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xlnet-base-cased_fold_5_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: 1.7395
  • F1: 0.8206

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 0.4246 0.8154
0.4211 2.0 576 0.5181 0.8063
0.4211 3.0 864 0.4939 0.8149
0.2483 4.0 1152 0.6181 0.8227
0.2483 5.0 1440 0.9251 0.8006
0.1512 6.0 1728 0.9639 0.8082
0.0858 7.0 2016 1.1315 0.8074
0.0858 8.0 2304 1.1322 0.8303
0.053 9.0 2592 1.3171 0.8017
0.053 10.0 2880 1.3729 0.8100
0.0325 11.0 3168 1.2708 0.8252
0.0325 12.0 3456 1.5105 0.8242
0.0203 13.0 3744 1.4902 0.8233
0.0179 14.0 4032 1.5874 0.8194
0.0179 15.0 4320 1.5933 0.8135
0.0174 16.0 4608 1.5908 0.8088
0.0174 17.0 4896 1.5692 0.8249
0.0129 18.0 5184 1.6597 0.8167
0.0129 19.0 5472 1.6009 0.8218
0.0095 20.0 5760 1.6962 0.8225
0.0062 21.0 6048 1.7075 0.8182
0.0062 22.0 6336 1.7335 0.8181
0.0077 23.0 6624 1.7175 0.8204
0.0077 24.0 6912 1.7680 0.8187
0.0024 25.0 7200 1.7395 0.8206

Framework versions

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