Remove columns before training
Hi,I see in many examples that we remove unnecessary columns from the dataset, before training.Is it mandatory? I guess Trainer will take the columns produced by the tokenizer anyway (together with the “labels” columns).Is it to save some IOs? I guess transformer does not load unnecessary columns, but not sure then, why in examples, we remove them.Sorry, very beginner question here