szagoruyko / Cifar.torch
Licence: mit
92.45% on CIFAR-10 in Torch
Stars: ✭ 167
Programming Languages
lua
6591 projects
cifar.torch
Newer version of this code is included in https://github.com/szagoruyko/wide-residual-networks
The code achieves 92.45% accuracy on CIFAR-10 just with horizontal reflections.
Corresponding blog post: http://torch.ch/blog/2015/07/30/cifar.html
Accuracies:
| No flips | Flips --- | --- | --- VGG+BN+Dropout | 91.3% | 92.45% NIN+BN+Dropout | 90.4% | 91.9%
Would be nice to add other architectures, PRs are welcome!
Data preprocessing:
OMP_NUM_THREADS=2 th -i provider.lua
provider = Provider()
provider:normalize()
torch.save('provider.t7',provider)
Takes about 30 seconds and saves 1400 Mb file.
Training:
CUDA_VISIBLE_DEVICES=0 th train.lua --model vgg_bn_drop -s logs/vgg
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