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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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datasets: |
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- nusatranslation_mt |
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metrics: |
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- sacrebleu |
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model-index: |
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- name: ind-to-bbc-nmt-v5 |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: nusatranslation_mt |
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type: nusatranslation_mt |
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config: nusatranslation_mt_btk_ind_source |
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split: test |
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args: nusatranslation_mt_btk_ind_source |
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metrics: |
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- name: Sacrebleu |
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type: sacrebleu |
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value: 31.266 |
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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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# ind-to-bbc-nmt-v5 |
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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 nusatranslation_mt dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1894 |
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- Sacrebleu: 31.266 |
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- Gen Len: 44.965 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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 | Sacrebleu | Gen Len | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:| |
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| 3.6651 | 1.0 | 1650 | 1.4838 | 26.4515 | 46.9715 | |
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| 1.3236 | 2.0 | 3300 | 1.2132 | 30.7977 | 45.688 | |
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| 1.0377 | 3.0 | 4950 | 1.1590 | 31.5249 | 45.2095 | |
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| 0.871 | 4.0 | 6600 | 1.1329 | 31.7139 | 44.965 | |
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| 0.7493 | 5.0 | 8250 | 1.1319 | 31.3062 | 45.139 | |
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| 0.6536 | 6.0 | 9900 | 1.1331 | 30.8031 | 45.242 | |
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| 0.5772 | 7.0 | 11550 | 1.1492 | 31.1586 | 45.1815 | |
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| 0.5195 | 8.0 | 13200 | 1.1684 | 31.0977 | 45.019 | |
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| 0.4763 | 9.0 | 14850 | 1.1798 | 31.2488 | 44.8915 | |
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| 0.4478 | 10.0 | 16500 | 1.1894 | 31.266 | 44.965 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.19.1 |
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