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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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- un_multi |
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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-2000instances-un_multi-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: un_multi |
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type: un_multi |
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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: 53.0137 |
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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-2000instances-un_multi-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 un_multi dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1873 |
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- Bleu: 53.0137 |
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- Meteor: 0.5005 |
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- Gen Len: 25.845 |
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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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| 0.6585 | 0.5 | 100 | 0.2085 | 52.5874 | 0.4969 | 25.485 | |
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| 0.1802 | 1.0 | 200 | 0.1788 | 52.9434 | 0.4982 | 25.1725 | |
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| 0.1501 | 1.5 | 300 | 0.1683 | 53.6994 | 0.5033 | 25.625 | |
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| 0.1454 | 2.0 | 400 | 0.1706 | 53.3946 | 0.5005 | 25.6675 | |
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| 0.1193 | 2.5 | 500 | 0.1774 | 53.2011 | 0.4982 | 25.58 | |
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| 0.1194 | 3.0 | 600 | 0.1741 | 53.8651 | 0.5026 | 25.5775 | |
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| 0.1002 | 3.5 | 700 | 0.1878 | 53.1332 | 0.5005 | 25.8975 | |
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| 0.0979 | 4.0 | 800 | 0.1881 | 52.5989 | 0.4974 | 25.485 | |
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| 0.0807 | 4.5 | 900 | 0.1873 | 53.0137 | 0.5005 | 25.845 | |
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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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