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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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- opus100 |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-ar-evaluated-en-to-ar-4000instances-opus-leaningRate2e-05-batchSize8-11-action-1 |
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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: opus100 |
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type: opus100 |
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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: 26.8232 |
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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-en-ar-evaluated-en-to-ar-4000instances-opus-leaningRate2e-05-batchSize8-11-action-1 |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ar](https://huggingface.co/Helsinki-NLP/opus-mt-en-ar) on the opus100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1717 |
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- Bleu: 26.8232 |
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- Meteor: 0.172 |
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- Gen Len: 12.1288 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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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: 11 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Meteor | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:| |
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| 0.7364 | 0.25 | 100 | 0.1731 | 27.2753 | 0.1729 | 12.0887 | |
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| 0.2175 | 0.5 | 200 | 0.1731 | 27.2055 | 0.1722 | 11.5675 | |
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| 0.2193 | 0.75 | 300 | 0.1722 | 27.3277 | 0.1798 | 12.1325 | |
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| 0.2321 | 1.0 | 400 | 0.1750 | 27.5152 | 0.1762 | 11.925 | |
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| 0.1915 | 1.25 | 500 | 0.1690 | 27.5043 | 0.1751 | 11.9038 | |
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| 0.1794 | 1.5 | 600 | 0.1719 | 26.8607 | 0.1713 | 11.8138 | |
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| 0.1741 | 1.75 | 700 | 0.1725 | 26.974 | 0.1724 | 11.8462 | |
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| 0.1732 | 2.0 | 800 | 0.1717 | 26.8232 | 0.172 | 12.1288 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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