readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - pub_med_summarization_dataset
  metrics:
  - rouge
  model-index:
  - name: distilbart-cnn-6-6-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: 39.2769
  ---
  
  <!-- 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. -->
  
  # distilbart-cnn-6-6-finetuned-pubmed
  
  This model is a fine-tuned version of [sshleifer/distilbart-cnn-6-6](https://huggingface.co/sshleifer/distilbart-cnn-6-6) on the pub_med_summarization_dataset dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0648
  - Rouge1: 39.2769
  - Rouge2: 15.876
  - Rougel: 24.2306
  - Rougelsum: 35.267
  - Gen Len: 141.8565
  
  ## 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
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
  | 2.2215        | 1.0   | 4000  | 2.0781          | 37.2476 | 14.2852 | 22.6875 | 33.1607   | 141.97   |
  | 2.0105        | 2.0   | 8000  | 2.0217          | 37.8038 | 14.7869 | 23.2025 | 33.7069   | 141.918  |
  | 1.8331        | 3.0   | 12000 | 2.0243          | 39.0497 | 15.8077 | 24.2237 | 34.9371   | 141.822  |
  | 1.6936        | 4.0   | 16000 | 2.0487          | 38.7059 | 15.4364 | 23.8514 | 34.7771   | 141.878  |
  | 1.5817        | 5.0   | 20000 | 2.0648          | 39.2769 | 15.876  | 24.2306 | 35.267    | 141.8565 |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 1.18.3
  - Tokenizers 0.11.6
  