Requests on pretrain code and experimental settings for other datasets
JoonHo-Jang opened this issue · 2 comments
Dear authors,
I have requests on several things I already sent an email to author.
- Could you release the pretraining code for the datasets other than CIFAR10?
- It would be pleasure if you provide the pretrain code and its corresponding experimental settings such as epochs, architecture, and learning rate on Office-Home or PACS.
- Could you release 'parameter.py' for each model/dataset in terms of standard settings ?
- the standard setting I said refers to the setting utilized in Table 2, including the pre-train codes (and settings) for each dataset.
My requests are just for reproducing the results in Table 2 of your paper.
I hope this requests do not disturb you much.
Thank you.
Best,
Hey JoonHo,
As per your request, I have released an improved pretraining script that can support pretraining on all of benchmark datasets appeared in our paper except ImageNet. You can check it out in \pretrain
.
I am unable to access the server I stored experiment logs before due to an unexpected vpn issue, so this time I cannot release the parameters you requested. I will update it asap once the vpn issue is resolved.
Hey JoonHo,
We have released a set of experimental setups in exps
we used to create Table 2 in the paper. In fact, we mainly care about the part of common hyperparameters which are relevant to each adaptation process, such as lr
and n_train_steps
as illustrated in our paper.
These setup scripts need to work with a experimental pipeline based on tmux
. We have also provided this pipeline in our codebase and you can check out the updated README documentation to see how to use it.
Hope this information helps!