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WinterExtreme9316 t1_j4skh3m wrote

Why? If you're just adding a category, why not use what you've got and just train the last layer. You mean in case the new category has some unique low-level feature that early layers of network need to extract?

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ed3203 t1_j4slyft wrote

Yes, you may arrive at a different local minima which could be more performant. You give the model more freedom to explore. OP gave no context, if it's a huge transformer model for instance that would be impractical to retain then sure use the model as is with a different final classification layer.

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