t5-small-finetuned-cnn-news

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

  • Loss: 2.3455
  • Rouge1: 25.2386
  • Rouge2: 9.5343
  • Rougel: 20.6686
  • Rougelsum: 23.2614

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: 0.00056
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.1393 1.0 718 2.4712 23.3266 8.6693 18.9609 21.406
1.7054 2.0 1436 2.2697 24.3337 9.4775 20.1514 22.5425
1.5479 3.0 2154 2.2868 24.3861 9.0245 20.0315 22.582
1.4377 4.0 2872 2.3311 25.0473 9.4761 20.4587 23.0242
1.3533 5.0 3590 2.3455 25.2386 9.5343 20.6686 23.2614

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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