---
license: mit
datasets:
- cifar10
language:
- en
pipeline_tag: image-classification
---

# Image Classifier (trained on CIFAR10)

The model aims to classify images from this dataset into 1 of 10 classes, in which we build a model on the training set & evaluate it on the test set.
The dataset include 10 classes which are: 
 - airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks

with roughly 60,000 images.

CIFAR10 models exist and so the aim here is not for a model that is identical and easy to train, this model has a unique architecture which will be explained.

## Model Details
- **Developed by:** Michael Peres
- **Model type:** Image Classification of CIFAR10 dataset.
- **Language(s) (NLP):** Michael Peres
- **License:** MIT


### Model Architecture

This model has a more unique approach for the architecture,

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6319030647a84df2a5dd106c/M1a1cCnq9cQBminzejk0r.png)


## Uses
This model is just intended as a learning challenge where CIFAR10 is trained on a unconventional architecture.

## How to Get Started with the Model

Use the code below to get started with the model.

Look at provided `main.py` which contains the model and the training code, if you would like to train it.
We are using optuna, to tune the hyperparameters. 
ore Information Needed]
 These are the evaluation metrics being used, ideally with a description of why. -->


## Model Card Contact

https://github.com/makiisthenes

ec20433@qmul.ac.uk