readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: bigbird-pegasus-large-bigpatent-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: 45.0851
  ---
  
  <!-- 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. -->
  
  # bigbird-pegasus-large-bigpatent-finetuned-pubMed
  
  This model is a fine-tuned version of [google/bigbird-pegasus-large-bigpatent](https://huggingface.co/google/bigbird-pegasus-large-bigpatent) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.5403
  - Rouge1: 45.0851
  - Rouge2: 19.5488
  - Rougel: 27.391
  - Rougelsum: 41.112
  - Gen Len: 231.608
  
  ## 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: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.1198        | 1.0   | 500  | 1.6285          | 43.0579 | 18.1792 | 26.421  | 39.0769   | 214.924 |
  | 1.6939        | 2.0   | 1000 | 1.5696          | 44.0679 | 18.9331 | 26.84   | 40.0684   | 222.814 |
  | 1.6195        | 3.0   | 1500 | 1.5506          | 44.7352 | 19.3532 | 27.2418 | 40.7454   | 229.396 |
  | 1.5798        | 4.0   | 2000 | 1.5403          | 45.0415 | 19.5019 | 27.2969 | 40.951    | 231.044 |
  | 1.5592        | 5.0   | 2500 | 1.5403          | 45.0851 | 19.5488 | 27.391  | 41.112    | 231.608 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  