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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_synthetic_cleaned_ar-to-en |
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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-finetuned_augmented_synthetic_cleaned_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: 0.7548 |
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- Bleu: 55.0936 |
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- Gen Len: 71.309 |
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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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| 1.0702 | 1.0 | 2085 | 0.9530 | 45.7652 | 72.802 | |
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| 0.8945 | 2.0 | 4170 | 0.8525 | 51.7618 | 70.845 | |
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| 0.8323 | 3.0 | 6255 | 0.8107 | 52.8262 | 71.099 | |
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| 0.7552 | 4.0 | 8340 | 0.7867 | 54.4572 | 71.243 | |
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| 0.7133 | 5.0 | 10425 | 0.7717 | 55.0749 | 71.354 | |
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| 0.6844 | 6.0 | 12510 | 0.7648 | 55.5344 | 71.477 | |
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| 0.6439 | 7.0 | 14595 | 0.7595 | 55.6968 | 70.883 | |
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| 0.6338 | 8.0 | 16680 | 0.7546 | 54.7998 | 71.414 | |
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| 0.6098 | 9.0 | 18765 | 0.7544 | 54.7933 | 71.567 | |
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| 0.6066 | 10.0 | 20850 | 0.7548 | 55.0936 | 71.309 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 1.13.1 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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