# 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.
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## 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