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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_keras_callback
model-index:
- name: zayuki/computer_generated_fake_review_detection
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# zayuki/computer_generated_fake_review_detection
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0116
- Validation Loss: 0.0731
- Train Accuracy: 0.9780
- Train F1: 0.9781
- Epoch: 2
## Model description
This model was empowered by fine-tuned version of Distilbert and trained on [Amazon Review Dataset](https://osf.io/tyue9/), comprising of computer-generated fake reviews and genuine Amazon reviews. The fake reviews were generated by GPT-2, an AI text algoritm.
This model was trained to detect computer-generated fake reviews which generated by AI text algorithm.
### 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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7580, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Validation Loss | Train Accuracy | Train F1 | Epoch |
|:----------:|:---------------:|:--------------:|:--------:|:-----:|
| 0.1207 | 0.0677 | 0.9723 | 0.9726 | 0 |
| 0.0343 | 0.0736 | 0.9753 | 0.9756 | 1 |
| 0.0116 | 0.0731 | 0.9780 | 0.9781 | 2 |
### Framework versions
- Transformers 4.33.1
- TensorFlow 2.12.0
- Datasets 2.14.5
- Tokenizers 0.13.3
|