readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - opus100
  metrics:
  - bleu
  model-index:
  - name: opus-mt-en-ar-evaluated-en-to-ar-1000instancesopus-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: 21.3028
  ---
  
  <!-- 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-1000instancesopus-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: 0.1421
  - Bleu: 21.3028
  - Meteor: 0.1285
  - Gen Len: 9.975
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 1.0508        | 1.0   | 100  | 0.1413          | 27.9009 | 0.1416 | 8.85    |
  | 0.1253        | 2.0   | 200  | 0.1372          | 23.11   | 0.1345 | 9.855   |
  | 0.1017        | 3.0   | 300  | 0.1390          | 21.7885 | 0.1364 | 9.97    |
  | 0.0868        | 4.0   | 400  | 0.1378          | 21.3889 | 0.1314 | 9.835   |
  | 0.0754        | 5.0   | 500  | 0.1398          | 22.198  | 0.132  | 9.675   |
  | 0.0667        | 6.0   | 600  | 0.1396          | 20.8645 | 0.1308 | 10.055  |
  | 0.0604        | 7.0   | 700  | 0.1408          | 20.289  | 0.1303 | 10.53   |
  | 0.0553        | 8.0   | 800  | 0.1414          | 21.7023 | 0.1293 | 10.005  |
  | 0.0518        | 9.0   | 900  | 0.1421          | 21.3028 | 0.1285 | 9.975   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  