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distilbart-cnn-12-6-rate-prof

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

  • Loss: 1.0922
  • Rouge1: 0.3041
  • Rouge2: 0.1196
  • Rougel: 0.2229
  • Rougelsum: 0.2241
  • Gen Len: 66.9333

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: 1e-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: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 68 1.1530 0.2844 0.0943 0.204 0.2027 67.8
No log 2.0 136 1.0948 0.2614 0.0498 0.1672 0.168 67.8
No log 3.0 204 1.0797 0.3042 0.0983 0.2068 0.2082 66.6667
No log 4.0 272 1.0808 0.2932 0.0914 0.2012 0.2024 67.1333
No log 5.0 340 1.0922 0.3041 0.1196 0.2229 0.2241 66.9333

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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