motivation
观测用BBN的模式训练出来的模型, 配上不同的(alpha), 结果会如何.
settings
Attribute | Value |
---|---|
attack | pgd-linf |
batch_size | 128 |
beta1 | 0.9 |
beta2 | 0.999 |
dataset | cifar10 |
description | AT=True-0.0=default-sgd-0.1=pgd-linf-0.0314-0.25-10=128=default |
epochs | 100 |
epsilon | 0.03137254901960784 |
eva_alpha | 0.0 |
learning_policy | [50, 75] x 0.1 |
loss | cross_entropy |
lr | 0.1 |
model | resnet32 |
momentum | 0.9 |
norm_cls | True |
optimizer | sgd |
progress | False |
resume | False |
seed | 1 |
stats_log | False |
steps | 10 |
stepsize | 0.25 |
transform | default |
weight_decay | 0.0005 |
results
Accuracy | Robustness | |
---|---|---|
parabolic decay | ||
fixed_alpha=0.5 | ||
fixed_alpha=0.5, 同时对抗样本也是采用alpha=0.5生成的 |
太奇怪了, 为啥会发生这种事情?