readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distill-pegasus-cnn-arxiv-pubmed-v3-e4
    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. -->
  
  # distill-pegasus-cnn-arxiv-pubmed-v3-e4
  
  This model is a fine-tuned version of [theojolliffe/distill-pegasus-cnn-arxiv-pubmed](https://huggingface.co/theojolliffe/distill-pegasus-cnn-arxiv-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8962
  - Rouge1: 49.5676
  - Rouge2: 30.7141
  - Rougel: 34.191
  - Rougelsum: 45.0269
  - Gen Len: 125.8333
  
  ## 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: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 2.7729        | 1.0   | 795  | 2.1332          | 48.4776 | 29.8247 | 33.8775 | 44.0771   | 126.2407 |
  | 2.3362        | 2.0   | 1590 | 1.9953          | 48.7574 | 30.0148 | 33.8955 | 44.3967   | 126.2407 |
  | 2.2766        | 3.0   | 2385 | 1.9159          | 49.3004 | 30.5548 | 34.5702 | 44.8082   | 125.5    |
  | 2.1815        | 4.0   | 3180 | 1.8962          | 49.5676 | 30.7141 | 34.191  | 45.0269   | 125.8333 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  