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t5-small-destination-inference

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6668
  • Rouge1: 25.6235
  • Rouge2: 0.0
  • Rougel: 25.6064
  • Rougelsum: 25.6064

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
2.6932 1.0 2927 2.0668 19.9009 0.0 19.9009 19.8838
2.1793 2.0 5854 1.8923 22.2668 0.0 22.2583 22.2412
2.0209 3.0 8781 1.8088 23.1807 0.0 23.1893 23.1978
1.9254 4.0 11708 1.7439 24.5815 0.0 24.5815 24.5815
1.8585 5.0 14635 1.7105 24.7865 0.0 24.7865 24.7865
1.814 6.0 17562 1.6863 25.2989 0.0 25.316 25.2989
1.781 7.0 20489 1.6730 25.3844 0.0 25.3844 25.3502
1.7679 8.0 23416 1.6668 25.6235 0.0 25.6064 25.6064

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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