readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - rouge
  model-index:
  - name: bart-cnn-pubmed-arxiv-pubmed-v3-e10
    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-v3-e10
  
  This model is a fine-tuned version of [theojolliffe/bart-cnn-pubmed-arxiv-pubmed](https://huggingface.co/theojolliffe/bart-cnn-pubmed-arxiv-pubmed) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.8410
  - Rouge1: 56.5123
  - Rouge2: 41.1641
  - Rougel: 43.4495
  - Rougelsum: 54.544
  - Gen Len: 141.6667
  
  ## 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 1.254         | 1.0   | 795  | 0.9244          | 52.4478 | 32.5958 | 34.8756 | 49.8059   | 142.0    |
  | 0.6985        | 2.0   | 1590 | 0.8156          | 52.4786 | 33.2296 | 35.5063 | 49.737    | 141.7963 |
  | 0.5252        | 3.0   | 2385 | 0.7821          | 52.0494 | 32.953  | 36.5502 | 49.7292   | 142.0    |
  | 0.3389        | 4.0   | 3180 | 0.7422          | 53.5408 | 36.2206 | 39.8389 | 51.6693   | 142.0    |
  | 0.26          | 5.0   | 3975 | 0.7670          | 54.4279 | 36.5972 | 40.255  | 52.0877   | 142.0    |
  | 0.1678        | 6.0   | 4770 | 0.8106          | 54.6811 | 37.8329 | 40.8512 | 52.3482   | 141.963  |
  | 0.1243        | 7.0   | 5565 | 0.7926          | 54.5081 | 37.9596 | 41.912  | 52.5097   | 142.0    |
  | 0.0967        | 8.0   | 6360 | 0.8079          | 56.0795 | 40.0954 | 43.7055 | 54.2041   | 142.0    |
  | 0.0709        | 9.0   | 7155 | 0.8390          | 55.5257 | 38.5546 | 42.1562 | 53.5524   | 141.963  |
  | 0.0691        | 10.0  | 7950 | 0.8410          | 56.5123 | 41.1641 | 43.4495 | 54.544    | 141.6667 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  