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xlnet-base-cased_fold_8_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: 1.5333
  • F1: 0.8407

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 1.0 290 0.3866 0.8172
0.4299 2.0 580 0.4215 0.8246
0.4299 3.0 870 0.4765 0.8238
0.2564 4.0 1160 0.7283 0.8350
0.2564 5.0 1450 0.6825 0.8363
0.1553 6.0 1740 0.9637 0.8339
0.0893 7.0 2030 1.1392 0.8239
0.0893 8.0 2320 1.1868 0.8231
0.0538 9.0 2610 1.2180 0.8346
0.0538 10.0 2900 1.2353 0.8253
0.0386 11.0 3190 1.1883 0.8317
0.0386 12.0 3480 1.2786 0.8375
0.0289 13.0 3770 1.3725 0.8375
0.0146 14.0 4060 1.3171 0.8463
0.0146 15.0 4350 1.2323 0.8425
0.0182 16.0 4640 1.3169 0.8485
0.0182 17.0 4930 1.4424 0.8336
0.0125 18.0 5220 1.4336 0.8385
0.0102 19.0 5510 1.4888 0.8405
0.0102 20.0 5800 1.5227 0.8419
0.0035 21.0 6090 1.4994 0.8421
0.0035 22.0 6380 1.4845 0.8424
0.0047 23.0 6670 1.5006 0.8422
0.0047 24.0 6960 1.5468 0.8422
0.0042 25.0 7250 1.5333 0.8407

Framework versions

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