readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - syssr_en_ar
  metrics:
  - bleu
  model-index:
  - name: opus-mt-en-ar-finetuned-dummyData-10-10-ar-to-en
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: syssr_en_ar
        type: syssr_en_ar
        args: default
      metrics:
      - name: Bleu
        type: bleu
        value: 7.9946
  ---
  
  <!-- 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-en-ar-finetuned-dummyData-10-10-ar-to-en
  
  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 syssr_en_ar dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2046
  - Bleu: 7.9946
  - Gen Len: 20.0
  
  ## 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-05
  - 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
  | No log        | 1.0   | 1    | 1.2038          | 7.9946 | 20.0    |
  | No log        | 2.0   | 2    | 1.2038          | 7.9946 | 20.0    |
  | No log        | 3.0   | 3    | 1.2038          | 7.9946 | 20.0    |
  | No log        | 4.0   | 4    | 1.2036          | 7.9946 | 20.0    |
  | No log        | 5.0   | 5    | 1.2046          | 7.9946 | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  