readme: ---
  license: apache-2.0
  tags:
  - summarization
  - arabic
  - ar
  - mt5
  - Abstractive Summarization
  - generated_from_trainer
  datasets:
  - xlsum
  model-index:
  - name: mt5-base-arabic
    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. -->
  
  # mt5-base-arabic
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on arabic subset on the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.2742
  - Rouge-1: 22.86
  - Rouge-2: 10.31
  - Rouge-l: 20.85
  - Gen Len: 19.0
  - Bertscore: 71.52
  
  ## 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: 0.0005
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 8
  - total_train_batch_size: 32
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 4.2331        | 1.0   | 1172 | 3.5051          | 18.54   | 6.63    | 16.77   | 19.0    | 70.28     |
  | 3.7075        | 2.0   | 2344 | 3.3737          | 19.99   | 7.94    | 18.19   | 19.0    | 70.79     |
  | 3.5132        | 3.0   | 3516 | 3.3171          | 20.76   | 8.57    | 18.96   | 19.0    | 70.95     |
  | 3.3859        | 4.0   | 4688 | 3.2811          | 21.49   | 8.99    | 19.51   | 19.0    | 71.19     |
  | 3.3012        | 5.0   | 5860 | 3.2742          | 21.79   | 9.18    | 19.77   | 19.0    | 71.25     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  