New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
GPU memory required to train r100 #5
Comments
you mean resnet100? you can easily change the batchsize in the configuration if you face a memory issue, I hava 100 batchsize in resnet100 training |
Thank you for your reply. Yes, I mean resnet100. My GPU is one Titan xp. I can change batchsize to 64 when backbone is resnet50. I want to try resnet100 and larger batchsize for better results. So I want to know the minimum GPU memory required. Maybe I can change a better to GPU? |
简单一点,如果你想要用大一点的batchsize,就直接把设置改了跑起来,然后用nvidia-smi 命令查看显存占用,多试几次就知道最大能放多少batchsize了,我一般是不会去算一个batch要占用多少显存的。提醒你batchsize不是越大越好的,而且改大了batchsize, learning rate也要调大。 |
谢谢 |
So what is the corresponding paras for the accuracy data mentioned in this repo? |
Thank you for your great work! However, I met a problem about limitation of GPU memory. Can you give me some suggestion about the minimum GPU memory required to train r100 ArcFace by your code?
The text was updated successfully, but these errors were encountered: