license:mit region:us
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license: mit
---

# LeNet5

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Architecture is given, learning based on Deep Learning module.
Best accuracy found is `99.06%` based on these methods and architecture given.

## Model Details

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6319030647a84df2a5dd106c/1ea8h0ejxJBJE5R3Sib9B.png)


### Model Description

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Experimented with LeNet5 implemented in PyTorch, using dataloader from dataset files,
Main experiments include:

- Normalising dataset with mean and std of training dataset.
- Applying data augmentations of 35 degrees rotation and affine.
- Xavier Initialisation of Parameters.
- Increasing and Descreasing Angles
- Appling inverse Laplacian filter to enhance image.
- Not sure if model is overfitting thus need graph per training.


- **Developed by:** Michael Peres
- **Model type:** LeNet5
- **Language(s) (NLP):** English
- **License:** MIT
- **Finetuned from model:** LeNet5


## Uses

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- **Hardware Type:** RTX 3070Ti
- **Hours used:** 0.35h
