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--- |
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language: |
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- multilingual |
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- pt |
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base_model: /content/opus-mt-en-mul |
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tags: |
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- generated_from_trainer |
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datasets: |
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- tiagoblima/translation-pt-indigenouns |
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metrics: |
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- bleu |
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model-index: |
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- name: tst-gun-gub-pt |
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results: |
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- task: |
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name: Translation |
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type: translation |
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dataset: |
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name: tiagoblima/translation-pt-indigenouns |
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type: tiagoblima/translation-pt-indigenouns |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 8.5368 |
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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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# tst-gun-gub-pt |
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This model is a fine-tuned version of [/content/opus-mt-en-mul](https://huggingface.co.//content/opus-mt-en-mul) on the tiagoblima/translation-pt-indigenouns dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8158 |
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- Bleu: 8.5368 |
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- Gen Len: 59.24 |
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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: 16 |
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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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- num_epochs: 3.0 |
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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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| 2.4421 | 0.29 | 4000 | 2.5285 | 3.3785 | 68.48 | |
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| 2.1667 | 0.59 | 8000 | 2.3018 | 4.5883 | 58.6 | |
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| 2.0255 | 0.88 | 12000 | 2.1290 | 5.1052 | 67.3 | |
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| 1.8995 | 1.18 | 16000 | 2.0535 | 7.8429 | 55.48 | |
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| 1.8322 | 1.47 | 20000 | 1.9960 | 7.2663 | 58.24 | |
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| 1.7868 | 1.77 | 24000 | 1.9224 | 7.0981 | 66.34 | |
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| 1.7012 | 2.06 | 28000 | 1.8869 | 7.5657 | 60.3 | |
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| 1.6773 | 2.36 | 32000 | 1.8613 | 7.9888 | 61.18 | |
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| 1.6631 | 2.65 | 36000 | 1.8354 | 8.0862 | 60.5 | |
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| 1.6379 | 2.94 | 40000 | 1.8158 | 8.4077 | 60.18 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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