readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-headline_writer_57k
    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-headline_writer_57k
  
  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: 1.3599
  - Rouge1: 42.2586
  - Rouge2: 23.2731
  - Rougel: 35.8685
  - Rougelsum: 36.0581
  - Gen Len: 34.3651
  
  ## 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: 8
  - eval_batch_size: 8
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.5213        | 1.0   | 5670  | 1.4040          | 41.8648 | 22.8205 | 35.3983 | 35.535    | 34.8817 |
  | 1.4171        | 2.0   | 11340 | 1.3672          | 42.26   | 23.2611 | 35.8016 | 35.9753   | 34.3492 |
  | 1.3722        | 3.0   | 17010 | 1.3599          | 42.2586 | 23.2731 | 35.8685 | 36.0581   | 34.3651 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  