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: 0.1966
  ---
  
  <!-- 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: 2.3829
  - Rouge1: 0.1966
  - Rouge2: 0.0969
  - Rougel: 0.1655
  - Rougelsum: 0.1657
  - Gen Len: 19.0
  
  ## 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: 2e-05
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 4
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
  | No log        | 1.0   | 248  | 2.5380          | 0.1441 | 0.0519 | 0.1188 | 0.1189    | 19.0    |
  | No log        | 2.0   | 496  | 2.4335          | 0.1939 | 0.0933 | 0.162  | 0.1622    | 19.0    |
  | 2.8683        | 3.0   | 744  | 2.3940          | 0.1974 | 0.0974 | 0.1665 | 0.1666    | 19.0    |
  | 2.8683        | 4.0   | 992  | 2.3829          | 0.1966 | 0.0969 | 0.1655 | 0.1657    | 19.0    |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  