ai-detector-distilbert

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

  • Train Loss: 0.0079
  • Train Accuracy: 0.9983
  • Validation Loss: 0.0156
  • Validation Accuracy: 0.9958
  • Train Lr: 1e-07
  • Epoch: 2

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': 'RMSprop', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': 100, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': 1e-07, 'rho': 0.9, 'momentum': 0.0, 'epsilon': 1e-07, 'centered': False}
  • training_precision: float32

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Train Lr Epoch
0.0921 0.9652 0.0141 0.9963 1e-05 0
0.0098 0.9974 0.0178 0.9956 1e-06 1
0.0079 0.9983 0.0156 0.9958 1e-07 2

Framework versions

  • Transformers 4.39.3
  • TensorFlow 2.15.0
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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