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LeNet5-experimental
makiisthebes/LeNet5-experimental
LeNet5-experimental is a machine learning model from makiisthebes. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
Architecture is given, learning based on Deep Learning module. Best accuracy found is 99.06% based on these methods and architecture given.
Access
Public
Updated Feb 6, 2024
Repo size
55.1 MB
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At a glance
- License
- mit
- Access
- Public
- Created
- Feb 6, 2024
- Updated
- Feb 6, 2024
- SHA
- 9185b48e
Model card
From the Hugging Face model README
LeNet5
<!-- Provide a quick summary of what the model is/does. -->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
<!-- Provide a longer summary of what this model is. -->Experimented with LeNet5 implemented in PyTorch, using dataloader from dataset files, Main experiments include:
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Normalising dataset with mean and std of training dataset.
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Applying data augmentations of 35 degrees rotation and affine.
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Xavier Initialisation of Parameters.
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Increasing and Descreasing Angles
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Appling inverse Laplacian filter to enhance image.
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Not sure if model is overfitting thus need graph per training.
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Developed by: Michael Peres
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Model type: LeNet5
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Language(s) (NLP): English
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License: MIT
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Finetuned from model: LeNet5
Uses
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->- Hardware Type: RTX 3070Ti
- Hours used: 0.35h
- License
- mit
- Created
- Feb 6, 2024
- Updated
- Feb 6, 2024