readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-multi_news-headline_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-multi_news-headline_57k
  
  This model is a fine-tuned version of [google/pegasus-multi_news](https://huggingface.co/google/pegasus-multi_news) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4503
  - Rouge1: 42.3147
  - Rouge2: 23.2213
  - Rougel: 35.7441
  - Rougelsum: 35.8964
  - Gen Len: 33.8245
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.6546        | 1.0   | 11339 | 1.5170          | 41.7822 | 22.7843 | 35.3913 | 35.5749   | 34.1139 |
  | 1.5132        | 2.0   | 22678 | 1.4602          | 42.0161 | 22.9778 | 35.5357 | 35.6921   | 33.9944 |
  | 1.4147        | 3.0   | 34017 | 1.4503          | 42.3147 | 23.2213 | 35.7441 | 35.8964   | 33.8245 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  