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xlnet-base-cased_fold_7_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: 1.7774
  • F1: 0.8111

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 0.4189 0.7903
0.432 2.0 576 0.3927 0.8045
0.432 3.0 864 0.4868 0.8108
0.2573 4.0 1152 0.6763 0.8019
0.2573 5.0 1440 0.8132 0.8105
0.1612 6.0 1728 0.8544 0.8086
0.0972 7.0 2016 1.1274 0.8109
0.0972 8.0 2304 1.2622 0.8056
0.0515 9.0 2592 1.3398 0.8013
0.0515 10.0 2880 1.5421 0.8082
0.0244 11.0 3168 1.4931 0.8042
0.0244 12.0 3456 1.5744 0.8045
0.0287 13.0 3744 1.4169 0.8091
0.0255 14.0 4032 1.5790 0.7999
0.0255 15.0 4320 1.6094 0.7994
0.0098 16.0 4608 1.5758 0.8006
0.0098 17.0 4896 1.5326 0.8140
0.0203 18.0 5184 1.6431 0.8114
0.0203 19.0 5472 1.7105 0.8072
0.0104 20.0 5760 1.6353 0.8139
0.0062 21.0 6048 1.6762 0.8108
0.0062 22.0 6336 1.7076 0.8106
0.0088 23.0 6624 1.7887 0.8035
0.0088 24.0 6912 1.7731 0.8099
0.0026 25.0 7200 1.7774 0.8111

Framework versions

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