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ratish/DBERT_CleanDesc_Collision_v2.1.4

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face
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ratish/DBERTCleanDescCollision_v2.1.4

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.3438
  • Validation Loss: 1.4467
  • Train Accuracy: 0.5897
  • Epoch: 11

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:

  • optimizer: {'name': 'Adam', 'weightdecay': None, 'clipnorm': None, 'globalclipnorm': None, 'clipvalue': None, 'useema': False, 'emamomentum': 0.99, 'emaoverwritefrequency': None, 'jitcompile': True, 'islegacyoptimizer': False, 'learningrate': {'classname': 'PolynomialDecay', 'config': {'initiallearningrate': 2e-05, 'decaysteps': 4575, 'endlearningrate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta1': 0.9, 'beta2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train LossValidation LossTrain AccuracyEpoch
1.61481.71510.30770
1.47831.72630.30771
1.39261.67790.41032
1.24621.57780.43593
1.05921.51540.43594
0.88141.53700.46155
0.75541.42500.53856
0.63031.43850.56417
0.54581.38700.48728
0.48081.34590.53859
0.40981.50490.538510
0.34381.44670.589711

Framework versions

  • Transformers 4.28.1
  • TensorFlow 2.12.0
  • Datasets 2.12.0
  • Tokenizers 0.13.3