Open Nancy0577 opened 3 years ago
How many runs have you tried?
From memory, convergence is highly dependent on the seed.
If it is not on track to converging early in training, just run it again.
I had tried 10 runs. And what's your best accuracy that you have got before?
From memory about 70% precision for MNIST. 1's and 7's were difficult to split right, 0's and 8's also...
On Tue, Dec 22, 2020 at 6:47 PM Nancy0577 notifications@github.com wrote:
I had tried 10 runs. And what's your best accuracy that you have got before?
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How about your best accuracy on cifar10?
Oh yeah, nowhere near that good on CIFAR. Probably about 30% or something like that.
I think the background messes things up quite a bit, as the mutual information over the entire image gets dominated by the background.
It works well on MNIST because the shape is the only source of information, and the shapes are quite distinct.
Natural images would be quite a bit harder I think.
Sorry :) heh..
I should have done a better writeup on this project.. but things move so fast, I'm often quick to rush to the next cool thing :)
On Tue, Dec 22, 2020 at 8:10 PM Nancy0577 notifications@github.com wrote:
How about your best accuracy on cifar10?
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This project is really good! And what's your clustering method? K-means? What is your accuracy? Purity, Precision or others?
Here's the paper I was reproducing from. It's an information theory based algorithm called Invariant Information Clustering. https://arxiv.org/abs/1807.06653
On Wed, Dec 23, 2020 at 1:38 AM Nancy0577 notifications@github.com wrote:
This project is really good! And what's your clustering method? K-means? What is your accuracy? Purity, Precision or others?
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Hi, I only can get around 30% of accuracy after 200 epochs. Could you please show me your parameters which can get over 50%?
Thanks