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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - f1
model-index:
  - name: xlnet-base-cased_fold_1_binary_v1
    results: []

xlnet-base-cased_fold_1_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: 1.7812
  • F1: 0.8161

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 0.3938 0.8019
0.4444 2.0 576 0.3945 0.8086
0.4444 3.0 864 0.4738 0.8245
0.2504 4.0 1152 0.6641 0.8123
0.2504 5.0 1440 0.8714 0.7863
0.159 6.0 1728 0.9177 0.8179
0.0832 7.0 2016 1.1719 0.8129
0.0832 8.0 2304 1.2858 0.8146
0.046 9.0 2592 1.2557 0.8181
0.046 10.0 2880 1.3332 0.8033
0.0313 11.0 3168 1.2840 0.8112
0.0313 12.0 3456 1.4164 0.8175
0.0246 13.0 3744 1.3709 0.8143
0.0173 14.0 4032 1.4319 0.8179
0.0173 15.0 4320 1.5706 0.8195
0.0138 16.0 4608 1.6072 0.8230
0.0138 17.0 4896 1.7454 0.8192
0.0016 18.0 5184 1.7281 0.8099
0.0016 19.0 5472 1.7692 0.8151
0.0088 20.0 5760 1.7376 0.8132
0.0081 21.0 6048 1.7715 0.8086
0.0081 22.0 6336 1.7400 0.8152
0.0053 23.0 6624 1.7845 0.8099
0.0053 24.0 6912 1.8096 0.8150
0.0062 25.0 7200 1.7812 0.8161

Framework versions

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