| # 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] | |
| <!-- Provide the basic links for the model. --> | |
| - **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 |