I have a pretty skewed dataset due to the generation of examples using entities. I have a couple of intents (inform among others) that use entities. To train CRF properly I need to generate the same sentence with a different entity all the time. Thus, the inform intent is about 3000 examples long.
Coupling this with intents that don’t use entities (e.g. tell_me_a_joke) makes the model misidentify these smaller intents since these only have about 50 examples (and for the life of me I cannot get any more examples than these 50).
Is there any way to de-skew the model by weighing the smaller intents more for instance?