readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-rewriter
    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-rewriter
  
  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: 1.3424
  - Rouge1: 46.6856
  - Rouge2: 31.6377
  - Rougel: 33.2741
  - Rougelsum: 44.5003
  - Gen Len: 126.58
  
  ## 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: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | No log        | 1.0   | 450  | 1.4020          | 47.0593 | 32.2065 | 33.9168 | 44.901    | 126.32  |
  | 1.9944        | 2.0   | 900  | 1.3567          | 46.2635 | 30.9959 | 32.933  | 44.1659   | 126.48  |
  | 1.6511        | 3.0   | 1350 | 1.3449          | 46.1544 | 30.7257 | 32.693  | 43.9977   | 126.4   |
  | 1.5951        | 4.0   | 1800 | 1.3424          | 46.6856 | 31.6377 | 33.2741 | 44.5003   | 126.58  |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  