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View Code? Open in Web Editor NEW[ICLR 2023] Code for BrainBERT
[ICLR 2023] Code for BrainBERT
My team is trying to reproduce the results of this paper. Our system has 24 GB VRAM capacity and I am trying to reproduce the results but I lately found that my system may not be appropriate for the necessary reproducibility of results. I am able to train results on small patches (~3GB when zipped) but I am not able to train it on the entire dataset as I find the training duration required to be extremely high.
I have found that if I get access to the informtion regarding the GPUs that was used for the results of this paper. It would be really helpful if we get all the hardware specifications used for your research.
Can you please share some demo data so we can at least try to process ours into the required format? Thanks!
Hi there, great work!
You mention in your paper that for BrainBERT pre-training you STFT/Superlet each individual electrode to get time-frequency representations. However, I wanted to know how do you handle multiple electrodes during the fine-tuning stage.
Thank You!
In this function: https://github.com/czlwang/BrainBERT/blob/master/util/mask_utils.py#L28
Shouldn't lines 48-49 come after the for loop on line 52?
Your masked_labels and masked input don't align
Hi, I'm trying to pretrain the model with custom dataset. I saw there is some code under /data for pre-processing data. Is it possble for you to provide some direction on how to process raw EDF file and other necessary meta-data into the form compatible with this project?
Thank you!
Could you please provide how to do fine-tuning? Thank you!
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