readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - opus100
  metrics:
  - bleu
  model-index:
  - name: opus-mt-en-ar-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: opus100
        type: opus100
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 26.2629
  ---
  
  <!-- 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-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize8-11epoch-3
  
  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 opus100 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1959
  - Bleu: 26.2629
  - Meteor: 0.1703
  - Gen Len: 11.0925
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 11
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 1.0519        | 0.5   | 100  | 0.1985          | 27.3525 | 0.1815 | 11.0725 |
  | 0.1947        | 1.0   | 200  | 0.1902          | 26.9728 | 0.1789 | 10.82   |
  | 0.1489        | 1.5   | 300  | 0.1910          | 27.7003 | 0.1811 | 10.975  |
  | 0.1665        | 2.0   | 400  | 0.1905          | 26.3739 | 0.1772 | 11.1075 |
  | 0.1321        | 2.5   | 500  | 0.1926          | 26.752  | 0.1772 | 10.975  |
  | 0.1271        | 3.0   | 600  | 0.1927          | 27.3663 | 0.1751 | 10.9725 |
  | 0.1105        | 3.5   | 700  | 0.1952          | 27.134  | 0.1738 | 10.9975 |
  | 0.109         | 4.0   | 800  | 0.1959          | 26.2629 | 0.1703 | 11.0925 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  