readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - xlsum
  model-index:
  - name: AraBART-finetune-ar-xlsum
    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. -->
  
  # AraBART-finetuned-ar
  
  This model is a fine-tuned version of [moussaKam/AraBART](https://huggingface.co/moussaKam/AraBART) on the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.7449
  - Rouge-1: 31.08
  - Rouge-2: 14.68
  - Rouge-l: 27.36
  - Gen Len: 19.64
  - Bertscore: 73.86
  
  ## 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: 5e-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
  - lr_scheduler_warmup_steps: 250
  - num_epochs: 10
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 4.4318        | 1.0   | 2345  | 3.7996          | 28.93   | 13.2    | 25.56   | 19.51   | 73.17     |
  | 4.0338        | 2.0   | 4690  | 3.7483          | 30.29   | 14.24   | 26.73   | 19.5    | 73.59     |
  | 3.8586        | 3.0   | 7035  | 3.7281          | 30.44   | 14.44   | 26.92   | 19.75   | 73.58     |
  | 3.7289        | 4.0   | 9380  | 3.7204          | 30.55   | 14.49   | 26.88   | 19.66   | 73.73     |
  | 3.6245        | 5.0   | 11725 | 3.7199          | 30.73   | 14.63   | 27.11   | 19.69   | 73.68     |
  | 3.5392        | 6.0   | 14070 | 3.7221          | 30.85   | 14.65   | 27.21   | 19.7    | 73.77     |
  | 3.4694        | 7.0   | 16415 | 3.7286          | 31.08   | 14.8    | 27.41   | 19.62   | 73.84     |
  | 3.4126        | 8.0   | 18760 | 3.7384          | 31.06   | 14.77   | 27.41   | 19.64   | 73.82     |
  | 3.3718        | 9.0   | 21105 | 3.7398          | 31.18   | 14.89   | 27.49   | 19.67   | 73.87     |
  | 3.3428        | 10.0  | 23450 | 3.7449          | 31.19   | 14.88   | 27.44   | 19.68   | 73.87     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  