Edit model card

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 }
}
Downloads last month
334
Inference API
This model can be loaded on Inference API (serverless).

Finetuned from

Dataset used to train ayatsuri/academic-ai-detector