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Image classification using CIFAR10 dataset and diy Convolutional Neural Network backed by PyTorch

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tlvu2697/image-classification-cifar10

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Configuration

  • NVIDIA Tesla K80
  • CUDA-8.0
  • PyTorch-0.4.0

Overview

Parameter v1 v2 v3
batch_size 100 100 100
epochs 100 300 300
eta 1e-2 1e-2 (1e-1, 1e-2, 1e-3)
normalize Yes Yes Yes
train_time ~18 mins ~55 mins ~ 55 mins
train_accuracy 100% 93% 96.73%
test_error 29.96% 25.47% 23.9%

Detail

Model Architecture Note
v1
v2 Replace BatchNorm by Dropout and increase the number of epochs to 300 make the test_error decrease 4.49% compared to the v1 model
v3 Train the model with 3 different learning rates at different epochs make the test_error decrease 1.57% compared to the v2 model

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Image classification using CIFAR10 dataset and diy Convolutional Neural Network backed by PyTorch

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