readme: ---
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - wiki_lingua
  model-index:
  - name: AraT5-base-title-generation-finetuned-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. -->
  
  # AraT5-base-title-generation-finetuned-ar-xlsum
  
  This model is a fine-tuned version of [UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation) on the wiki_lingua dataset.
  It achieves the following results on the evaluation set:
  - Loss: 4.8120
  - Rouge-1: 23.29
  - Rouge-2: 8.44
  - Rouge-l: 20.74
  - Gen Len: 18.16
  - Bertscore: 70.88
  
  ## 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: 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 6.1002        | 1.0   | 5111  | 5.2917          | 18.95   | 5.84    | 17.01   | 17.9    | 68.69     |
  | 5.4427        | 2.0   | 10222 | 5.0877          | 20.61   | 6.73    | 18.58   | 17.14   | 69.69     |
  | 5.1876        | 3.0   | 15333 | 4.9631          | 21.27   | 7.17    | 19.09   | 17.69   | 69.82     |
  | 5.0256        | 4.0   | 20444 | 4.8984          | 21.7    | 7.53    | 19.55   | 17.56   | 70.18     |
  | 4.9104        | 5.0   | 25555 | 4.8538          | 22.23   | 7.54    | 19.79   | 17.6    | 70.33     |
  | 4.8251        | 6.0   | 30666 | 4.8309          | 22.35   | 7.6     | 19.96   | 17.64   | 70.51     |
  | 4.7666        | 7.0   | 35777 | 4.8168          | 22.45   | 7.81    | 20.15   | 17.47   | 70.61     |
  | 4.7275        | 8.0   | 40888 | 4.8120          | 22.67   | 7.83    | 20.34   | 17.56   | 70.66     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  