 407607f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
---
base_model: IAmSkyDra/BARTBana_v3
library_name: transformers
license: mit
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: BARTBana_Translation_v3
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_v3
This model is a fine-tuned version of [IAmSkyDra/BARTBana_v3](https://huggingface.co/IAmSkyDra/BARTBana_v3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4571
- Sacrebleu: 11.0566
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu |
|:-------------:|:-----:|:----:|:---------------:|:---------:|
| 0.7013 | 1.0 | 742 | 0.6063 | 6.2147 |
| 0.6067 | 2.0 | 1484 | 0.5359 | 8.3509 |
| 0.5273 | 3.0 | 2226 | 0.5025 | 9.5105 |
| 0.5043 | 4.0 | 2968 | 0.4846 | 10.0064 |
| 0.4699 | 5.0 | 3710 | 0.4747 | 10.4437 |
| 0.4558 | 6.0 | 4452 | 0.4658 | 10.6266 |
| 0.4296 | 7.0 | 5194 | 0.4613 | 10.8692 |
| 0.417 | 8.0 | 5936 | 0.4582 | 10.9131 |
| 0.4127 | 9.0 | 6678 | 0.4567 | 11.0361 |
| 0.4021 | 10.0 | 7420 | 0.4571 | 11.0566 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|