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07 - Advanced Convolutions

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Session 7 - Advanced Convolutions

Open In Colab

The model reaches a test accuracy of 84.83% in CIFAR-10 dataset. The model uses the following types of convolutions:

  • 3x3 Convolution
  • Pointwise Convolution
  • Atrous Convolution
  • Depthwise Separable Convolution
  • Max Pooling

The model has 94,218 parameters.

Model Architecture

architecture

Parameters and Hyperparameters

  • Loss Function: Cross Entropy Loss
  • Optimizer: SGD
  • Learning Rate: 0.01
  • Dropout Rate: 0.1
  • Batch Size: 64
  • Epochs: 50

Change in Validation Loss and Accuracy

Project Setup

On Local System

Install the required packages
$ pip install -r requirements.txt

On Google Colab

Upload the files in the root folder and select Python 3 as the runtime type and GPU as the harware accelerator.

Group Members

  • Rakhee (Canvas ID: 25180625)
  • Shantanu Acharya (Canvas ID: 25180630)