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roberta-base_fold_1_binary_v1

This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4984
  • F1: 0.8339

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 0.3819 0.8117
0.4108 2.0 576 0.3696 0.8281
0.4108 3.0 864 0.4890 0.8343
0.2261 4.0 1152 0.7605 0.8298
0.2261 5.0 1440 0.7754 0.8307
0.1404 6.0 1728 0.7650 0.8174
0.0962 7.0 2016 0.8539 0.8315
0.0962 8.0 2304 1.0770 0.8263
0.0433 9.0 2592 1.1450 0.8292
0.0433 10.0 2880 1.1700 0.8205
0.0344 11.0 3168 1.2376 0.8241
0.0344 12.0 3456 1.2688 0.8329
0.0219 13.0 3744 1.3276 0.8283
0.0123 14.0 4032 1.2930 0.8320
0.0123 15.0 4320 1.4631 0.8266
0.0177 16.0 4608 1.4326 0.8270
0.0177 17.0 4896 1.4770 0.8334
0.0053 18.0 5184 1.5972 0.8214
0.0053 19.0 5472 1.5331 0.8327
0.0045 20.0 5760 1.5487 0.8359
0.0086 21.0 6048 1.4610 0.8315
0.0086 22.0 6336 1.4685 0.8353
0.0071 23.0 6624 1.4933 0.8358
0.0071 24.0 6912 1.4898 0.8310
0.0022 25.0 7200 1.4984 0.8339

Framework versions

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