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ZCalkins / Model-Performance-and-Tuning-Analysis-on-CIFAR

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Model performance and tuning analysis conducted on the CIFAR10 and CIFAR100 datasets. Convolutional Neural Network (CNN), Gated Multilayer Perceptron (gMLP), and Vision Transformer (ViT) model architectures are utilized. The study is built using PyTorch, PyTorch Lightning for clean and concise code and Optuna for hyperparameter tuning.

yaml deep-learning logging cnn pytorch configuration-management image-classification tensorboard vit hyperparameter-tuning cifar10 cifar100 optuna experiment-tracking ablation-studies pytorch-lightning gin-config gmlp dataclasses-python
  • Updated Jun 30, 2024
  • Python

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