Itinai.com a modern office workspace featuring a computer wit 1806a220 be34 4644 a20a 7b02eb350167 0
Itinai.com a modern office workspace featuring a computer wit 1806a220 be34 4644 a20a 7b02eb350167 0

Fine-tune a Mistral-7b model with Direct Preference Optimization

The text discusses methods to boost the performance of fine-tuned models, particularly Large Language Models (LLMs) using Reinforcement Learning from Human Feedback (RLHF) and Direct Preference Optimization (DPO). It details the formatting of preference datasets, training the model with DPO, and evaluating the performance of the model. The process results in the creation of a new model, NeuralHermes-2.5, which shows significant improvement on the Open LLM Leaderboard.

 Fine-tune a Mistral-7b model with Direct Preference Optimization

Boost Performance with Direct Preference Optimization

Boost the performance of your supervised fine-tuned models with Direct Preference Optimization (DPO), a practical AI solution that improves the behavior of pre-trained Large Language Models (LLMs). Created NeuralHermes-2.5 by fine-tuning OpenHermes-2.5 using a DPO-like technique. In this article, we’ll explain how DPO significantly enhances model performance based on real-world application.

Preference Datasets

Preference datasets are collections of ranked answers by humans. These rankings guide the fine-tuning of LLMs to output preferred answers. However, creating these datasets can be costly and prone to biases. To address these issues, several solutions, like replacing human feedback with AI feedback, are available. Despite being smaller than fine-tuning datasets, preference datasets play a crucial role in improving LLM performance.

Direct Preference Optimization

Direct Preference Optimization (DPO) simplifies the control process by treating the task as a classification problem. By leveraging the LLM itself as a reward model, DPO efficiently aligns the model’s outputs with human preferences, resulting in a more stable, efficient, and computationally less demanding process compared to traditional methods.

Formatting the Data

We demonstrated how to fine-tune the OpenHermes-2.5-Mistral-7B model using the Intel/orca_dpo_pairs dataset. The dataset was formatted using a specific chat template, and the process was streamlined using the tokenizer’s apply_chat_template() function.

Training the Model with DPO

We defined LoRA configurations and loaded the model for fine-tuning with DPO. The training process, including fine-tuning the model and evaluating its performance, was explained step by step. The model’s performance was evaluated, and the significant improvement in the average score compared to the original model was highlighted.

Conclusion

We showcased the practical application of DPO in fine-tuning LLMs and creating our own model, NeuralHermes-2.5. The article emphasized the potential for improvement in the fine-tuning pipeline and provided references for further learning.

Discover how AI can redefine your company’s way of work. Identify Automation Opportunities, Define KPIs, Select an AI Solution, and Implement Gradually. For AI KPI management advice, connect with us at hello@itinai.com.

Spotlight on a Practical AI Solution: Consider the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages.

Discover how AI can redefine your sales processes and customer engagement. Explore solutions at itinai.com.

For continuous insights into leveraging AI, stay tuned on our Telegram t.me/itinainews or Twitter @itinaicom.

List of Useful Links:

Itinai.com office ai background high tech quantum computing 0002ba7c e3d6 4fd7 abd6 cfe4e5f08aeb 0

Vladimir Dyachkov, Ph.D – Editor-in-Chief itinai.com

I believe that AI is only as powerful as the human insight guiding it.

Unleash Your Creative Potential with AI Agents

Competitors are already using AI Agents

Business Problems We Solve

  • Automation of internal processes.
  • Optimizing AI costs without huge budgets.
  • Training staff, developing custom courses for business needs
  • Integrating AI into client work, automating first lines of contact

Large and Medium Businesses

Startups

Offline Business

100% of clients report increased productivity and reduced operati

AI news and solutions