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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, and Optuna. MLflow, DVC, YAML files and the Hydra framework are used.

yaml deep-learning logging cnn pytorch configuration-management hydra image-classification vit hyperparameter-tuning cifar10 cifar100 dvc mlflow optuna ablation-studies pytorch-lightning gmlp dataclasses-python
  • Updated Aug 15, 2024
  • Python

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