This is a 3B reward model fine-tuned from Qwen 2.5 3B using Anthropic HH-RLHF data.
It is designed to score model outputs for alignment and quality, and can be used with RewardBench for evaluation.

Eval Results (RewardBench)

Category	Score
Chat	83.5%
Chat Hard	53.2%
Safety	72.2%
Reasoning	73.4%

Sub-benchmarks

alpacaeval-easy: 0.82
alpacaeval-hard: 0.874
hep-python: 0.835
mt-bench-easy: 0.893
refusals-offensive: 0.91

Usage

python

from transformers import AutoModelForSequenceClassification, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("kanishkez/Reward-Model")
model = AutoModelForSequenceClassification.from_pretrained("kanishkez/Reward-Model")