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
{{ message }}
This repository has been archived by the owner on Jun 9, 2023. It is now read-only.
First of all, I'd like to thank you tremendously for sharing this clean TensorFlow implementation - it saved me a lot of time!
Second, I am wondering if by any chance you have compared your pi-model results with the original paper. I tried training the pi-model on SVHN using the same hyperparameters reported with 1000 labels, but for some reason the model overfits around the 50th-60th epoch, and the final test accuracy of the best ckpt is only 85%, versus almost 95% in the paper.
The text was updated successfully, but these errors were encountered:
At the time I was not using a good GPU so I was not able to get the exact results as I stated in the docs:
The results are not exactly the ones reported in the paper with 1000 labels, but I have to admit that I do not have the hardware to find the best parameters with structured batches (the experiments were run in a 860M NVIDIA card).
With proper hyperparameter tuning it should be close to the reported results.
Sign up for freeto subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Hi,
First of all, I'd like to thank you tremendously for sharing this clean TensorFlow implementation - it saved me a lot of time!
Second, I am wondering if by any chance you have compared your pi-model results with the original paper. I tried training the pi-model on SVHN using the same hyperparameters reported with 1000 labels, but for some reason the model overfits around the 50th-60th epoch, and the final test accuracy of the best ckpt is only 85%, versus almost 95% in the paper.
The text was updated successfully, but these errors were encountered: