You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
With the commit prior to the unsupervised additions, I am able to easily get 70+% top-1 accuracy using the Kinetics/SLOW_8x8_R50.yaml finetuning config. But with the new unsupervised code, I can barely get 40% top-1 accuracy on Kinetics-400 using the same config and training command.
There are a number of bugs I had to fix for the code to run, but I think there may be more. Could the authors consider carefully examining the new codebase for bugs that were introduced with recent code?
I am also unable to reproduce the results of the MoCo unsupervised model trained with p=2 for 200 epochs, but there are larger issues if supervised R50 no longer works on Kinetics either.
The text was updated successfully, but these errors were encountered:
My commit in #541 had a small bug as noted by XinyuSun's comment. After adding that fix on top of my commit, I am able to achieve proper results on K400 for supervised now. Hope this helps anyone else running into this issue
With the commit prior to the unsupervised additions, I am able to easily get 70+% top-1 accuracy using the
Kinetics/SLOW_8x8_R50.yaml
finetuning config. But with the new unsupervised code, I can barely get 40% top-1 accuracy on Kinetics-400 using the same config and training command.There are a number of bugs I had to fix for the code to run, but I think there may be more. Could the authors consider carefully examining the new codebase for bugs that were introduced with recent code?
run_net.py
. Thus LR scaling doesn't work as nowhere else in the code scales the LR by the number of shards.I am also unable to reproduce the results of the MoCo unsupervised model trained with p=2 for 200 epochs, but there are larger issues if supervised R50 no longer works on Kinetics either.
The text was updated successfully, but these errors were encountered: