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--- |
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license: apache-2.0 |
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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: opus-mt-ja-en-finetuned-ja-to-en_test |
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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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metric: |
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name: Bleu |
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type: bleu |
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value: 80.2723 |
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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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# opus-mt-ja-en-finetuned-ja-to-en_test |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ja-en](https://huggingface.co/Helsinki-NLP/opus-mt-ja-en) on an unkown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4737 |
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- Bleu: 80.2723 |
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- Gen Len: 16.5492 |
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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: 0.0002 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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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- mixed_precision_training: Native AMP |
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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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| 1.1237 | 1.0 | 247 | 0.6131 | 60.9383 | 16.4152 | |
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| 0.5395 | 2.0 | 494 | 0.5274 | 67.5705 | 16.2883 | |
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| 0.3584 | 3.0 | 741 | 0.5122 | 71.3098 | 16.3777 | |
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| 0.2563 | 4.0 | 988 | 0.4887 | 73.6639 | 16.401 | |
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| 0.138 | 5.0 | 1235 | 0.4796 | 76.7942 | 16.4873 | |
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| 0.0979 | 6.0 | 1482 | 0.4849 | 76.9404 | 16.6162 | |
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| 0.0792 | 7.0 | 1729 | 0.4806 | 78.9831 | 16.5442 | |
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| 0.0569 | 8.0 | 1976 | 0.4765 | 79.3461 | 16.4873 | |
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| 0.0299 | 9.0 | 2223 | 0.4751 | 79.7901 | 16.4863 | |
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| 0.0204 | 10.0 | 2470 | 0.4737 | 80.2723 | 16.5492 | |
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### Framework versions |
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- Transformers 4.9.1 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.10.2 |
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- Tokenizers 0.10.3 |
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