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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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datasets: |
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- opus_infopankki |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-ar-en-finetuned-ar-to-en |
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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: opus_infopankki |
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type: opus_infopankki |
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args: ar-en |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 51.6508 |
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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-ar-en-finetuned-ar-to-en |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the opus_infopankki dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7269 |
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- Bleu: 51.6508 |
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- Gen Len: 15.0812 |
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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: 2e-06 |
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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: 20 |
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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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| 1.4974 | 1.0 | 1587 | 1.3365 | 36.9061 | 15.3385 | |
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| 1.3768 | 2.0 | 3174 | 1.2139 | 39.5476 | 15.2079 | |
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| 1.2887 | 3.0 | 4761 | 1.1265 | 41.2771 | 15.2034 | |
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| 1.2076 | 4.0 | 6348 | 1.0556 | 42.6907 | 15.2687 | |
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| 1.1512 | 5.0 | 7935 | 0.9975 | 43.9498 | 15.2072 | |
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| 1.0797 | 6.0 | 9522 | 0.9491 | 45.224 | 15.2034 | |
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| 1.0499 | 7.0 | 11109 | 0.9101 | 46.1387 | 15.1651 | |
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| 1.0095 | 8.0 | 12696 | 0.8778 | 47.0586 | 15.1788 | |
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| 0.9833 | 9.0 | 14283 | 0.8501 | 47.8083 | 15.162 | |
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| 0.9601 | 10.0 | 15870 | 0.8267 | 48.5236 | 15.1784 | |
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| 0.9457 | 11.0 | 17457 | 0.8059 | 49.1717 | 15.095 | |
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| 0.9233 | 12.0 | 19044 | 0.7883 | 49.7742 | 15.1126 | |
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| 0.8964 | 13.0 | 20631 | 0.7736 | 50.2168 | 15.0917 | |
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| 0.8849 | 14.0 | 22218 | 0.7606 | 50.5583 | 15.0913 | |
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| 0.8751 | 15.0 | 23805 | 0.7504 | 50.8481 | 15.1108 | |
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| 0.858 | 16.0 | 25392 | 0.7417 | 51.1841 | 15.0989 | |
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| 0.8673 | 17.0 | 26979 | 0.7353 | 51.4271 | 15.0939 | |
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| 0.8548 | 18.0 | 28566 | 0.7306 | 51.535 | 15.0911 | |
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| 0.8483 | 19.0 | 30153 | 0.7279 | 51.6102 | 15.078 | |
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| 0.8614 | 20.0 | 31740 | 0.7269 | 51.6508 | 15.0812 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.7.1+cu110 |
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- Datasets 2.2.2 |
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- Tokenizers 0.12.1 |
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