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bart-base-finetuned-multi-news

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

  • Loss: 2.6353
  • Rouge1: 15.1146
  • Rouge2: 5.3873
  • Rougel: 11.4132
  • Rougelsum: 13.2739

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 7

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.9189 1.0 625 2.4645 15.2063 5.2852 11.5864 13.4208
2.4697 2.0 1250 2.4706 15.3737 5.4725 11.7465 13.5681
2.1831 3.0 1875 2.4789 14.8306 5.0857 11.2416 13.1072
1.9598 4.0 2500 2.5299 15.1744 5.5465 11.6445 13.4053
1.7777 5.0 3125 2.5799 14.9417 5.2124 11.3553 13.1401
1.6454 6.0 3750 2.6028 14.9804 5.333 11.294 13.2385
1.554 7.0 4375 2.6353 15.1146 5.3873 11.4132 13.2739

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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