readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-headline_writer
    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
  
  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: 1.3988
  - Rouge1: 41.8748
  - Rouge2: 23.1947
  - Rougel: 35.6263
  - Rougelsum: 35.7355
  - Gen Len: 34.1266
  
  ## 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: 1
  - eval_batch_size: 1
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.5784        | 1.0   | 31200 | 1.4287          | 41.4257 | 22.9355 | 35.3299 | 35.4648   | 34.4677 |
  | 1.3501        | 2.0   | 62400 | 1.3955          | 41.9119 | 23.1912 | 35.6698 | 35.7479   | 33.8672 |
  | 1.2417        | 3.0   | 93600 | 1.3988          | 41.8748 | 23.1947 | 35.6263 | 35.7355   | 34.1266 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  