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xlnet-base-cased_fold_10_binary_v1

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

  • Loss: 1.7782
  • F1: 0.8137

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 288 0.3796 0.8145
0.4196 2.0 576 0.4319 0.7810
0.4196 3.0 864 0.6227 0.8002
0.231 4.0 1152 0.6258 0.7941
0.231 5.0 1440 1.0692 0.7866
0.1307 6.0 1728 1.1257 0.8005
0.0756 7.0 2016 1.2283 0.8072
0.0756 8.0 2304 1.3407 0.8061
0.0486 9.0 2592 1.5232 0.8059
0.0486 10.0 2880 1.6731 0.8053
0.0339 11.0 3168 1.6536 0.8087
0.0339 12.0 3456 1.7526 0.7996
0.019 13.0 3744 1.6662 0.7909
0.0237 14.0 4032 1.6028 0.8071
0.0237 15.0 4320 1.7627 0.7964
0.0078 16.0 4608 1.6513 0.8169
0.0078 17.0 4896 1.7795 0.8039
0.015 18.0 5184 1.8669 0.7935
0.015 19.0 5472 1.6288 0.8118
0.0124 20.0 5760 1.6630 0.8104
0.004 21.0 6048 1.7418 0.8167
0.004 22.0 6336 1.7651 0.8128
0.0043 23.0 6624 1.7279 0.8163
0.0043 24.0 6912 1.8177 0.8093
0.004 25.0 7200 1.7782 0.8137

Framework versions

  • Transformers 4.21.1
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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