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In PyTorch, calling model.train does not train your model. It only switches the model into training mode so certain layers behave differently. For example, dropout turns on and batch norm uses batch stats. You still need a training loop where you run a forward pass, compute a loss, call loss.backward, and then step the optimizer to update the ...
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