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--- |
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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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- 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-finetuned_augmented_MT_ar-to-en |
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results: [] |
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pipeline_tag: translation |
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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-finetuned_augmented_MT_ar-to-en |
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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: 0.7204 |
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- Bleu: 64.0069 |
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- Gen Len: 65.416 |
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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: 8 |
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- eval_batch_size: 8 |
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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: 10 |
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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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| 1.0557 | 1.0 | 2195 | 0.9595 | 49.4737 | 68.419 | |
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| 0.9159 | 2.0 | 4390 | 0.8377 | 55.3155 | 67.247 | |
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| 0.8074 | 3.0 | 6585 | 0.7898 | 58.8942 | 66.102 | |
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| 0.7441 | 4.0 | 8780 | 0.7559 | 60.8889 | 65.846 | |
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| 0.6963 | 5.0 | 10975 | 0.7395 | 61.3835 | 66.31 | |
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| 0.641 | 6.0 | 13170 | 0.7320 | 62.4226 | 65.985 | |
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| 0.6106 | 7.0 | 15365 | 0.7257 | 62.8285 | 65.505 | |
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| 0.5826 | 8.0 | 17560 | 0.7212 | 63.5372 | 65.474 | |
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| 0.5766 | 9.0 | 19755 | 0.7195 | 63.8042 | 65.525 | |
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| 0.5533 | 10.0 | 21950 | 0.7204 | 64.0069 | 65.416 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
