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-1000instances-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: 64.0048
  ---
  
  <!-- 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-1000instances-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: 0.1294
  - Bleu: 64.0048
  - Meteor: 0.4903
  - Gen Len: 21.85
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 0.0489        | 1.0   | 100  | 0.1287          | 63.7573 | 0.4877 | 21.79   |
  | 0.0447        | 2.0   | 200  | 0.1293          | 63.8776 | 0.49   | 21.875  |
  | 0.0442        | 3.0   | 300  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  | 0.0433        | 4.0   | 400  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  | 0.0429        | 5.0   | 500  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  | 0.0435        | 6.0   | 600  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  | 0.0429        | 7.0   | 700  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  | 0.0426        | 8.0   | 800  | 0.1294          | 64.0048 | 0.4903 | 21.85   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  