I think you probably don’t want the prior on sigma to be a normal with a negative mean, since the sigma of a lognormal can’t be negative (it would be different if there were predictors on sigma, in which case sigma would be modelled with a log link, and you might want such a negative value).
Also, I would probably use an exponential distribution as priors on “sigma” and “sd”.
(here are some examples from my own work of priors for lognormal/shifted-lognormal models for RTs and naming times:
https://osf.io/preprints/psyarxiv/7wfus_v1
Investigating variability in morphological processing with Bayesian distributional models | Psychonomic Bulletin & Review )