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xlnet-base-cased_fold_9_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: 1.7204
  • F1: 0.8203

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 1.0 291 0.4045 0.8001
0.4262 2.0 582 0.3914 0.8297
0.4262 3.0 873 0.5050 0.8029
0.2488 4.0 1164 0.7681 0.8007
0.2488 5.0 1455 0.8349 0.8262
0.1483 6.0 1746 0.9045 0.8220
0.0894 7.0 2037 1.1584 0.8165
0.0894 8.0 2328 1.1818 0.8300
0.0389 9.0 2619 1.3332 0.8147
0.0389 10.0 2910 1.2373 0.8285
0.038 11.0 3201 1.3156 0.8234
0.038 12.0 3492 1.3251 0.8341
0.0211 13.0 3783 1.3144 0.8255
0.0158 14.0 4074 1.5686 0.8168
0.0158 15.0 4365 1.5382 0.8185
0.0165 16.0 4656 1.5203 0.8282
0.0165 17.0 4947 1.5352 0.8136
0.0142 18.0 5238 1.4799 0.8243
0.0062 19.0 5529 1.5030 0.8294
0.0062 20.0 5820 1.6264 0.8094
0.0078 21.0 6111 1.6949 0.8122
0.0078 22.0 6402 1.7106 0.8139
0.0043 23.0 6693 1.7234 0.8218
0.0043 24.0 6984 1.7344 0.8208
0.0028 25.0 7275 1.7204 0.8203

Framework versions

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