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plain-bart-on-presummarized-to-story-wcep

This model is a fine-tuned version of sshleifer/distilbart-cnn-6-6 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3683
  • Rouge1: 34.6044
  • Rouge2: 13.4823
  • Rougel: 24.3208
  • Rougelsum: 27.9903
  • Gen Len: 66.4687

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: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.4933 1.0 510 2.3683 34.6044 13.4823 24.3208 27.9903 66.4687

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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