readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - opus_infopankki
  metrics:
  - bleu
  model-index:
  - name: opus-mt-ar-en-finetuned-ar-to-en
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: opus_infopankki
        type: opus_infopankki
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 53.5086
  ---
  
  <!-- 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-ar-en-finetuned-ar-to-en
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the opus_infopankki dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7636
  - Bleu: 53.5086
  - Gen Len: 13.5728
  
  ## 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-06
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 30
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | No log        | 1.0   | 278  | 1.5114          | 35.2767 | 14.2084 |
  | 1.6677        | 2.0   | 556  | 1.4025          | 37.5243 | 14.0245 |
  | 1.6677        | 3.0   | 834  | 1.3223          | 39.4262 | 13.8101 |
  | 1.4743        | 4.0   | 1112 | 1.2567          | 40.7045 | 13.8533 |
  | 1.4743        | 5.0   | 1390 | 1.2001          | 41.8356 | 13.8083 |
  | 1.3428        | 6.0   | 1668 | 1.1504          | 43.2448 | 13.6958 |
  | 1.3428        | 7.0   | 1946 | 1.1072          | 44.177  | 13.6783 |
  | 1.2595        | 8.0   | 2224 | 1.0701          | 45.17   | 13.6587 |
  | 1.1829        | 9.0   | 2502 | 1.0345          | 45.9612 | 13.6706 |
  | 1.1829        | 10.0  | 2780 | 1.0042          | 46.9009 | 13.6236 |
  | 1.1188        | 11.0  | 3058 | 0.9760          | 47.7478 | 13.6205 |
  | 1.1188        | 12.0  | 3336 | 0.9505          | 48.3082 | 13.6283 |
  | 1.0735        | 13.0  | 3614 | 0.9270          | 48.9782 | 13.6203 |
  | 1.0735        | 14.0  | 3892 | 0.9060          | 49.5541 | 13.6311 |
  | 1.0269        | 15.0  | 4170 | 0.8869          | 49.9905 | 13.6222 |
  | 1.0269        | 16.0  | 4448 | 0.8700          | 50.4806 | 13.6047 |
  | 0.9983        | 17.0  | 4726 | 0.8538          | 50.9186 | 13.6159 |
  | 0.9647        | 18.0  | 5004 | 0.8398          | 51.3492 | 13.6146 |
  | 0.9647        | 19.0  | 5282 | 0.8271          | 51.7219 | 13.5275 |
  | 0.9398        | 20.0  | 5560 | 0.8156          | 52.0177 | 13.5756 |
  | 0.9398        | 21.0  | 5838 | 0.8053          | 52.3619 | 13.5807 |
  | 0.9206        | 22.0  | 6116 | 0.7963          | 52.6051 | 13.5652 |
  | 0.9206        | 23.0  | 6394 | 0.7885          | 52.8322 | 13.5669 |
  | 0.9012        | 24.0  | 6672 | 0.7818          | 52.9402 | 13.5701 |
  | 0.9012        | 25.0  | 6950 | 0.7762          | 53.1182 | 13.5695 |
  | 0.8965        | 26.0  | 7228 | 0.7717          | 53.1596 | 13.5612 |
  | 0.8836        | 27.0  | 7506 | 0.7681          | 53.3116 | 13.5719 |
  | 0.8836        | 28.0  | 7784 | 0.7656          | 53.4399 | 13.5758 |
  | 0.8777        | 29.0  | 8062 | 0.7642          | 53.4805 | 13.5737 |
  | 0.8777        | 30.0  | 8340 | 0.7636          | 53.5086 | 13.5728 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  