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tidy-tab-model-pegasus-xsum

This model is a fine-tuned version of google/pegasus-xsum on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9644
  • Rouge1: 0.7456
  • Rouge2: 0.6153
  • Rougel: 0.7401
  • Rougelsum: 0.7422
  • Gen Len: 5.2607

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • 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 Gen Len
1.5893 3.7879 500 1.0234 0.7302 0.594 0.7229 0.7244 5.3034
0.9308 7.5758 1000 0.9644 0.7456 0.6153 0.7401 0.7422 5.2607

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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