readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: pegasus-large-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: 39.1107
  ---
  
  <!-- 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. -->
  
  # pegasus-large-finetuned-Pubmed
  
  This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7669
  - Rouge1: 39.1107
  - Rouge2: 15.4127
  - Rougel: 24.3729
  - Rougelsum: 35.1236
  - Gen Len: 226.594
  
  ## 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
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.065         | 1.0   | 1000 | 1.8262          | 37.1986 | 14.3685 | 23.7153 | 33.0713   | 218.902 |
  | 1.9552        | 2.0   | 2000 | 1.7933          | 38.0663 | 14.7813 | 23.8412 | 33.9574   | 217.488 |
  | 1.8983        | 3.0   | 3000 | 1.7768          | 38.3975 | 15.0983 | 24.0247 | 34.314    | 222.32  |
  | 1.882         | 4.0   | 4000 | 1.7687          | 39.1311 | 15.4167 | 24.2978 | 35.078    | 222.564 |
  | 1.8456        | 5.0   | 5000 | 1.7669          | 39.1107 | 15.4127 | 24.3729 | 35.1236   | 226.594 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  