readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - scientific_papers
  metrics:
  - rouge
  model-index:
  - name: bart-large-cnn-pubmed1o3
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: scientific_papers
        type: scientific_papers
        args: pubmed
      metrics:
      - name: Rouge1
        type: rouge
        value: 36.7566
  ---
  
  <!-- 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-large-cnn-pubmed1o3
  
  This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the scientific_papers dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9359
  - Rouge1: 36.7566
  - Rouge2: 14.813
  - Rougel: 22.4693
  - Rougelsum: 33.4325
  - Gen Len: 138.7332
  
  ## 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: 1
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:--------:|
  | 2.028         | 1.0   | 19988 | 1.9359          | 36.7566 | 14.813 | 22.4693 | 33.4325   | 138.7332 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  