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A Multilayer Perceptron (MLP) Neural Network is trained on MNIST dataset using Pytorch LIghtning library

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MNIST_Pytorch_Lightning

A Multilayer Perceptron (MLP) Neural Network is trained using Pytorch LIghtning library. MNIST and Fashion MNIST datasets are used to trian the neural network.

Different Experiments are performed and results are observed. Type of experiments and validation accuracy of network is given below:

Version 0: Batch_SIze: 8 Hidden_Layers: 1 Hidden Neurons: 1024 Optimizer: SGD Sigmoid Val_Acc: 0.9527

Version 1: Batch_SIze: 8 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: SGD Sigmoid Val_Acc: 0.9552

Version 2: Batch_SIze: 16 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: SGD Sigmoid Val_Acc: 0.9377 Increasing

Version 3: Batch_SIze: 32 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: SGD Sigmoid Val_Acc: 0.9298 Increasing

Version 4: Batch_SIze: 32 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: SGD Relu Val_Acc: 0.9739

Version 5: Batch_SIze: 32 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: Adam Relu Val_Acc: 0.9763

Version 6: Batch_SIze: 32 Hidden_Layers: 1 Hidden Neurons: 512 Optimizer: Adam Relu Val_Acc: 0.9835 With Augmentation

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A Multilayer Perceptron (MLP) Neural Network is trained on MNIST dataset using Pytorch LIghtning library

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