readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - samsum
  model-index:
  - name: pegasus-samsum
    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-samsum
  
  This model is a fine-tuned version of [google/pegasus-cnn_dailymail](https://huggingface.co/google/pegasus-cnn_dailymail) on the samsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.4177
  
  ## 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: 5e-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
  - lr_scheduler_warmup_steps: 500
  - num_epochs: 0.4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 1.6092        | 0.03  | 500  | 1.6488          |
  | 1.9715        | 0.07  | 1000 | 1.5444          |
  | 1.8325        | 0.1   | 1500 | 1.5093          |
  | 1.876         | 0.14  | 2000 | 1.4890          |
  | 1.3081        | 0.17  | 2500 | 1.4737          |
  | 1.7769        | 0.2   | 3000 | 1.4496          |
  | 1.6276        | 0.24  | 3500 | 1.4430          |
  | 1.6624        | 0.27  | 4000 | 1.4288          |
  | 1.9202        | 0.31  | 4500 | 1.4235          |
  | 1.4404        | 0.34  | 5000 | 1.4189          |
  | 1.8016        | 0.37  | 5500 | 1.4177          |
  
  
  ### Framework versions
  
  - Transformers 4.12.0.dev0
  - Pytorch 1.9.1+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  