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How to remove data Overfitting Issue in my training model

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Naitik
Naitik el 12 de Abr. de 2024
Respondida: Ayush Modi el 12 de Abr. de 2024
I am working on project of facial recognisation of endangered species and I am getting mini batch accuracy of 100% , I am using AlexNet for training. The number of images of endangered species I am using is African elephant with count of 470. Even after do argumantation mini batch accuracy is still same. Help me to remove this overfitting.
Dataset Link: Dataset
Data Training Code:
net = alexnet;
layers = [imageInputLayer([227 227 3])
net(2:end-3)
fullyConnectedLayer(1)
softmaxLayer
classificationLayer()
];
opt = trainingOptions('sgdm', 'MaxEpochs', 100, 'InitialLearnRate', 0.0001,'Plots','training-progress');
training = trainNetwork(trainData,layers,opt);

Respuestas (1)

Ayush Modi
Ayush Modi el 12 de Abr. de 2024
Hi Naitik,
I found similar question in the community -
Also, refer to the following MathWorks documentation for more information on how to avoid overfitting:
Hope this helps!

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