readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-headline_writer_oct22
    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_oct22
  
  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: 1.3462
  - Rouge1: 41.8799
  - Rouge2: 23.1785
  - Rougel: 35.5346
  - Rougelsum: 35.6203
  - Gen Len: 34.3108
  
  ## 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 |
  |:-------------:|:-----:|:------:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.4364        | 1.0   | 38400  | 1.3730          | 41.9525 | 23.0823 | 35.5435 | 35.6485   | 34.1161 |
  | 1.2483        | 2.0   | 76800  | 1.3430          | 42.1538 | 23.3302 | 35.8119 | 35.9063   | 33.9333 |
  | 1.1873        | 3.0   | 115200 | 1.3462          | 41.8799 | 23.1785 | 35.5346 | 35.6203   | 34.3108 |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  