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pegasus-large-finetune-xsum

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

  • Loss: 10.0826
  • Rouge1: 5.0462
  • Rouge2: 0.6914
  • Rougel: 3.5071
  • Rougelsum: 3.9548

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: 3

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
11.4044 1.0 13 10.7501 5.5154 0.5561 3.8425 4.2435
10.5741 2.0 26 10.2309 5.4282 0.7228 3.5759 4.0538
10.0146 3.0 39 10.0826 5.0462 0.6914 3.5071 3.9548

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.13.0
  • Datasets 2.6.1
  • Tokenizers 0.11.0
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Dataset used to train Paligonshik/pegasus-large-finetune-xsum

Evaluation results