|
--- |
|
license: apache-2.0 |
|
base_model: distilbert/distilbert-base-uncased |
|
tags: |
|
- generated_from_keras_callback |
|
model-index: |
|
- name: ayatsuri/academic-ai-detector |
|
results: [] |
|
datasets: |
|
- NicolaiSivesind/human-vs-machine |
|
metrics: |
|
- accuracy |
|
- recall |
|
- precision |
|
- f1 |
|
pipeline_tag: text-classification |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# ayatsuri/academic-ai-detector |
|
|
|
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on [NicolaiSivesind/human-vs-machine](https://huggingface.co/datasets/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 } |
|
} |
|
``` |
