internlm2-1_8b-reward EU AI Act Compliance Profile

InternLM

💻Github Repo • 🤔Reporting Issues • 📜Technical Report

Introduction

InternLM2-1.8B-Reward is a reward model trained on the foundation of InternLM2-Chat-1.8B-SFT. This model has been trained using over 2.4 million preference samples, both human-annotated and AI-synthesized, achieving outstanding performance while ensuring a balance between helpful and harmless.

Key Features:

• Variety of Sizes Available: Our open-sourced reward models are available in sizes of 1.8B, 7B, and 20B, each demonstrating exceptional performance across various metrics. We aim for these different-sized models to facilitate research on the scaling laws of reward models, providing valuable insights to the community.
• Comprehensive Coverage of Preference: Trained with 2.4 million preference pairs derived from both human annotations and AI synthesis, covering diverse areas such as dialogue, writing, poetry, summarization, coding, mathematics, etc. It also maintains a balance between helpful and harmless.
• Multilingual Support: InternLM2-Reward was trained on high-quality English and Chinese preference data, delivering robust performance in both languages.

This model was applied to the RLHF training process of InternLM2-Chat. The reward model training techniques from the [InternLM2 Technical Report](https://arxiv.org/abs/2403.17

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