cvignac / DiGress

code for the paper "DiGress: Discrete Denoising diffusion for graph generation"
MIT License
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About experiment on Comm20. #77

Open xinyangATK opened 6 months ago

xinyangATK commented 6 months ago

Hello, thanks for your great work! I am trying to reproduce the experiment on comm20 dataset with DiGress. I'm curious about why the number of epochs is so large (1000000) while training the model on comm20. In contrast, training DiGress on other dataset only need epochs far smaller than this. Is there a special case on comm20?

Thanks a lot if you can give me some advice!

cvignac commented 6 months ago

Hello, the number of epochs is large but we don't train until the end. We simply stop the run when validation metrics have converged.

Le jeu. 21 déc. 2023 à 06:31, Xinyang Liu @.***> a écrit :

Hello, thanks for your great work! I am trying to reproduce the experiment on comm20 dataset with DiGress. I'm curious about why the number of epochs is so large (1000000) while training the model on comm20. In contrast, training DiGress on other dataset only need epochs far smaller than this. Is there a special case on comm20?

Thanks a lot if you can give me some advice!

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xinyangATK commented 6 months ago

Thanks for your quick reply.