readme: ---
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - wiki_lingua
  model-index:
  - name: mbart-large-50-finetuned-ar-wikilingua
    results: []
  ---
  
  <!-- 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. -->
  
  # mbart-large-50-finetuned-ar-wikilingua
  
  This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the wiki_lingua dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.0001
  - Rouge-1: 22.11
  - Rouge-2: 7.33
  - Rouge-l: 19.75
  - Gen Len: 59.4
  - Bertscore: 68.9
  
  ## 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: 1e-06
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 250
  - num_epochs: 8
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 5.2671        | 1.0   | 5111  | 4.6414          | 18.37   | 5.63    | 16.32   | 96.39   | 65.12     |
  | 4.5375        | 2.0   | 10222 | 4.3144          | 20.49   | 6.64    | 18.35   | 95.44   | 65.79     |
  | 4.308         | 3.0   | 15333 | 4.1592          | 21.16   | 7.09    | 18.85   | 67.75   | 67.65     |
  | 4.1562        | 4.0   | 20444 | 4.0812          | 21.59   | 7.31    | 19.42   | 68.66   | 68.02     |
  | 4.0749        | 5.0   | 25555 | 4.0409          | 21.99   | 7.42    | 19.82   | 66.4    | 68.05     |
  | 4.0271        | 6.0   | 30666 | 4.0183          | 22.04   | 7.42    | 19.64   | 56.88   | 68.95     |
  | 3.9991        | 7.0   | 35777 | 4.0042          | 22.05   | 7.35    | 19.71   | 55.75   | 68.94     |
  | 3.9833        | 8.0   | 40888 | 4.0001          | 22.12   | 7.39    | 19.78   | 55.72   | 69.0      |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  