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billsum-model

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

  • Loss: 2.2894
  • Rouge1: 0.4161
  • Rouge2: 0.1838
  • Rougel: 0.2786
  • Rougelsum: 0.2791
  • Gen Len: 149.0

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: 1e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • 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 2.4737 0.3984 0.1645 0.261 0.2607 144.9718
No log 2.0 496 2.3435 0.4126 0.1783 0.2762 0.2764 148.754
3.4184 3.0 744 2.3004 0.4162 0.1814 0.2765 0.2767 149.0
3.4184 4.0 992 2.2894 0.4161 0.1838 0.2786 0.2791 149.0

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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