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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-1000instances-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: 64.0048
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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-1000instances-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: 0.1294
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- Bleu: 64.0048
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- Meteor: 0.4903
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- Gen Len: 21.85
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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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| 0.0489 | 1.0 | 100 | 0.1287 | 63.7573 | 0.4877 | 21.79 |
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| 0.0447 | 2.0 | 200 | 0.1293 | 63.8776 | 0.49 | 21.875 |
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| 0.0442 | 3.0 | 300 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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| 0.0433 | 4.0 | 400 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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| 0.0429 | 5.0 | 500 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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| 0.0435 | 6.0 | 600 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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| 0.0429 | 7.0 | 700 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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| 0.0426 | 8.0 | 800 | 0.1294 | 64.0048 | 0.4903 | 21.85 |
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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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