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legal_text_summarizer

This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5451
  • Rouge1: 0.1861
  • Rouge2: 0.1106
  • Rougel: 0.1654
  • Rougelsum: 0.17
  • Gen Len: 20.0

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: 2e-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: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 124 1.6742 0.1765 0.1017 0.1569 0.1611 20.0
No log 2.0 248 1.5853 0.1829 0.1059 0.1618 0.1661 20.0
No log 3.0 372 1.5608 0.1745 0.1041 0.156 0.1597 20.0
No log 4.0 496 1.5451 0.1861 0.1106 0.1654 0.17 20.0

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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