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End of training
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metadata
license: apache-2.0
base_model: google/flan-t5-base
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
model-index:
  - name: flan-t5-base-billsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: billsum
          type: billsum
          config: default
          split: train[16000:]
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 14.041

flan-t5-base-billsum

This model is a fine-tuned version of google/flan-t5-base on the billsum dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Rouge1: 14.041
  • Rouge2: 6.012
  • Rougel: 11.3068
  • Rougelsum: 12.0551
  • Gen Len: 16.0610

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: 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 Gen Len
0.0 1.0 2359 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 2.0 4718 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 3.0 7077 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 4.0 9436 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 5.0 11795 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 6.0 14154 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 7.0 16513 nan 14.041 6.012 11.3068 12.0551 16.0610
0.0 8.0 18872 nan 14.041 6.012 11.3068 12.0551 16.0610

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3