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,...,X_n) 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).