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53496ca
metadata
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

my_awesome_billsum_model

This model is a fine-tuned version of 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