readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-arxiv-pubmed-pubmed-v3-e8
    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. -->
  
  # distilbart-cnn-arxiv-pubmed-pubmed-v3-e8
  
  This model is a fine-tuned version of [theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed](https://huggingface.co/theojolliffe/distilbart-cnn-arxiv-pubmed-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8422
  - Rouge1: 54.9328
  - Rouge2: 36.7154
  - Rougel: 39.5674
  - Rougelsum: 52.4889
  - Gen Len: 142.0
  
  ## 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: 8
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 1.0   | 398  | 1.1158          | 50.9754 | 30.9416 | 33.9908 | 48.4925   | 142.0    |
  | 1.3585        | 2.0   | 796  | 0.9733          | 52.7954 | 33.8196 | 36.7836 | 50.4929   | 141.9259 |
  | 0.8785        | 3.0   | 1194 | 0.9142          | 53.5548 | 35.3954 | 37.4787 | 51.1024   | 142.0    |
  | 0.6485        | 4.0   | 1592 | 0.8666          | 52.6449 | 34.0018 | 37.5391 | 50.428    | 141.4074 |
  | 0.6485        | 5.0   | 1990 | 0.8458          | 53.8913 | 35.4481 | 38.1552 | 51.3737   | 141.8889 |
  | 0.4993        | 6.0   | 2388 | 0.8571          | 54.7333 | 36.8173 | 40.228  | 52.5574   | 141.9444 |
  | 0.3957        | 7.0   | 2786 | 0.8455          | 54.9826 | 37.9674 | 40.5786 | 52.5968   | 141.9815 |
  | 0.328         | 8.0   | 3184 | 0.8422          | 54.9328 | 36.7154 | 39.5674 | 52.4889   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.0
  - Tokenizers 0.12.1
  