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--- |
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library_name: transformers |
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license: cc-by-nc-4.0 |
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base_model: facebook/nllb-200-distilled-600M |
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tags: |
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- translation |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: nllb-200-distilled-600M-mt-finetuned-zindi-dyu-to-fr |
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results: [] |
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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-distilled-600M-mt-finetuned-zindi-dyu-to-fr |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2584 |
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- Bleu: 6.4075 |
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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: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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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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| 3.1707 | 0.1575 | 20 | 2.7356 | 4.8084 | |
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| 2.9074 | 0.3150 | 40 | 2.5883 | 5.0141 | |
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| 2.7168 | 0.4724 | 60 | 2.4902 | 5.5785 | |
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| 2.6912 | 0.6299 | 80 | 2.4154 | 5.7743 | |
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| 2.6062 | 0.7874 | 100 | 2.3742 | 6.0010 | |
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| 2.5794 | 0.9449 | 120 | 2.3480 | 6.1354 | |
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| 2.4634 | 1.1024 | 140 | 2.3314 | 5.9899 | |
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| 2.5055 | 1.2598 | 160 | 2.3167 | 6.1080 | |
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| 2.5062 | 1.4173 | 180 | 2.3032 | 6.3784 | |
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| 2.4771 | 1.5748 | 200 | 2.2944 | 6.4510 | |
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| 2.4284 | 1.7323 | 220 | 2.2854 | 6.2883 | |
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| 2.4423 | 1.8898 | 240 | 2.2783 | 6.5036 | |
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| 2.3202 | 2.0472 | 260 | 2.2730 | 6.4039 | |
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| 2.3855 | 2.2047 | 280 | 2.2701 | 6.2921 | |
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| 2.4292 | 2.3622 | 300 | 2.2658 | 6.3025 | |
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| 2.3678 | 2.5197 | 320 | 2.2626 | 6.2881 | |
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| 2.4158 | 2.6772 | 340 | 2.2600 | 6.3684 | |
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| 2.351 | 2.8346 | 360 | 2.2588 | 6.2852 | |
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| 2.3755 | 2.9921 | 380 | 2.2584 | 6.2819 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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