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--- |
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license: cc-by-nc-4.0 |
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tags: |
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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-600m-swh_Latn-to-eng_Latn |
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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-600m-swh_Latn-to-eng_Latn |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2490 |
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- Bleu: 31.1907 |
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- Gen Len: 34.464 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 7 |
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- total_train_batch_size: 14 |
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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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- training_steps: 8000 |
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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 | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
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| 2.8224 | 0.41 | 500 | 2.3121 | 8.4908 | 34.136 | |
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| 2.1656 | 0.83 | 1000 | 1.9451 | 14.9983 | 33.604 | |
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| 1.885 | 1.24 | 1500 | 1.7385 | 18.7049 | 33.928 | |
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| 1.6922 | 1.66 | 2000 | 1.6102 | 21.7399 | 33.648 | |
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| 1.5693 | 2.07 | 2500 | 1.5175 | 23.2299 | 34.912 | |
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| 1.4695 | 2.49 | 3000 | 1.4552 | 24.8572 | 32.612 | |
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| 1.4195 | 2.9 | 3500 | 1.3948 | 26.3956 | 33.56 | |
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| 1.3413 | 3.32 | 4000 | 1.3564 | 27.2599 | 32.824 | |
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| 1.3094 | 3.73 | 4500 | 1.3263 | 27.9728 | 33.42 | |
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| 1.2748 | 4.15 | 5000 | 1.3044 | 28.8956 | 33.56 | |
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| 1.227 | 4.56 | 5500 | 1.2844 | 29.8314 | 33.552 | |
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| 1.2255 | 4.97 | 6000 | 1.2692 | 30.4411 | 33.716 | |
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| 1.191 | 5.39 | 6500 | 1.2611 | 31.1336 | 34.432 | |
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| 1.1842 | 5.8 | 7000 | 1.2542 | 30.8819 | 33.716 | |
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| 1.1712 | 6.22 | 7500 | 1.2506 | 31.528 | 33.768 | |
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| 1.1606 | 6.63 | 8000 | 1.2490 | 31.1907 | 34.464 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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