readme: ---
  license: apache-2.0
  tags:
  - summarization
  - arabic
  - ar
  - ur
  - urdu
  - mt5
  - Abstractive Summarization
  - generated_from_trainer
  model-index:
  - name: mt5-base-finetuned-ar-fa
    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-ar-fa
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.0303
  - Rouge-1: 26.73
  - Rouge-2: 12.63
  - Rouge-l: 23.96
  - Gen Len: 18.99
  - Bertscore: 71.41
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 3.7736        | 1.0   | 3287  | 3.2308          | 24.22   | 10.11   | 21.46   | 18.99   | 70.69     |
  | 3.3783        | 2.0   | 6574  | 3.1283          | 25.28   | 10.9    | 22.43   | 18.99   | 71.02     |
  | 3.2351        | 3.0   | 9861  | 3.0693          | 25.77   | 11.36   | 22.93   | 19.0    | 71.2      |
  | 3.1363        | 4.0   | 13148 | 3.0421          | 25.88   | 11.57   | 23.08   | 18.99   | 71.22     |
  | 3.0669        | 5.0   | 16435 | 3.0303          | 26.25   | 11.84   | 23.44   | 18.99   | 71.39     |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  