go to ORKG: http://orkg.org/orkg/predicate/P163012
fine-tuning data
In the context of large language models (LLMs), fine-tuning data refers to a curated dataset used to further train a pre-trained model on specific tasks or domains. This data is typically domain-specific, task-oriented, or reflective of desired linguistic behaviors, allowing the model to adapt and perform more effectively in targeted applications. The quality, diversity, and relevance of the fine-tuning data are critical for achieving optimal model performance.