mn_nllb_1.3B_continue
This model is a fine-tuned version of facebook/nllb-200-distilled-1.3B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 7.1680
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: 5e-05
- train_batch_size: 40
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 160
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 7.0421 | 0.32 | 20 | 7.1684 |
| 7.0297 | 0.64 | 40 | 7.1668 |
| 7.0254 | 0.96 | 60 | 7.1666 |
| 7.0207 | 1.272 | 80 | 7.1669 |
| 7.0429 | 1.592 | 100 | 7.1672 |
| 7.0276 | 1.912 | 120 | 7.1675 |
| 7.0199 | 2.224 | 140 | 7.1675 |
| 7.0254 | 2.544 | 160 | 7.1678 |
| 7.0379 | 2.864 | 180 | 7.1678 |
| 7.0454 | 3.176 | 200 | 7.1680 |
| 7.0415 | 3.496 | 220 | 7.1680 |
| 7.0466 | 3.816 | 240 | 7.1680 |
Framework versions
- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Downloads last month
- 5
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
Ask for provider support
HF Inference deployability: The model has no pipeline_tag.
Model tree for Billyyy/mn_nllb_1.3B_continue
Base model
facebook/nllb-200-distilled-1.3B