I am doing a GLM regression analysis and have a question about interactions and model fit.

My dependent variable is 'salary', and I have the independent variable as 'years in the workforce'. However, there are data from male and female subjects which could be important. I have included 'gender' as a dummy variable in the analysis, as well as the "gender*years worked" interaction.

I understand how to interpret the beta regression coefficients, but have a question on the model fit (R-square). Let's assume the interaction is statistically significant: my thought is that it would be appropriate to rerun the analysis with male and female separately to obtain 2 different R-squared values. But is the incremental increase in R-squared that accompanies the (significant) interaction useful, and how is it interpreted?

Thanks

William