These kinds of things can happen surprisingly easily in the real-world. The most common cause is &quot;target leaks&quot;, which happen when the thing you are trying to predict accidentally ends up in your dataset, usually indirectly through some non-obvious process. Neural networks are especially good learners, and will perform suspiciously well in these situations.<p>There&#x27;s often no way to know exactly what a neural network is doing, but sanity checks can catch most issues. Realistically, you wouldn&#x27;t expect a neural network to perform with 100% accuracy, which would be a first clue in your example.