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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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- news_commentary
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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: news_commentary
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type: news_commentary
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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: 36.3138
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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 news_commentary dataset.
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It achieves the following results on the evaluation set:
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- Loss: 9.7675
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- Bleu: 36.3138
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- Gen Len: 57.0
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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-09
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 3
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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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| No log | 1.0 | 4 | 9.7676 | 36.3138 | 57.0 |
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| No log | 2.0 | 8 | 9.7675 | 36.3138 | 57.0 |
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| No log | 3.0 | 12 | 9.7675 | 36.3138 | 57.0 |
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### Framework versions
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- Transformers 4.19.4
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- Pytorch 1.11.0+cu113
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- Datasets 2.3.2
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- Tokenizers 0.12.1
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