readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-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. -->
  
  # bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv-earlystopping
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed-arxiv-arxiv) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8347
  - Rouge1: 53.9049
  - Rouge2: 35.5953
  - Rougel: 39.788
  - Rougelsum: 51.4101
  - 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: 200
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | No log        | 0.31  | 125  | 1.0240          | 52.5632 | 32.977  | 34.672  | 49.9905   | 142.0    |
  | No log        | 0.63  | 250  | 1.0056          | 52.5508 | 32.4826 | 34.6851 | 49.835    | 141.6852 |
  | No log        | 0.94  | 375  | 0.8609          | 53.0475 | 32.9384 | 35.3322 | 50.272    | 141.6481 |
  | 0.8255        | 1.26  | 500  | 0.9022          | 52.2493 | 31.5622 | 33.389  | 49.6612   | 142.0    |
  | 0.8255        | 1.57  | 625  | 0.8706          | 53.3568 | 33.2533 | 35.7531 | 50.4568   | 141.8889 |
  | 0.8255        | 1.88  | 750  | 0.8186          | 52.7375 | 33.4439 | 37.1094 | 50.5323   | 142.0    |
  | 0.8255        | 2.2   | 875  | 0.8041          | 53.4992 | 34.6929 | 37.9614 | 51.091    | 142.0    |
  | 0.5295        | 2.51  | 1000 | 0.7907          | 52.6185 | 33.8053 | 37.1725 | 50.4881   | 142.0    |
  | 0.5295        | 2.83  | 1125 | 0.7740          | 52.7107 | 33.1023 | 36.0865 | 50.0365   | 142.0    |
  | 0.5295        | 3.14  | 1250 | 0.8200          | 52.5607 | 33.7948 | 37.2312 | 50.3345   | 142.0    |
  | 0.5295        | 3.45  | 1375 | 0.8188          | 53.9233 | 34.446  | 36.7566 | 51.3135   | 142.0    |
  | 0.351         | 3.77  | 1500 | 0.8071          | 53.9096 | 35.5977 | 38.6832 | 51.4986   | 142.0    |
  | 0.351         | 4.08  | 1625 | 0.8347          | 53.9049 | 35.5953 | 39.788  | 51.4101   | 142.0    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.1
  - Tokenizers 0.12.1
  