readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: pegasus-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: 44.286
  ---
  
  <!-- 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-arxiv-finetuned-pubmed
  
  This model is a fine-tuned version of [google/pegasus-arxiv](https://huggingface.co/google/pegasus-arxiv) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8118
  - Rouge1: 44.286
  - Rouge2: 19.0477
  - Rougel: 27.1122
  - Rougelsum: 40.2609
  - Gen Len: 230.586
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
  | 2.65          | 1.0   | 1000 | 1.9848          | 40.6984 | 16.387  | 25.0097 | 36.4831   | 215.294 |
  | 2.1317        | 2.0   | 2000 | 1.8524          | 43.6431 | 18.6794 | 26.7571 | 39.6642   | 224.646 |
  | 2.0591        | 3.0   | 3000 | 1.8254          | 43.6707 | 18.5176 | 26.6015 | 39.6325   | 225.894 |
  | 2.0109        | 4.0   | 4000 | 1.8138          | 44.1244 | 18.8866 | 26.8313 | 40.0913   | 229.656 |
  | 1.9894        | 5.0   | 5000 | 1.8118          | 44.286  | 19.0477 | 27.1122 | 40.2609   | 230.586 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.9.1
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  