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LED_multi_lexsum_peft

This model is a fine-tuned version of pszemraj/led-large-book-summary on an allenai/multi_lexsum dataset. It achieves the following results on the evaluation set:

  • Loss: 4.2303
  • Rouge1: 0.3156
  • Rouge2: 0.1258
  • Rougel: 0.1548
  • Rougelsum: 0.185
  • Bert Precision: 0.8468
  • Bert Recall: 0.887
  • Bert F1: 0.8664
  • Gen Len: 949.968

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: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Bert Precision Bert Recall Bert F1 Gen Len
6.2726 1.0 850 4.2979 0.3208 0.1202 0.1551 0.185 0.8724 0.8797 0.876 906.8
4.5041 2.0 1700 4.2303 0.3156 0.1258 0.1548 0.185 0.8468 0.887 0.8664 949.968

Framework versions

  • PEFT 0.10.0
  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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