If dropout is applied during training, I know that dropout rate should be set to 0 through model.eval() when evaluating. Then, are the droppedout weights given random values when evaluated? If so, I think the performance will be worse. Can’t we keep dropout even when we evaluate?
Hi,
Since dropout is random every time it is used, there are not a fixed set of weights that are droppedout. They are all used sometimes during training and so have been trained properly.
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Hi,
Thank you so much!