Data & Evaluation
Glossary
Overfitting
When a model memorises training examples instead of learning patterns that generalise.
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An overfit model performs well on the data it saw during training but poorly on new data. It usually happens when a model is too complex for the amount of data available or when training runs too long. Techniques such as more data, regularisation and validation splits help keep a model generalising rather than memorising.
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