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update model card README.md

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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-vie_Latn-to-eng_Latn
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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-600m-vie_Latn-to-eng_Latn
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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 the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1189
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+ - Bleu: 36.6767
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+ - Gen Len: 47.504
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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: 3
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+ - eval_batch_size: 3
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_batch_size: 24
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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: 10000
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+ - mixed_precision_training: Native AMP
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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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+ | 1.9294 | 2.24 | 1000 | 1.5970 | 23.6201 | 48.1 |
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+ | 1.4 | 4.47 | 2000 | 1.3216 | 28.9526 | 45.156 |
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+ | 1.2071 | 6.71 | 3000 | 1.2245 | 32.5538 | 46.576 |
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+ | 1.0893 | 8.95 | 4000 | 1.1720 | 34.265 | 46.052 |
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+ | 1.0064 | 11.19 | 5000 | 1.1497 | 34.9249 | 46.508 |
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+ | 0.9562 | 13.42 | 6000 | 1.1331 | 36.4619 | 47.244 |
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+ | 0.9183 | 15.66 | 7000 | 1.1247 | 36.4723 | 47.26 |
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+ | 0.8858 | 17.9 | 8000 | 1.1198 | 36.7058 | 47.376 |
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+ | 0.8651 | 20.13 | 9000 | 1.1201 | 36.7897 | 47.496 |
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+ | 0.8546 | 22.37 | 10000 | 1.1189 | 36.6767 | 47.504 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.22.1
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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