readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-v3-e16
    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-v3-e16
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9340
  - Rouge1: 57.6388
  - Rouge2: 44.834
  - Rougel: 47.5043
  - Rougelsum: 56.1122
  - 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: 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: 16
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 1.2407        | 1.0   | 795   | 0.9270          | 53.3842 | 33.8559 | 35.7393 | 50.6907   | 142.0   |
  | 0.704         | 2.0   | 1590  | 0.8092          | 53.2159 | 35.0209 | 37.8641 | 50.9514   | 141.963 |
  | 0.5277        | 3.0   | 2385  | 0.7588          | 52.7709 | 34.2453 | 36.6319 | 50.1137   | 142.0   |
  | 0.3449        | 4.0   | 3180  | 0.7617          | 52.0249 | 34.5679 | 37.3669 | 49.7643   | 142.0   |
  | 0.2668        | 5.0   | 3975  | 0.7575          | 54.3131 | 35.3985 | 38.9242 | 51.5667   | 142.0   |
  | 0.1756        | 6.0   | 4770  | 0.8161          | 53.6214 | 36.4376 | 39.1745 | 51.3685   | 142.0   |
  | 0.1326        | 7.0   | 5565  | 0.7848          | 55.7549 | 38.8517 | 42.0106 | 53.4243   | 142.0   |
  | 0.1051        | 8.0   | 6360  | 0.7912          | 55.2709 | 39.952  | 42.7398 | 53.6479   | 142.0   |
  | 0.0781        | 9.0   | 7155  | 0.8491          | 55.5698 | 40.0599 | 42.9521 | 53.6734   | 142.0   |
  | 0.0685        | 10.0  | 7950  | 0.8684          | 55.1142 | 40.3136 | 43.699  | 53.5463   | 142.0   |
  | 0.0494        | 11.0  | 8745  | 0.8886          | 57.7988 | 43.6659 | 46.0913 | 56.3383   | 142.0   |
  | 0.0338        | 12.0  | 9540  | 0.8827          | 57.0166 | 42.7553 | 46.2344 | 55.2893   | 142.0   |
  | 0.0296        | 13.0  | 10335 | 0.9111          | 56.7741 | 42.6116 | 45.1692 | 55.2065   | 142.0   |
  | 0.0228        | 14.0  | 11130 | 0.9209          | 56.635  | 43.2461 | 46.314  | 55.049    | 142.0   |
  | 0.0189        | 15.0  | 11925 | 0.9193          | 56.4404 | 43.4216 | 46.279  | 55.1403   | 142.0   |
  | 0.0152        | 16.0  | 12720 | 0.9340          | 57.6388 | 44.834  | 47.5043 | 56.1122   | 142.0   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  