nmsc_classifier

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

  • Loss: 0.3765
  • Accuracy: 0.9015
  • F1: 0.9030
  • Precision: 0.8956
  • Recall: 0.9105
  • Auroc: 0.9014

Model description

KLUE/BERT๋ฅผ ์‚ฌ์šฉํ•ด ๋„ค์ด๋ฒ„ ์˜ํ™” ๋ฆฌ๋ทฐ ๋ฐ์ดํ„ฐ์…‹์— ๋Œ€ํ•œ ์ด์ง„๋ถ„๋ฅ˜ ์ˆ˜ํ–‰

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: 128
  • eval_batch_size: 128
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.5.1+cu124
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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