Some mistakes in generating niid mnist data about pfedme HOT 11 OPEN

Thank you for your suggestion and sorry for the late reply, I didn't get the notification for the issue. I haven't tested the new code. Could you make a pull request with your update and then I can check the correctness?

from pfedme.

Hello, author. I run the code directly without change, but the loss value has always been 2.3. Why. I use cifar10, and every model is like this

from pfedme.

same for me, loss stays on 2.3

from pfedme.

Hello, author. I run the code directly without change, but the loss value has always been 2.3. Why. I use cifar10, and every model is like this

Hello, I also ran into this problem, did you solve it afterwards? thx

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

What about u, buddy?I've been stuck in this for a long time

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

What about u, buddy?I've been stuck in this for a long time

I found that it just due to the model is too simple and unable to learn.

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

What about u, buddy?I've been stuck in this for a long time

I found that it just due to the model is too simple and unable to learn.

u mean the model "CNNCifar" in models.py?I did think it cannot train because of the model, but I don't notice the simplicity and construction of it. Could you offer any good suggestions regarding this? Thank you very much.

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

What about u, buddy?I've been stuck in this for a long time

I found that it just due to the model is too simple and unable to learn.

u mean the model "CNNCifar" in models.py?I did think it cannot train because of the model, but I don't notice the simplicity and construction of it. Could you offer any good suggestions regarding this? Thank you very much.

I was working on federated learning for my final year project and also learning about it. I forked the pFedMe repo and did some simple work and tries on it. You may visit my work if you are interested. Just the commit message and code maybe a bit messy since the repo is for my personal use.

from pfedme.

same for me, loss stays on 2.3

Hello, I also ran into this problem, did you solve it afterwards? thx

Did anyone solve this issue.....? I also stuck in this problem....

What about u, buddy?I've been stuck in this for a long time

I found that it just due to the model is too simple and unable to learn.

u mean the model "CNNCifar" in models.py?I did think it cannot train because of the model, but I don't notice the simplicity and construction of it. Could you offer any good suggestions regarding this? Thank you very much.

I was working on federated learning for my final year project and also learning about it. I forked the pFedMe repo and did some simple work and tries on it. You may visit my work if you are interested. Just the commit message and code maybe a bit messy since the repo is for my personal use.
That would be great if I could learn from you! I'm currently studying the pFedMe paper in depth, but there are still many aspects I don't understand. I hope to have the opportunity to learn and exchange ideas with you when you have time.

from pfedme.