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bart-large-xsum-dc

This model is a fine-tuned version of facebook/bart-large-xsum on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6335
  • Rouge1: 32.0323
  • Rouge2: 14.1008
  • Rougel: 24.5596
  • Rougelsum: 25.6498

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: 5.6e-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
1.9052 1.0 2676 1.7569 30.4785 12.762 23.1862 23.9824
1.4258 2.0 5352 1.5930 31.7087 13.5933 23.9115 24.7093
1.1141 3.0 8028 1.5729 32.3123 14.3572 24.8666 25.856
0.8621 4.0 10704 1.6335 32.0323 14.1008 24.5596 25.6498

Framework versions

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