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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_ar-to-en
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+ results: []
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+ ---
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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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+
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+ # nllb-200-distilled-600M-finetuned_augmented_synthetic_ar-to-en
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+
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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: 0.7501
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+ - Bleu: 62.4193
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+ - Gen Len: 64.586
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
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+ | 1.0564 | 1.0 | 2210 | 1.0374 | 45.431 | 65.406 |
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+ | 0.8998 | 2.0 | 4420 | 0.8975 | 52.6173 | 66.014 |
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+ | 0.7972 | 3.0 | 6630 | 0.8399 | 55.9624 | 65.357 |
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+ | 0.7451 | 4.0 | 8840 | 0.8021 | 57.3958 | 65.94 |
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+ | 0.6884 | 5.0 | 11050 | 0.7771 | 59.9589 | 65.367 |
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+ | 0.6742 | 6.0 | 13260 | 0.7648 | 61.0786 | 64.74 |
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+ | 0.6599 | 7.0 | 15470 | 0.7562 | 61.9442 | 64.694 |
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+ | 0.6168 | 8.0 | 17680 | 0.7530 | 62.0067 | 64.965 |
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+ | 0.6234 | 9.0 | 19890 | 0.7502 | 62.0721 | 64.888 |
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+ | 0.5948 | 10.0 | 22100 | 0.7501 | 62.4193 | 64.586 |
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+
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+
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+ ### Framework versions
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+
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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