Indeed, models can be sensitive to the actual choice of encoders, intercepts etc. It might be the case that changing the distributions that the parameters are drawn from will make your models more robust.
As to the difference between behavior in Spyder and the GUI, I'm not 100% sure, but my guess would be that the Python environment that you're using in Spyder is different from the one in the GUI. You can verify this by running a script in both environments that has the line
It will print out the location of the
python program that ends up being run. If they're not the same, then it's likely that they're using different installation of NumPy. NumPy is how we generate random numbers; I'm not sure about the details of how it draws random numbers, but it's possible that you would get different results with the same seed using different versions of NumPy.