In contrast, generative models are trained to maximize the joint probability of the training data, which is not as closely tied to the accuracy metrics of interest if the actual data was not generated by the model, as is always the case in practice.
since sequential classifiers are trained to make the best local decision, unlike generative models they cannot trade off decisions at different positions against each other.