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Probably nothing specific. By definition, an overfitted model has only learned to deal with the training input and will perform worse on anything that is differ
by samus 3y ago
Probably nothing specific. By definition, an overfitted model has only learned to deal with the training input and will perform worse on anything that is different. In training metrics it shows as a large gap between the performance metrics on the training test vs. on the test set.
- exe34 3y agoWhen the training data is the entire internet, I suspect it can still perform well enough in economically profitable situations to be worth having.
- samus 3y agoSurely it might still work, but training a model into true overfitting territory is a waste of resources. An overtrained model is usually a worse model than an earlier checkpoint. That's the main reason one strives to avoid that.