---
license: mit
datasets:
- Anthropic/hh-rlhf
language:
- en
base_model:
- Qwen/Qwen2.5-3B
pipeline_tag: text-classification
library_name: transformers
tags:
- reward-model
- 3b
- RLHF
---

# Qwen-2.5-3B Reward Model

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")