metadata
base_model: Qwen/Qwen3-0.6B-Base
library_name: transformers
model_name: qwen3-0.6b-RM-hs2
tags:
- generated_from_trainer
- trl
- reward-model
licence: license
datasets:
- Jennny/helpsteer2-helpfulness-preference
- nvidia/HelpSteer2
license: mit
language:
- en
pipeline_tag: text-classification
Model Card for qwen3-0.6b-RM-hs2
This model is a fine-tuned version of Qwen/Qwen3-0.6B-Base. It has been trained using TRL. Intended Use: Research on model diffing, preference fine-tuning, and evaluation of lightweight LLM behavior changes. It was developed for use in the Model Diffing project of AI-Plans.
Training procedure
This model is a reward model and was trained using prompts with a chosen response >=3 only. It took about 1h 20mins with an A100(40 GB).
Framework versions
- TRL: 0.25.1
- Transformers: 4.57.3
- Pytorch: 2.9.0+cu126
- Datasets: 4.4.1
- Tokenizers: 0.22.1
Citations
Cite TRL as:
@misc{vonwerra2022trl,
title = {{TRL: Transformer Reinforcement Learning}},
author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
year = 2020,
journal = {GitHub repository},
publisher = {GitHub},
howpublished = {\url{https://github.com/huggingface/trl}}
}