readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-arxiv-pubmed-pubmed-earlystopping
    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-earlystopping
  
  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: 0.8596
  - Rouge1: 53.4491
  - Rouge2: 35.0041
  - Rougel: 37.2742
  - Rougelsum: 50.9867
  - 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: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 0.31  | 125  | 1.3772          | 50.6084 | 30.8075 | 32.6113 | 47.883    | 142.0    |
  | No log        | 0.63  | 250  | 1.2423          | 52.1758 | 31.6326 | 32.9448 | 49.8089   | 141.6296 |
  | No log        | 0.94  | 375  | 1.1223          | 52.3494 | 32.3508 | 35.3638 | 49.6019   | 142.0    |
  | 1.3557        | 1.26  | 500  | 1.1004          | 51.8935 | 32.8506 | 35.521  | 49.6249   | 142.0    |
  | 1.3557        | 1.57  | 625  | 1.0600          | 50.8085 | 31.0397 | 34.2021 | 48.2264   | 141.5741 |
  | 1.3557        | 1.88  | 750  | 0.9834          | 53.0701 | 34.0699 | 36.4029 | 51.043    | 142.0    |
  | 1.3557        | 2.2   | 875  | 0.9554          | 53.4385 | 34.2976 | 36.8142 | 51.1262   | 141.9444 |
  | 0.868         | 2.51  | 1000 | 0.9256          | 52.2123 | 32.7568 | 34.5883 | 49.8566   | 142.0    |
  | 0.868         | 2.83  | 1125 | 0.8944          | 53.8062 | 34.6687 | 36.9645 | 51.5162   | 142.0    |
  | 0.868         | 3.14  | 1250 | 0.9290          | 53.1356 | 34.1301 | 37.7713 | 50.762    | 141.9074 |
  | 0.868         | 3.45  | 1375 | 0.9017          | 53.4455 | 35.0572 | 37.3033 | 50.9773   | 142.0    |
  | 0.6252        | 3.77  | 1500 | 0.8519          | 53.9228 | 35.5575 | 38.9119 | 51.5202   | 142.0    |
  | 0.6252        | 4.08  | 1625 | 0.8991          | 54.4223 | 36.3072 | 38.5771 | 51.9874   | 141.9074 |
  | 0.6252        | 4.4   | 1750 | 0.8857          | 53.4105 | 35.348  | 37.5814 | 50.8842   | 142.0    |
  | 0.6252        | 4.71  | 1875 | 0.8596          | 53.4491 | 35.0041 | 37.2742 | 50.9867   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  