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My fine-tuned model scored 100%... The benchmark was lying

I fine-tuned Mistral 7B on my laptop to detect personal data in log lines and support messages. On my first test set it scored 100%. Perfect. Every single line classified correctly. I did not publish that number, because the same test set gave few-shot prompting 94%, and a six-point gap over a prompt you can write in five minutes is not a reason to fine-tune anything. The honest conclusion looked…

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Rationale

The rationale is simple - I want my project repos to be self-sufficient in the sense that it includes both its source code as well as goals/issues/docs.

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