readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - news_commentary
  metrics:
  - bleu
  model-index:
  - name: opus-mt-ar-en-finetuned-ar-to-en
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: news_commentary
        type: news_commentary
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 32.5327
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # opus-mt-ar-en-finetuned-ar-to-en
  
  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.
  It achieves the following results on the evaluation set:
  - Loss: 10.6102
  - Bleu: 32.5327
  - Gen Len: 56.234
  
  ## Model description
  
  More information needed
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  More information needed
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-09
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | No log        | 1.0   | 32   | 10.6112         | 32.5327 | 56.234  |
  | No log        | 2.0   | 64   | 10.6103         | 32.5327 | 56.234  |
  | No log        | 3.0   | 96   | 10.6102         | 32.5327 | 56.234  |
  
  
  ### Framework versions
  
  - Transformers 4.20.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  