readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: pegasus-multi_news_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-multi_news_wires_hdwriter42k
  
  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: 1.6427
  - Rouge1: 37.3045
  - Rouge2: 17.2478
  - Rougel: 30.7768
  - Rougelsum: 31.3514
  - Gen Len: 34.6955
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.7914        | 1.0   | 16875 | 1.6849          | 36.6608 | 17.005  | 30.4166 | 30.9289   | 35.4077 |
  | 1.6658        | 2.0   | 33750 | 1.6452          | 37.2837 | 17.3162 | 30.8358 | 31.3382   | 34.7757 |
  | 1.5478        | 3.0   | 50625 | 1.6427          | 37.3045 | 17.2478 | 30.7768 | 31.3514   | 34.6955 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  