readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - scientific_papers
  metrics:
  - rouge
  model-index:
  - name: bart-base-finetuned-arxiv
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: scientific_papers
        type: scientific_papers
        args: arxiv
      metrics:
      - name: Rouge1
        type: rouge
        value: 13.6917
  ---
  
  <!-- 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-arxiv
  
  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: 2.2912
  - Rouge1: 13.6917
  - Rouge2: 5.9564
  - Rougel: 11.1734
  - Rougelsum: 12.6817
  - Gen Len: 19.9992
  
  ## 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: 32
  - eval_batch_size: 32
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 2.6027        | 1.0   | 6345  | 2.4504          | 13.3687 | 5.603  | 10.8671 | 12.3297   | 20.0    |
  | 2.4807        | 2.0   | 12690 | 2.3561          | 13.6207 | 5.855  | 11.1073 | 12.594    | 20.0    |
  | 2.4041        | 3.0   | 19035 | 2.3035          | 13.6222 | 5.8863 | 11.1173 | 12.5984   | 20.0    |
  | 2.3716        | 4.0   | 25380 | 2.2912          | 13.6917 | 5.9564 | 11.1734 | 12.6817   | 19.9992 |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.1+cu102
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  