How to interpret the results of a logistic regression model? Or, what are the meanings of the different betas in a logistic regression model?

β0 is the baseline in a logistic regression model. It is the log odds for an instance when all the attributes (X1,X2,X3,...,Xn) are zero. In practical scenarios, the probability of all the attributes being zero is very low. In another interpretation, β0 is the log odds for an instance when none of the attributes is taken into consideration.

All the other Betas are the values by which the log odds change by a unit change in a particular attribute by keeping all other attributes fixed or unchanged (control variables).