It’s a point of debate: Text for warning message
I was talking to someone in a similar situation (they were wondering about iteratively increasing adapt_delta). For them it turned out just running with a higher adapt delta wasn’t much slower than the base adapt delta.
Following up on what @torkar said, there’s a few things you can do to try to figure out what is causing the divergences.
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Fit with a smaller amount of data so you can iterate faster. It sounds like you’re doing that already though and you’re getting divergences. Did you get divergences with the full dataset?
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Figure out a set of data that gives you divergences. Try tightening your priors with this model or simplifying bits of the model until the divergences go away. If you can find the part of the model that is causing the divergences, maybe there’s a way to fix it.
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Simulate small datasets from your model and see if you get divergences fitting it. When you simulate data from your model, just use estimated parameters from a previous fit so you’re in the ballpark of where you think you need to be.