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