readme: ---
  license: apache-2.0
  tags:
  - summarization
  - generated_from_trainer
  datasets:
  - wiki_lingua
  model-index:
  - name: mt5-base-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-base-finetuned-ar-wikilingua
  
  This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wiki_lingua dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.6790
  - Rouge-1: 19.46
  - Rouge-2: 6.82
  - Rouge-l: 17.57
  - Gen Len: 18.83
  - Bertscore: 70.18
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
  | 4.9783        | 1.0   | 5111  | 4.0107          | 15.8    | 4.65    | 14.18   | 18.98   | 68.66     |
  | 4.2093        | 2.0   | 10222 | 3.8664          | 16.46   | 5.17    | 15.08   | 18.91   | 68.5      |
  | 4.0303        | 3.0   | 15333 | 3.7847          | 17.0    | 5.43    | 15.45   | 18.89   | 68.75     |
  | 3.9165        | 4.0   | 20444 | 3.7405          | 17.03   | 5.5     | 15.45   | 18.86   | 68.78     |
  | 3.8396        | 5.0   | 25555 | 3.7102          | 17.14   | 5.57    | 15.48   | 18.87   | 68.92     |
  | 3.7825        | 6.0   | 30666 | 3.6944          | 17.64   | 5.73    | 15.96   | 18.82   | 69.14     |
  | 3.7447        | 7.0   | 35777 | 3.6801          | 17.6    | 5.66    | 15.9    | 18.78   | 69.23     |
  | 3.7203        | 8.0   | 40888 | 3.6790          | 17.94   | 5.81    | 16.21   | 18.81   | 69.29     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  