readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: bart-base-finetuned-pubmed
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: pub_med_summarization_dataset
        type: pub_med_summarization_dataset
        args: document
      metrics:
      - name: Rouge1
        type: rouge
        value: 9.3963
  ---
  
  <!-- 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 pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0277
  - Rouge1: 9.3963
  - Rouge2: 4.0473
  - Rougel: 8.4526
  - Rougelsum: 8.9659
  - 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: 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 2.3706        | 1.0   | 4000  | 2.1245          | 9.1644 | 3.8264 | 8.2223 | 8.718     | 20.0    |
  | 2.2246        | 2.0   | 8000  | 2.0811          | 9.023  | 3.7716 | 8.1453 | 8.5998    | 20.0    |
  | 2.1034        | 3.0   | 12000 | 2.0469          | 9.4412 | 4.0783 | 8.4949 | 8.9977    | 20.0    |
  | 2.0137        | 4.0   | 16000 | 2.0390          | 9.2261 | 3.9307 | 8.3154 | 8.7937    | 20.0    |
  | 1.9288        | 5.0   | 20000 | 2.0277          | 9.3963 | 4.0473 | 8.4526 | 8.9659    | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.16.2
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  