readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-newsroom_wires_hdwriter42k
    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_wires_hdwriter42k
  
  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: 1.5521
  - Rouge1: 37.5311
  - Rouge2: 17.6638
  - Rougel: 31.2287
  - Rougelsum: 31.7152
  - Gen Len: 35.1639
  
  ## 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: 2
  - eval_batch_size: 2
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.662         | 1.0   | 16875 | 1.5702          | 36.8068 | 17.3179 | 30.6952 | 31.1331   | 36.4668 |
  | 1.5071        | 2.0   | 33750 | 1.5503          | 37.5627 | 17.6519 | 31.2538 | 31.7985   | 35.3514 |
  | 1.4512        | 3.0   | 50625 | 1.5521          | 37.5311 | 17.6638 | 31.2287 | 31.7152   | 35.1639 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  