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bart-base-finetuned-CNN-DailyNews

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: 0.9584
  • Rouge1: 0.1977
  • Rouge2: 0.1321
  • Rougel: 0.1792
  • Rougelsum: 0.1884

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: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.6767 1.0 63 1.8911 0.1745 0.0915 0.1536 0.1644
2.0691 2.0 126 1.5904 0.1777 0.1003 0.1579 0.1677
1.8047 3.0 189 1.3652 0.1778 0.1029 0.1587 0.1663
1.6345 4.0 252 1.2317 0.1959 0.1226 0.1751 0.1842
1.4837 5.0 315 1.1099 0.2015 0.1265 0.1796 0.1911
1.3904 6.0 378 1.0267 0.2004 0.1278 0.1799 0.1893
1.2876 7.0 441 0.9788 0.1978 0.1307 0.1784 0.1878
1.2578 8.0 504 0.9584 0.1977 0.1321 0.1792 0.1884

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1
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