t5-small-finetuned-summarization-cnn

This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:

  • Loss: 2.0105
  • Rouge1: 24.4825
  • Rouge2: 9.1573
  • Rougel: 19.7135
  • Rougelsum: 22.2551

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: 2

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.0389 1.0 718 2.0150 24.4413 9.1782 19.7202 22.2225
1.9497 2.0 1436 2.0105 24.4825 9.1573 19.7135 22.2551

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.0
  • Tokenizers 0.13.2
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Dataset used to train Alred/t5-small-finetuned-summarization-cnn

Evaluation results