readme: ---
  license: apache-2.0
  tags:
  - summarization
  - arabic
  - ar
  - mt5
  - Abstractive Summarization
  - generated_from_trainer
  datasets:
  - xlsum
  model-index:
  - name: mt5-base-finetuned-persian-finetuned-persian-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-finetuned-persian-finetuned-persian-arabic
  
  This model is a fine-tuned version of [ahmeddbahaa/mt5-base-finetuned-persian](https://huggingface.co/ahmeddbahaa/mt5-base-finetuned-persian) on the xlsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.3234
  - Rouge-1: 22.96
  - Rouge-2: 10.27
  - Rouge-l: 20.95
  - Gen Len: 19.0
  - Bertscore: 71.59
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 4.2754        | 1.0   | 1172 | 3.5717          | 19.26   | 7.26    | 17.48   | 19.0    | 70.49     |
  | 3.7388        | 2.0   | 2344 | 3.4291          | 19.71   | 7.88    | 17.94   | 19.0    | 70.64     |
  | 3.541         | 3.0   | 3516 | 3.3653          | 21.18   | 8.84    | 19.35   | 19.0    | 71.05     |
  | 3.4113        | 4.0   | 4688 | 3.3306          | 21.54   | 9.11    | 19.65   | 19.0    | 71.19     |
  | 3.3256        | 5.0   | 5860 | 3.3234          | 21.69   | 9.22    | 19.81   | 19.0    | 71.31     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  