Fashion MNIST (https://github.com/zalandoresearch/fashion-mnist) classifier.
$ python src/train.py -g 0
Options:
-g (--gpu) <int>: Optional
GPU device ID. Negative value indicates CPU (default: -1)-m (--model) <model file path>: Optional
Model file path to load (default: None)-b (--batch_size) <int>: Optional
Mini batch size (default: 128)-p (--prefix) <str>: Optional
Prefix of saved model file. (default:fashion_<base size>)--epoch <int>: Optional
Training epochs (default: 300)--save-epoch <int>: Optional
Epoch interval to save model parameter file. 0 indicates model parameter is not saved at fixed intervals. Note that the best accuracy model is always saved even if this parameter is 0. (default: 0)--optimizer <str>: Optional
Optimizer name (sgdoradam, default: sgd)--lr <float>: Optional
Initial learning rate for SGD (default: 0.1)--alpha <float>: Optional
Initial alpha for Adam (default: 0.001)--lr-decay-iter <int>: Optional
Iteration interval to decay learning rate. Learning rate is decay to 1/10 at this intervals. (default: 100)--weight-decay <float>: Optional
Weight decay (default: 0.0001)--seed <int>: Optional
Random seed (default: 1)
- VGG like neural network model
- Data augmentation
- random crops
- random horizontal flips
- random erasing (see https://arxiv.org/abs/1708.04896)
MIT license
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