turns in the English language that are
high-quality, based on their human annotated rank (choosing only the highest rank 0). In
our experiments, we compare to a model fine-tuned from the base model using only this data
via supervised fine-tuning, and refer to it as our SFT baseline.
EFT Seed Data
The Open Assistant data also provides multiple ranked human responses
per prompt from which we can construct evaluation fine-tuning data. We split this into train
and evaluation sets, and use it to create LLM-as-a-