When 8,000 Examples Beat 80,000: What a Model Still Needs to Learn
TL;DR for operators A team has 80,000 instruction-response examples but enough resources to fine-tune on only 8,000. Selecting the examples with the highest model loss may prioritize genuinely missing knowledge, but it can also prioritize noise. Random selection and conventional quality ratings do not necessarily reveal what the current model can already retrieve. ...