readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-malay_headlines
    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. -->
  
  # pegasus-newsroom-malay_headlines
  
  This model is a fine-tuned version of [google/pegasus-newsroom](https://huggingface.co/google/pegasus-newsroom) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6603
  - Rouge1: 42.6667
  - Rouge2: 22.8739
  - Rougel: 38.6684
  - Rougelsum: 38.6928
  - Gen Len: 34.7995
  
  ## 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: 2e-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
  - num_epochs: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.9713        | 1.0   | 15310 | 1.8121          | 41.1469 | 21.5262 | 37.3081 | 37.3377   | 35.0939 |
  | 1.7917        | 2.0   | 30620 | 1.6913          | 42.4027 | 22.6089 | 38.4471 | 38.4699   | 34.8149 |
  | 1.7271        | 3.0   | 45930 | 1.6603          | 42.6667 | 22.8739 | 38.6684 | 38.6928   | 34.7995 |
  
  
  ### Framework versions
  
  - Transformers 4.12.2
  - Pytorch 1.9.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  