Thank you @ptrblck
At the risk of exposing myself as a complete novice.  Could you provide a layman’s understanding of what the impact of that large gradient has on the training process?  Do I understand that this will essentially propagate a  greater value back when adjusting the weights?  And could this be balanced out with a much smaller learning rate?  If my batch sizes are always the same will there be a noticeable impact on the ability to converge, because I am perhaps taking too large of a step when adjusting the weight values?
This little tidbit has really helped expose a slightly better understanding of the training process, so thank you very much for shining some light.