readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - farleyknight/big_patent_5_percent
  metrics:
  - rouge
  model-index:
  - name: patent-summarization-fb-bart-base-2022-09-20
    results:
    - task:
        name: Summarization
        type: summarization
      dataset:
        name: farleyknight/big_patent_5_percent
        type: farleyknight/big_patent_5_percent
        config: all
        split: train
        args: all
      metrics:
      - name: Rouge1
        type: rouge
        value: 39.4401
  ---
  
  <!-- 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. -->
  
  # patent-summarization-fb-bart-base-2022-09-20
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the farleyknight/big_patent_5_percent dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.4088
  - Rouge1: 39.4401
  - Rouge2: 14.2445
  - Rougel: 26.2701
  - Rougelsum: 33.7535
  - Gen Len: 78.9702
  
  ## 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: 5e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 1.0
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
  | 3.0567        | 0.08  | 5000  | 2.8864          | 18.9387 | 7.1014 | 15.4506 | 16.8377   | 19.9979 |
  | 2.9285        | 0.17  | 10000 | 2.7800          | 19.8983 | 7.3258 | 16.0823 | 17.7019   | 20.0    |
  | 2.9252        | 0.25  | 15000 | 2.7080          | 19.6623 | 7.4627 | 16.0153 | 17.4485   | 20.0    |
  | 2.8123        | 0.33  | 20000 | 2.6585          | 19.7414 | 7.5251 | 15.8166 | 17.4668   | 20.0    |
  | 2.7117        | 0.41  | 25000 | 2.6070          | 19.7661 | 7.7193 | 16.2795 | 17.7884   | 20.0    |
  | 2.7131        | 0.5   | 30000 | 2.5616          | 19.6706 | 7.4229 | 15.7998 | 17.4324   | 20.0    |
  | 2.6373        | 0.58  | 35000 | 2.5250          | 20.0155 | 7.6811 | 16.1231 | 17.7578   | 20.0    |
  | 2.6785        | 0.66  | 40000 | 2.4977          | 20.0974 | 7.9578 | 16.543  | 18.0242   | 20.0    |
  | 2.6265        | 0.75  | 45000 | 2.4701          | 19.994  | 7.9114 | 16.3501 | 17.8786   | 20.0    |
  | 2.5833        | 0.83  | 50000 | 2.4441          | 19.9981 | 7.934  | 16.3033 | 17.8674   | 20.0    |
  | 2.5579        | 0.91  | 55000 | 2.4251          | 20.0544 | 7.8966 | 16.3889 | 17.9491   | 20.0    |
  | 2.5242        | 0.99  | 60000 | 2.4097          | 20.1093 | 8.0572 | 16.4935 | 17.9823   | 20.0    |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.12.0
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  