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--- |
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library_name: peft |
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language: |
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- multilingual |
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base_model: facebook/nllb-200-1.3B |
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tags: |
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- generated_from_trainer |
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datasets: |
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- elmamounedieye/agri_wol |
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metrics: |
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- bleu |
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model-index: |
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- name: nllb-200-1.3B-wol-fr |
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results: |
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- task: |
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type: translation |
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name: Translation |
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dataset: |
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name: elmamounedieye/agri_wol |
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type: elmamounedieye/agri_wol |
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metrics: |
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- type: bleu |
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value: 24.98280401781312 |
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name: Bleu |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# nllb-200-1.3B-wol-fr |
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This model is a fine-tuned version of [nllb-200-1.3B](https://huggingface.co/nllb-200-1.3B) on the elmamounedieye/agri_wol dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2740 |
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- Bleu: 24.9828 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:| |
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| 0.1963 | 1.0 | 1125 | 0.1795 | 20.8754 | |
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| 0.1055 | 2.0 | 2250 | 0.1807 | 21.3156 | |
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| 0.0422 | 3.0 | 3375 | 0.2031 | 22.9941 | |
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| 0.0216 | 4.0 | 4500 | 0.2324 | 22.2155 | |
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| 0.012 | 5.0 | 5625 | 0.2412 | 23.8844 | |
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| 0.0069 | 6.0 | 6750 | 0.2501 | 23.5372 | |
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| 0.0043 | 7.0 | 7875 | 0.2587 | 23.4568 | |
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| 0.0024 | 8.0 | 9000 | 0.2657 | 24.7322 | |
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| 0.001 | 9.0 | 10125 | 0.2683 | 24.9165 | |
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| 0.0006 | 10.0 | 11250 | 0.2740 | 24.9828 | |
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### Framework versions |
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- PEFT 0.14.0 |
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- Transformers 4.48.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.4.1 |
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- Tokenizers 0.21.1 |
