You can deploy this model and start earning money today!

ayatsuri/
academic-ai-detector

Name: academic-ai-detector
Availability: InStock

transformers

distilbert

text-classification

generated_from_keras_callback

NicolaiSivesind/human-vs-machine

distilbert/distilbert-base-uncased

Views

No views yet

ayatsuri/academic-ai-detector

This model is a fine-tuned version of distilbert/distilbert-base-uncased on NicolaiSivesind/human-vs-machine dataset. It achieves the following best results on the evaluation set:

Train Loss: 0.0910
Validation Loss: 0.0326
Train Accuracy: 0.9937
Train Recall: 0.9927
Train Precision: 0.9947
Train F1: 0.9937
Validation Accuracy: 0.99
Validation Recall: 0.986
Validation Precision: 0.9940
Validation F1: 0.9900
Epoch: 0

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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2625, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
training_precision: float32

Training results

Set	Loss	Accuracy	Recall	Precision	F1
Train	0.0910	0.9937	0.9927	0.9947	0.9937
Validation	0.0326	0.99	0.986	0.9940	0.9900

Framework versions

Transformers 4.41.1
TensorFlow 2.15.0
Datasets 2.19.1
Tokenizers 0.19.1

Citation

Please use the following citation:

@misc {ayatsuri24,
  author    = { Bagas Nuriksan },
  title     = { Academic AI Detector },
  url       = { https://huggingface.co/ayatsuri/academic-ai-detector }
  year      = 2024,
  publisher = { Hugging Face }
}