 Reward model trained from human feedback  Reward model (RM) trained to predict which generated answer is better judged by a human, given a question.  RM are useful in these domain:  - QA model evaluation  - serves as reward score in RLHF    All models are train on these dataset with a same split seed across datasets (if validation split wasn't available)  - [webgpt_comparisons](https://huggingface.co/datasets/openai/webgpt_comparisons)  - [summarize_from_feedback](https://huggingface.co/datasets/openai/summarize_from_feedback)  - [synthetic-instruct-gptj-pairwise](https://huggingface.co/datasets/Dahoas/synthetic-instruct-gptj-pairwise)  