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t5-base-news_headlines

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

  • Loss: 0.9299
  • Rouge1: 55.5197
  • Rouge2: 37.289
  • Rougel: 52.5423
  • Rougelsum: 52.5447

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: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.9936 1.0 1531 1.5027 44.1546 22.1175 40.3432 40.2843
1.6014 2.0 3062 1.2953 46.5025 25.0728 43.0053 43.0156
1.4043 3.0 4593 1.2426 48.2614 27.7433 45.0913 45.0575
1.2605 4.0 6124 1.1145 50.9833 31.0849 47.7984 47.8105
1.1521 5.0 7655 1.0423 53.1185 33.8153 49.9944 50.0043
1.0663 6.0 9186 0.9820 54.3416 35.6212 51.3341 51.3527
1.0089 7.0 10717 0.9346 55.4265 37.1236 52.5535 52.5711
0.9703 8.0 12248 0.9299 55.5197 37.289 52.5423 52.5447

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3
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