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distilbart-cnn-12-6-ftn-multi_news

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the multi_news dataset. It achieves the following results on the evaluation set:

  • Loss: 3.8143
  • Rouge1: 41.6136
  • Rouge2: 14.7454
  • Rougel: 23.3597
  • Rougelsum: 36.1973
  • Gen Len: 130.874

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1
  • mixed_precision_training: Native AMP
  • label_smoothing_factor: 0.1

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.8821 0.89 2000 3.8143 41.6136 14.7454 23.3597 36.1973 130.874

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train datien228/distilbart-cnn-12-6-ftn-multi_news

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Evaluation results