Wintersmith/LLM_generated_text_detector
This model is a fine-tuned version of distilbert/distilbert-base-uncased-finetuned-sst-2-english on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0082
- Train Accuracy: 0.9974
- Validation Loss: 0.0191
- Validation Accuracy: 0.9941
- Epoch: 1
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': 5e-05, 'decay_steps': 3630, '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-07, 'amsgrad': False}
- training_precision: float32
Training results
Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
---|---|---|---|---|
0.0579 | 0.9809 | 0.0272 | 0.9920 | 0 |
0.0082 | 0.9974 | 0.0191 | 0.9941 | 1 |
Framework versions
- Transformers 4.37.0
- TensorFlow 2.15.0
- Datasets 2.15.0
- Tokenizers 0.15.1
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