about hyperparameter setting and detail about mtag HOT 5 CLOSED

Hi @ztqwdk, thanks for your interest in our work! Note that you might be looking at the validation results when you directly run run.sh. To evaluate on the test set, please take a look at #1. Also please take a look at the appendix of the paper for the hyperparameters used for each dataset. Let me know if you need additional help!

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Hi @ztqwdk, thanks for your interest in our work! Note that you might be looking at the validation results when you directly run run.sh. To evaluate on the test set, please take a look at #1. Also please take a look at the appendix of the paper for the hyperparameters used for each dataset. Let me know if you need additional help!

Thanks for your reply @jedyang97 . Yes, I have noticed the #1 and I have evaluated on the test set.
And the hyperparameter in run.sh, the default parameters in main.py, and the hyperparameters in the appendix, these three kinds of settings are all different. That made me confused.
If it is convenient, could you please tell me specifically every args of main.py ?

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@ztqwdk I believe the ones in the appendix should be the ones to use.

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@jedyang97 The appendix tells me batch size, initial learning rate, optimizer, MTAG layers, attention heads, node embedding dimension, edge pruning keep percentage, and epochs. But there are still some other config settings in the args of main.py.
I hope to get the whole ‘run.sh' file or specifical every args to make sure that I would not miss any detail.
Thanks for your reply.

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@ztqwdk I compiled a more comprehensive hyperparameter list (along with each setting's performance we obtained) in this Google Sheet. For any parameters that are not specified here, we used the default values in main.py.

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