CoolFace
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jleem/deberta_core_technology

sourceHugging Facemitupdated 1y agoView on Hugging Face
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Model Card

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debertacoretechnology

This model is a fine-tuned version of kisti/korscideberta on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.6353
  • Accuracy: 0.7619

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: 1.5e-05
  • trainbatchsize: 32
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Use adamwtorch with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • lrschedulerwarmup_steps: 500
  • num_epochs: 50
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
0.370416.66671000.81230.7143
0.126533.33332001.05350.7619
0.010150.03003.63530.7619

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1