readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-multi_news-headline
    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
  
  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: 1.4421
  - Rouge1: 41.616
  - Rouge2: 22.922
  - Rougel: 35.2189
  - Rougelsum: 35.3561
  - Gen Len: 33.9532
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.6637        | 1.0   | 31200 | 1.4877          | 41.0996 | 22.579  | 34.9311 | 35.0611   | 34.3431 |
  | 1.4395        | 2.0   | 62400 | 1.4388          | 41.6075 | 22.8274 | 35.2051 | 35.3526   | 33.7965 |
  | 1.3137        | 3.0   | 93600 | 1.4421          | 41.616  | 22.922  | 35.2189 | 35.3561   | 33.9532 |
  
  
  ### Framework versions
  
  - Transformers 4.12.2
  - Pytorch 1.9.0+cu111
  - Datasets 1.14.0
  - Tokenizers 0.10.3
  