readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - scientific_papers
  metrics:
  - rouge
  model-index:
  - name: bart-base-finetuned-pubmed
    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: 9.1984
  ---
  
  <!-- 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-base-finetuned-pubmed
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the scientific_papers dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9804
  - Rouge1: 9.1984
  - Rouge2: 4.3091
  - Rougel: 7.9739
  - Rougelsum: 8.6759
  - Gen Len: 20.0
  
  ## 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: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 2.2869        | 1.0   | 29981  | 2.1241          | 9.0852 | 4.1152 | 7.842  | 8.5395    | 20.0    |
  | 2.1469        | 2.0   | 59962  | 2.0225          | 9.1609 | 4.2437 | 7.9311 | 8.6273    | 20.0    |
  | 2.113         | 3.0   | 89943  | 1.9959          | 9.3086 | 4.3305 | 8.0363 | 8.7713    | 20.0    |
  | 2.0632        | 4.0   | 119924 | 1.9804          | 9.1984 | 4.3091 | 7.9739 | 8.6759    | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  