Model Card for aedupuga/image-autogluon-predictor
Model Description
This is an AutoGluon Image AutoML NN implementation on a image dataset containing cover images of books. The model predicts whether the book is "fiction" or "non-fiction".
- Model developed by: Anuhya Edupuganti
- Model type: AutoGluon TabularPredictor
Model Sources [optional]
- Dataset: jennifee/HW1-images-dataset
Direct Use
- This model was intended to practice automl implementation on an image dataset
Bias, Risks, and Limitations
- Small data size. cannot to generallised to all existing books on the market.
Training Data:
The model was trained on the augmented split of the "jennifee/HW1-images-dataset".
Evaluation Data:
The model achieved an accuracy of 1.000 and a weighted F1 score of 1.000 on the original dataset.
Model Card Contact
Anuhya Edupuganti (Carnegie Mellon Univerity)- aedupuga@andrew.cmu.edu