readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - un_multi
  metrics:
  - bleu
  model-index:
  - name: opus-mt-en-ar-evaluated-en-to-ar-2000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: un_multi
        type: un_multi
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 53.0137
  ---
  
  <!-- 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-2000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1
  
  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.
  It achieves the following results on the evaluation set:
  - Loss: 0.1873
  - Bleu: 53.0137
  - Meteor: 0.5005
  - Gen Len: 25.845
  
  ## 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 0.6585        | 0.5   | 100  | 0.2085          | 52.5874 | 0.4969 | 25.485  |
  | 0.1802        | 1.0   | 200  | 0.1788          | 52.9434 | 0.4982 | 25.1725 |
  | 0.1501        | 1.5   | 300  | 0.1683          | 53.6994 | 0.5033 | 25.625  |
  | 0.1454        | 2.0   | 400  | 0.1706          | 53.3946 | 0.5005 | 25.6675 |
  | 0.1193        | 2.5   | 500  | 0.1774          | 53.2011 | 0.4982 | 25.58   |
  | 0.1194        | 3.0   | 600  | 0.1741          | 53.8651 | 0.5026 | 25.5775 |
  | 0.1002        | 3.5   | 700  | 0.1878          | 53.1332 | 0.5005 | 25.8975 |
  | 0.0979        | 4.0   | 800  | 0.1881          | 52.5989 | 0.4974 | 25.485  |
  | 0.0807        | 4.5   | 900  | 0.1873          | 53.0137 | 0.5005 | 25.845  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  