You'd have to give me an example. If less training performs better, it's because it's overfitting. In the case of NLP/CV you, in general, cannot really "overfi

You'd have to give me an example. If less training performs better, it's because it's overfitting. In the case of NLP/CV you, in general, cannot really "overfit" because most of the goal isnt predictive, but rather representational -- so training=templating, rather than predicting. In these cases training for longer should mostly improve the quality of the output, since there isnt any ground truth to overfit against.