readme: ---
  tags:
  - paraphrasing
  - generated_from_trainer
  datasets:
  - paws
  metrics:
  - rouge
  model-index:
  - name: pegasus-pubmed-finetuned-paws
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: paws
        type: paws
        args: labeled_final
      metrics:
      - name: Rouge1
        type: rouge
        value: 56.8108
  ---
  
  <!-- 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-pubmed-finetuned-paws
  
  This model is a fine-tuned version of [google/pegasus-pubmed](https://huggingface.co/google/pegasus-pubmed) on the paws dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.5012
  - Rouge1: 56.8108
  - Rouge2: 36.2576
  - Rougel: 51.1666
  - Rougelsum: 51.2193
  
  ## 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: 0.0001
  - train_batch_size: 16
  - eval_batch_size: 8
  - 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
  - label_smoothing_factor: 0.1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
  | No log        | 0.73  | 1000 | 3.8839          | 51.2731 | 29.8072 | 45.767  | 45.5732   |
  | 4.071         | 1.47  | 2000 | 3.6459          | 52.756  | 31.9185 | 48.0092 | 48.0544   |
  | 3.5467        | 2.2   | 3000 | 3.5849          | 54.8127 | 33.1959 | 49.326  | 49.4971   |
  | 3.5467        | 2.93  | 4000 | 3.5267          | 55.387  | 33.9516 | 50.683  | 50.6313   |
  | 3.3654        | 3.66  | 5000 | 3.5031          | 57.5279 | 35.2664 | 51.9903 | 52.258    |
  | 3.2844        | 4.4   | 6000 | 3.5296          | 56.0536 | 33.395  | 50.9909 | 51.244    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  