Intro to stats question (all items are given with a 95% confidence level):

I have a linear regression model with two independent, statistically significant variables (non-correlated, sufficiently high t-stats, etc.). If my R square is .60 and my Adjusted R Square is .56, how should I rate the overall quality of the regression model?

Can I say; "the model has a moderate explanatory power, as the independent variables are both statistically significant and account for 60% (56% with adjusted R-Square) of variance of the dependent variable's values?

Can I use Adjusted R-square in this way? Meaning, can I say that, per the model's Adjusted R-Square, the independent variables explain 56% of the variance in the dependent variable's value? Or is that incorrect to state? If my summary is incorrect, how should I best rate the overall quality of the model using both R-Square and Adjusted R-Square?

Again, this is for an intro to stats exercise, so no need to get too deep on this.