readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - farleyknight/big_patent_5_percent
  metrics:
  - rouge
  model-index:
  - name: patent-summarization-allen-led-large-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: 0.0
  ---
  
  <!-- 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-allen-led-large-2022-09-20
  
  This model is a fine-tuned version of [allenai/led-large-16384-arxiv](https://huggingface.co/allenai/led-large-16384-arxiv) on the farleyknight/big_patent_5_percent dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8233
  - Rouge1: 0.0
  - Rouge2: 0.0
  - Rougel: 0.0
  - Rougelsum: 0.0
  - Gen Len: 128.0
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | 3.4766        | 0.08  | 5000  | 3.4240          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 3.2549        | 0.17  | 10000 | 3.2908          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 3.2295        | 0.25  | 15000 | 3.1862          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 3.1455        | 0.33  | 20000 | 3.1291          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 3.0526        | 0.41  | 25000 | 3.0684          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 3.0024        | 0.5   | 30000 | 3.0134          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.9671        | 0.58  | 35000 | 2.9696          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.9862        | 0.66  | 40000 | 2.9431          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.9168        | 0.75  | 45000 | 2.8989          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.9063        | 0.83  | 50000 | 2.8559          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.8417        | 0.91  | 55000 | 2.8398          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  | 2.7853        | 0.99  | 60000 | 2.8240          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
  
  
  ### Framework versions
  
  - Transformers 4.23.0.dev0
  - Pytorch 1.12.0
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  