kcELECTRA-interview-sentiment-3class

This model is a fine-tuned version of beomi/KcELECTRA-base-v2022 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8481
  • Accuracy: 0.8339
  • Macro F1: 0.7945
  • Weighted F1: 0.8394

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: 3e-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
  • lr_scheduler_warmup_ratio: 0.06
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Macro F1 Weighted F1
0.2666 1.0 999 0.6992 0.8250 0.7866 0.8311
0.0867 2.0 1998 0.6471 0.8406 0.7989 0.8448
0.0447 3.0 2997 0.8481 0.8339 0.7945 0.8394

Framework versions

  • Transformers 4.40.2
  • Pytorch 2.8.0+cu128
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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