readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - billsum
  metrics:
  - rouge
  model-index:
  - name: my_awesome_billsum_model
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: billsum
        type: billsum
        config: default
        split: ca_test
        args: default
      metrics:
      - name: Rouge1
        type: rouge
        value: 19.4885
  ---
  
  <!-- 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. -->
  
  # my_awesome_billsum_model
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.1303
  - Rouge1: 19.4885
  - Rouge2: 9.7756
  - Rougel: 16.7539
  - Rougelsum: 18.153
  
  ## 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: 5.6e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|
  | 2.9287        | 1.0   | 124  | 2.3690          | 18.7685 | 8.721  | 15.7134 | 17.2109   |
  | 2.5051        | 2.0   | 248  | 2.2540          | 19.5651 | 9.5886 | 16.5619 | 18.1252   |
  | 2.4042        | 3.0   | 372  | 2.2140          | 19.4716 | 9.7429 | 16.6675 | 18.0006   |
  | 2.3442        | 4.0   | 496  | 2.1800          | 19.5841 | 9.7078 | 16.7923 | 18.1682   |
  | 2.3075        | 5.0   | 620  | 2.1562          | 19.4162 | 9.6647 | 16.5106 | 17.9637   |
  | 2.2693        | 6.0   | 744  | 2.1394          | 19.5064 | 9.8462 | 16.6515 | 18.0461   |
  | 2.2714        | 7.0   | 868  | 2.1321          | 19.475  | 9.7216 | 16.6698 | 18.1103   |
  | 2.2413        | 8.0   | 992  | 2.1303          | 19.4885 | 9.7756 | 16.7539 | 18.153    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  