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-4000instances-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: 51.7715
  ---
  
  <!-- 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-4000instances-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: 0.1850
  - Bleu: 51.7715
  - Meteor: 0.5164
  - Gen Len: 25.5612
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 0.6999        | 0.25  | 100  | 0.1959          | 50.1492 | 0.508  | 25.2788 |
  | 0.1994        | 0.5   | 200  | 0.1931          | 51.003  | 0.513  | 25.4038 |
  | 0.1863        | 0.75  | 300  | 0.1864          | 51.3268 | 0.5145 | 25.1675 |
  | 0.1826        | 1.0   | 400  | 0.1841          | 51.2507 | 0.513  | 25.2388 |
  | 0.1494        | 1.25  | 500  | 0.1840          | 51.4291 | 0.5159 | 25.4225 |
  | 0.1483        | 1.5   | 600  | 0.1839          | 51.2645 | 0.5126 | 25.395  |
  | 0.1547        | 1.75  | 700  | 0.1837          | 51.7589 | 0.5157 | 25.48   |
  | 0.1487        | 2.0   | 800  | 0.1845          | 51.896  | 0.5177 | 25.3988 |
  | 0.1235        | 2.25  | 900  | 0.1852          | 52.0583 | 0.5177 | 25.5212 |
  | 0.1164        | 2.5   | 1000 | 0.1850          | 51.7715 | 0.5164 | 25.5612 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  