| --- |
| library_name: transformers |
| license: cc-by-nc-4.0 |
| base_model: facebook/nllb-200-distilled-600M |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: nllb-mulgi |
| 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. --> |
|
|
| # nllb-mulgi |
|
|
| This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6669 |
|
|
| ## 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: 32 |
| - eval_batch_size: 32 |
| - 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 |
| - lr_scheduler_warmup_steps: 200 |
| - num_epochs: 20 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:------:|:---------------:| |
| | 1.1832 | 1.0 | 5381 | 1.0899 | |
| | 0.9676 | 2.0 | 10762 | 0.9221 | |
| | 0.8225 | 3.0 | 16143 | 0.8334 | |
| | 0.7285 | 4.0 | 21524 | 0.7831 | |
| | 0.6536 | 5.0 | 26905 | 0.7447 | |
| | 0.5835 | 6.0 | 32286 | 0.7133 | |
| | 0.5209 | 7.0 | 37667 | 0.6919 | |
| | 0.4773 | 8.0 | 43048 | 0.6752 | |
| | 0.4316 | 9.0 | 48429 | 0.6662 | |
| | 0.3868 | 10.0 | 53810 | 0.6621 | |
| | 0.3783 | 11.0 | 59191 | 0.6568 | |
| | 0.3298 | 12.0 | 64572 | 0.6571 | |
| | 0.3217 | 13.0 | 69953 | 0.6558 | |
| | 0.2898 | 14.0 | 75334 | 0.6569 | |
| | 0.2803 | 15.0 | 80715 | 0.6606 | |
| | 0.2513 | 16.0 | 86096 | 0.6597 | |
| | 0.2418 | 17.0 | 91477 | 0.6644 | |
| | 0.2302 | 18.0 | 96858 | 0.6647 | |
| | 0.2235 | 19.0 | 102239 | 0.6665 | |
| | 0.2259 | 20.0 | 107620 | 0.6669 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.7.0 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 4.8.5 |
| - Tokenizers 0.22.2 |
| |
