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update model card README.md
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README.md
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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-4000instances-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: 51.7715
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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-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: 0.1850
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- Bleu: 51.7715
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- Meteor: 0.5164
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- Gen Len: 25.5612
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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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| 0.6999 | 0.25 | 100 | 0.1959 | 50.1492 | 0.508 | 25.2788 |
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| 0.1994 | 0.5 | 200 | 0.1931 | 51.003 | 0.513 | 25.4038 |
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| 0.1863 | 0.75 | 300 | 0.1864 | 51.3268 | 0.5145 | 25.1675 |
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| 0.1826 | 1.0 | 400 | 0.1841 | 51.2507 | 0.513 | 25.2388 |
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| 0.1494 | 1.25 | 500 | 0.1840 | 51.4291 | 0.5159 | 25.4225 |
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| 0.1483 | 1.5 | 600 | 0.1839 | 51.2645 | 0.5126 | 25.395 |
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| 0.1547 | 1.75 | 700 | 0.1837 | 51.7589 | 0.5157 | 25.48 |
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| 0.1487 | 2.0 | 800 | 0.1845 | 51.896 | 0.5177 | 25.3988 |
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| 0.1235 | 2.25 | 900 | 0.1852 | 52.0583 | 0.5177 | 25.5212 |
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| 0.1164 | 2.5 | 1000 | 0.1850 | 51.7715 | 0.5164 | 25.5612 |
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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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