Splitting Temporal Data
It sounds likes you have non-stationary data which can be a challenge to model.
One option is to completely discard all older data and only train/test on newer data. This way the model will only capture the newer relationships. This approach assumes there is enough newer data to train a model.
Another option is heavily regularize the model. The goal of regularization  is to increase generalization.