LeNet5
Architecture is given, learning based on Deep Learning module.
Best accuracy found is 99.06% based on these methods and architecture given.
Model Details
Model Description
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
- Hardware Type: RTX 3070Ti
- Hours used: 0.35h
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API:
The model has no library tag.