How to train with variable number of candidates for multiple choice selection?
# ❓ Questions

## Details
I am trying to train `GPT2DoubleHeadsModel` for the tasks of generation and multiple-choice selection. My dataset has examples with variable number of candidates - some examples have 10 candidates, some have 15, etc.

I wanted to be able to create a single `TensorDataset` object for my dataset and train the model using a `DataLoader` wrapped around this dataset. But clearly, since the number of candidates varies across examples, I am unable to do so.

What is an appropriate way (or best practice) to train `GPT2DoubleHeadsModel` with such a dataset?
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