readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: bigbird-pegasus-large-arxiv-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: 45.4807
  ---
  
  <!-- 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-arxiv-finetuned-pubmed
  
  This model is a fine-tuned version of [google/bigbird-pegasus-large-arxiv](https://huggingface.co/google/bigbird-pegasus-large-arxiv) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.6049
  - Rouge1: 45.4807
  - Rouge2: 20.0199
  - Rougel: 28.3621
  - Rougelsum: 41.4618
  - Gen Len: 219.144
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.594         | 1.0   | 500  | 1.9879          | 33.6364 | 13.5074 | 21.4286 | 29.7158   | 189.014 |
  | 1.9146        | 2.0   | 1000 | 1.6494          | 44.0056 | 19.0069 | 27.5142 | 40.0492   | 210.528 |
  | 1.7378        | 3.0   | 1500 | 1.6213          | 44.7071 | 19.3559 | 27.6806 | 40.6124   | 213.596 |
  | 1.692         | 4.0   | 2000 | 1.6081          | 45.1505 | 19.7355 | 28.06   | 41.0108   | 213.674 |
  | 1.6656        | 5.0   | 2500 | 1.6049          | 45.4807 | 20.0199 | 28.3621 | 41.4618   | 219.144 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  