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t5-base-billsum

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

  • Loss: 1.6188
  • Rouge1: 51.4114
  • Rouge2: 30.6521
  • Rougel: 40.9417
  • Rougelsum: 44.6839

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.9236 1.0 1185 1.5895 52.5513 32.239 42.0215 45.9665
1.7231 2.0 2370 1.5380 53.3168 33.2784 42.9286 46.7854
1.6708 3.0 3555 1.5187 53.2982 33.3262 42.979 46.8863
1.7884 4.0 4740 1.6197 51.4854 30.768 41.0231 44.7727
1.8212 5.0 5925 1.6188 51.4114 30.6521 40.9417 44.6839

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.2
  • Tokenizers 0.19.1
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