Image Classification
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metadata
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

    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 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.