tinfoilhat0 / defending-against-backdoors-with-robust-learning-rate Goto Github PK

Hi,
I change the model to resnet. However, it seems to fail to defend the backdoor on resnet. I write the code by myself, so I am not sure if I make something wrong with the code.

By the way, vector_to_parameters() and parameters_to_vector() can not be used to update resnet, because model.parameters() omit some parameters in resnet. Do you know why?

Regards.

Please provide a mirror for the datasets links, the uploaded file is no longer available.

hi,when I tried to run python federated.py --data=fmnist --local_ep=2 --bs=256 --num_agents=10 --rounds=200
there is a problem show up

do you have any ideas about it ?

I have tried running tests on the fedemnist dataset with the default parameters from the runner.sh file. In my 500 round tests, the model's accuracy starts to degrade after approximately round 100.

I have ran experiments in two separate environments and have tried tweaking some parameters, but the results I am getting all show the same issue. Here are the library versions I am using:

NVIDIA PyTorch Container version 22.12
PyTorch version 1.14.0+410ce96
Python3 version 3.8.10