Improving language model behavior by training on a curated dataset
OpenAI Blog
Researchers demonstrated that fine-tuning language models on small, curated datasets improves their behavior according to specific values. The study used a limited set of hand-selected training examples rather than large-scale datasets to achieve this improvement. This approach allows developers to guide model behavior toward desired outcomes without requiring massive amounts of training data.
Why it matters
Our latest research finds we can improve language model behavior with respect to specific behavioral values by fine-tuning on a small, curated dataset.
