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t5-base-destination-inference

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

  • Loss: 1.4240
  • Rouge1: 29.0369
  • Rouge2: 0.0
  • Rougel: 29.0007
  • Rougelsum: 28.9826

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
2.1788 1.0 2762 1.6737 21.7686 0.0 21.7958 21.7596
1.7176 2.0 5524 1.5569 24.6017 0.0 24.6017 24.5474
1.556 3.0 8286 1.4978 26.05 0.0 26.05 26.0319
1.4456 4.0 11048 1.4613 26.937 0.0 26.937 26.8827
1.3661 5.0 13810 1.4351 28.2223 0.0 28.2223 28.2042
1.3045 6.0 16572 1.4196 27.9508 0.0 27.9146 27.8965
1.2519 7.0 19334 1.4211 28.8559 0.0 28.8378 28.8197
1.2262 8.0 22096 1.4240 29.0369 0.0 29.0007 28.9826

Framework versions

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