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AI Engineering · Fine Tuning
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Think about a school exam that decides who passes. A fair school does not let one teacher mark every paper alone. Two teachers mark the same papers, each in a separate room, and neither sees the other's marks. Afterwards someone puts the two sets of marks side by side. Where they are the same, the mark stands. Where they differ, someone reads the paper again.
Most of the time, the two teachers agree. When they do not, the reason is often not that one of them was careless. Very often the marking guide did not say what to do with that kind of answer. One teacher gave the point and the other did not, and both could defend their choice. The useful thing to do then is to add one sentence to the marking guide, so that the next hundred papers are marked the same way.

A set of examples for training a model is exactly like that pile of exam papers. Each example needs a right answer, and a person, or here a model, has to decide what the right answer is. If the answers are careless or unclear, a model trained on them learns the carelessness, and a test scored against them measures nothing useful. This lesson is about building the examples for the rest of the chapter, before any model is trained on them. I wrote the rules, had the messages written and marked twice, read every place the marks differed, fixed one rule, and checked the test messages had not leaked into the training messages.