Temporal-Ensembling-for-Semi-Supervised-Learning
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Unable to Reproduce Paper Results with Pi-Model
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.
Hi @iamshahd,
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.