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flan-t5-small-billsum

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

  • Loss: 1.5675
  • Rouge1: 24.0011
  • Rouge2: 18.8602
  • Rougel: 22.9037
  • Rougelsum: 23.1161
  • 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: 5e-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: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 195 1.6773 22.8625 17.311 21.829 22.0089 19.0
No log 2.0 390 1.6134 23.6942 18.553 22.561 22.8895 19.0
1.9532 3.0 585 1.5882 23.8253 18.7086 22.6519 22.9745 19.0
1.9532 4.0 780 1.5739 24.0178 18.8429 22.9119 23.1471 19.0
1.9532 5.0 975 1.5675 24.0011 18.8602 22.9037 23.1161 19.0

Framework versions

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

Dataset used to train hp1502/Legal_Text_Summarizer

Evaluation results