When should one opt for the Supervised Fine Tuning Trainer (SFTTrainer) instead of the regular Transformers Trainer when it comes to instruction fine-tuning for Language Models (LLMs)? From what I gather, the regular Transformers Trainer typically refers to unsupervised fine-tuning, often utilized for tasks such as Input-Output schema formatting after conducting supervised fine-tuning. There seem to be various examples of fine-tuning tasks with similar characteristics, but with some employing the SFTTrainer and others using the regular Trainer. Which factors should be considered in choosing between the two approaches?
I looking for Fine Tuning a LLM for generating json to json transformation (matching texts in json) using huggingface and trl libraries.
