readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - un_multi
  metrics:
  - bleu
  model-index:
  - name: opus-mt-en-ar-finetuned-en-to-ar
    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: 64.6767
  ---
  
  <!-- 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-en-to-ar
  
  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: 0.8133
  - Bleu: 64.6767
  - Gen Len: 17.595
  
  ## 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | No log        | 1.0   | 50   | 0.7710          | 64.3416 | 17.4    |
  | No log        | 2.0   | 100  | 0.7569          | 63.9546 | 17.465  |
  | No log        | 3.0   | 150  | 0.7570          | 64.7484 | 17.385  |
  | No log        | 4.0   | 200  | 0.7579          | 65.4073 | 17.305  |
  | No log        | 5.0   | 250  | 0.7624          | 64.8939 | 17.325  |
  | No log        | 6.0   | 300  | 0.7696          | 65.1257 | 17.45   |
  | No log        | 7.0   | 350  | 0.7747          | 65.527  | 17.395  |
  | No log        | 8.0   | 400  | 0.7791          | 65.1357 | 17.52   |
  | No log        | 9.0   | 450  | 0.7900          | 65.3812 | 17.415  |
  | 0.3982        | 10.0  | 500  | 0.7925          | 65.7346 | 17.39   |
  | 0.3982        | 11.0  | 550  | 0.7951          | 65.1267 | 17.62   |
  | 0.3982        | 12.0  | 600  | 0.8040          | 64.6874 | 17.495  |
  | 0.3982        | 13.0  | 650  | 0.8069          | 64.7788 | 17.52   |
  | 0.3982        | 14.0  | 700  | 0.8105          | 64.6701 | 17.585  |
  | 0.3982        | 15.0  | 750  | 0.8120          | 64.7111 | 17.58   |
  | 0.3982        | 16.0  | 800  | 0.8133          | 64.6767 | 17.595  |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  