classification.jittor

Classification on CIFAR-10/100 and ImageNet with Jittor.

Features

• Unified interface for different network architectures
• Training progress bar with rich info
• visualize the training state.

Install

1. Download the CIFAT-10 Dataset and put it into ./data/cifar
2. Run commond to run

python cifar_train.py --model resnet18 --cuda

Result

Top1 error rate on the CIFAR-10/100 benchmarks are reported. .

• Note that the number of parameters are computed on the CIFAR-10 dataset.

Model	CIFAR-10 (%)	CIFAR-100 (%)
ResNet18	92.04%	-
SENet18	91.58%	-