The first table is a set of statistics like R-square, mean square error, mean absolute percentage error etc that decribe how well the model fits the data. The acfs and pacfs are presented for the residuals. If the model is reasonable the residuals will look like white noise (independent zero mean random variables) which means that the acf and pacf are theoretically 0 at all non-zero lags. The sample estimates in your case indicate that the residuals do not have significant lagged acfs and pacfs. So that is good for the model.
The model parameter block show which AR and MA terms were fit, the value of their coefficients, the standard error of the estimate, the t statistic for the significance test and the p-values for the test of the null hypothesis that these coefficients are different fromthe coefficient is 0. The other covariates that you included in the model are also given with their parameter estimates and p-values. There is one AR term at lag 2 and moving average terms at lag 7, lag 9, and lag 17.