readme: ---
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - wiki_lingua
  model-index:
  - name: mT5_multilingual_XLSum-finetuned-ar-wikilingua
    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_multilingual_XLSum-finetuned-ar-wikilingua
  
  This model is a fine-tuned version of [csebuetnlp/mT5_multilingual_XLSum](https://huggingface.co/csebuetnlp/mT5_multilingual_XLSum) on the wiki_lingua dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.6903
  - Rouge-1: 24.47
  - Rouge-2: 7.69
  - Rouge-l: 20.04
  - Gen Len: 39.64
  - Bertscore: 72.63
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 4.4406        | 1.0   | 5111  | 3.9582          | 22.35   | 6.84    | 18.39   | 34.78   | 71.94     |
  | 4.0158        | 2.0   | 10222 | 3.8316          | 22.87   | 7.24    | 18.92   | 34.7    | 71.99     |
  | 3.8626        | 3.0   | 15333 | 3.7695          | 23.65   | 7.5     | 19.6    | 35.53   | 72.31     |
  | 3.7626        | 4.0   | 20444 | 3.7313          | 24.01   | 7.59    | 19.68   | 38.16   | 72.41     |
  | 3.6934        | 5.0   | 25555 | 3.7118          | 24.37   | 7.77    | 19.93   | 39.36   | 72.47     |
  | 3.6421        | 6.0   | 30666 | 3.7016          | 24.48   | 7.8     | 20.07   | 38.58   | 72.58     |
  | 3.6073        | 7.0   | 35777 | 3.6907          | 24.31   | 7.83    | 20.13   | 38.07   | 72.5      |
  | 3.5843        | 8.0   | 40888 | 3.6903          | 24.55   | 7.88    | 20.2    | 38.33   | 72.6      |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  