---
license: apache-2.0
language:
- en
---
# Model Description

The LeNNon_smile_detector model is used to detect smiling and not-smiling faces.

The model was trained with CelebA dataset. 

## Details

- Dataset: [CelebFaces Attributes](https://www.kaggle.com/datasets/jessicali9530/celeba-dataset/)
  
  The creators of the dataset wrote the following paper employing CelebA for face detection:
  S. Yang, P. Luo, C. C. Loy, and X. Tang,
  "From Facial Parts Responses to Face Detection: A Deep Learning Approach", in IEEE International Conference on Computer Vision (ICCV), 2015.
- Language: English
- Number of Training Steps: 20
- Batch size: 32
- Optimizer: Adam
- Learning Rate: 0.001
- GPU: T4
- This repository has the source [code used](https://github.com/Nkluge-correa/teeny-tiny_castle/blob/master/ML%20Fairness/fair_metrics_celeba.ipynb) to train this model.


## Performance

Final Validation Accuracy: 90.56% Final Validation Loss: 0.6397

# Cite as 🤗
```
@misc{teenytinycastle,
    doi = {10.5281/zenodo.7112065},
    url = {https://huggingface.co/AiresPucrs/LeNNon_smile_detector},
    author = {Nicholas Kluge Corr{\^e}a},
    title = {Teeny-Tiny Castle},
    year = {2023},
    publisher = {HuggingFace},
    journal = {HuggingFace repository},
}
```
## License
The LeNNon_smile_detector model is licensed under the Apache License, Version 2.0. See the LICENSE file for more details.