readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom-summarizer_02
    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-summarizer_02
  
  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: 1.2204
  - Rouge1: 52.4459
  - Rouge2: 35.2568
  - Rougel: 41.6213
  - Rougelsum: 48.7859
  - Gen Len: 98.0627
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.3231        | 1.0   | 16113 | 1.2305          | 52.1565 | 34.8681 | 41.3189 | 48.4258   | 95.9049 |
  | 1.3001        | 2.0   | 32226 | 1.2186          | 52.4921 | 35.2661 | 41.6264 | 48.8168   | 98.9241 |
  | 1.2372        | 3.0   | 48339 | 1.2204          | 52.4459 | 35.2568 | 41.6213 | 48.7859   | 98.0627 |
  
  
  ### Framework versions
  
  - Transformers 4.12.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.15.1
  - Tokenizers 0.10.3
  