Snorkel-Mistral-PairRM-DPO
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Base Model | Mistral-7B-Instruct-v0.2 |
| Training Approach | Iterative DPO with PairRM |
| Alpaca-Eval 2.0 Score | 30.22 (34.86 with post-processing) |
What is Snorkel-Mistral-PairRM-DPO?
Snorkel-Mistral-PairRM-DPO is an advanced language model that combines the powerful Mistral-7B architecture with innovative alignment techniques. Developed by Snorkel AI, this model implements an iterative Direct Preference Optimization (DPO) process using PairRM for response ranking, resulting in significantly improved instruction-following capabilities.
Implementation Details
The model follows a sophisticated three-step training methodology: First, it generates multiple response variations for each prompt using Mistral-7B-Instruct-v0.2. Second, it applies PairRM for response ranking. Finally, it uses DPO to optimize the model based on preferred and rejected responses. This process is repeated three times to achieve optimal performance.
- Utilizes prompts from UltraFeedback dataset
- Implements Mistral's instruction format: [INST] {prompt} [/INST]
- Leverages the Zephyr training recipe
- Available through Together AI API and Hugging Face endpoints
Core Capabilities
- Enhanced instruction-following abilities
- Ranked 3rd on Alpaca-Eval 2.0 leaderboard
- Specialized response generation
- Efficient integration with existing infrastructure
Frequently Asked Questions
Q: What makes this model unique?
The model's uniqueness lies in its iterative alignment approach using PairRM for response ranking and DPO for optimization, achieving state-of-the-art performance for open-source base models on the Alpaca-Eval 2.0 benchmark.
Q: What are the recommended use cases?
The model is optimized for chat purposes and general instruction-following tasks. It's particularly suitable for enterprises requiring high-quality response generation, though it should be noted that it doesn't include built-in moderation mechanisms.
