Llama-3.1-Tulu-3-8B-RM
| Property | Value |
|---|---|
| License | Llama 3.1 Community License |
| Base Model | allenai/Llama-3.1-Tulu-3-8B-SFT |
| Primary Language | English |
| Training Repository | github.com/allenai/open-instruct |
What is Llama-3.1-Tulu-3-8B-RM?
Llama-3.1-Tulu-3-8B-RM is a reward model that forms part of the larger Tulu 3 family, designed to enhance instruction-following capabilities. This model serves as the reward component in the Tulu 3 training pipeline, helping to optimize model responses across various tasks including MATH, GSM8K, and IFEval.
Implementation Details
The model is implemented using specific hyperparameters including a 3E-6 learning rate, 256 effective batch size, and 2048 max sequence length. It utilizes a linear learning rate schedule and implements gradient norm thresholding at 1.0.
- Built on the Llama 3.1 architecture
- Trained with comprehensive publicly available and synthetic datasets
- Incorporates advanced post-training techniques
- Optimized for sequence classification tasks
Core Capabilities
- Advanced instruction following across diverse tasks
- Strong performance in mathematical reasoning (MATH, GSM8K)
- Robust evaluation capabilities for model outputs
- Specialized in preference learning and reward modeling
Frequently Asked Questions
Q: What makes this model unique?
This model stands out as a specialized reward model in the Tulu 3 ecosystem, specifically designed to guide the training of other models through preference learning. It's built on the Llama 3.1 architecture and demonstrates strong performance across various benchmarks.
Q: What are the recommended use cases?
The model is primarily intended for research and educational purposes, specifically in the context of training and evaluating other language models. It's particularly useful for tasks requiring preference learning and reward modeling in the context of instruction-following scenarios.
