Your R-squared is not too bad but your Ljung-Box statistic shows that your model is not well specified.
"Stationary R-squared: The higher the better"
"Although the Time Series Modeler offers a number of different goodness-of-fit statistics, we
opted only for the stationary R-squared value. This statistic provides an estimate of the proportion
of the total variation in the series that is explained by the model and is preferable to ordinary
R-squared when there is a trend or seasonal pattern, as is the case here. Larger values of stationary
R-squared (up to a maximum value of 1) indicate better fit. A value of 0.948 means that the model
does an excellent job of explaining the observed variation in the series.
The Ljung-Box statistic, also known as the modified Box-Pierce statistic, provides an indication
of whether the model is correctly specified. A significance value less than 0.05 implies that there
is structure in the observed series which is not accounted for by the model. The value of 0.984
shown here is not significant, so we can be confident that the model is correctly specified".