# regression with categorical variable - choice of reference category

I have an OLS with continuous outcome and a mix of continuous/categorical predictors. For categorical predictor X, which has 5 categories, one particular category X_5 dominates in terms of volumes --- it is 70% of the data. The other 4 categories combined are only 30%. When I create dummies for these categories X1,...,X5 and use them in the regression, does it make a difference if I decide to use X_5 as the reference category?

It wont make a difference in terms of model predictions or in terms of measures such as $R^2$, AIC, etc. You can think of the coefficients for the category indicators as offsets to the the intercept, and whatever your base case is there will be a set of values for the intercept and the offsets that give the same set of predictions. Parameter estimation tries to find a set of coefficients that optimize the predictions on the data (usually maximizing likelihood). Since we can get the same intercept+offset values regardless of the base case, the models will be equivalent.