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pegasus-large-samsum

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

  • Loss: 1.4109
  • Rouge1: 48.0968
  • Rouge2: 24.6663
  • Rougel: 40.2569
  • Rougelsum: 44.0137

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 64
  • total_train_batch_size: 64
  • 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
No log 1.0 230 1.4646 45.0631 22.5567 38.0518 41.2694
No log 2.0 460 1.4203 47.4122 24.158 39.7414 43.3485
1.699 3.0 690 1.4109 48.0968 24.6663 40.2569 44.0137

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train RobertoFont/pegasus-large-samsum

Evaluation results