Part 7/10:
- Iterative Refinement: Using the reward predictions to guide the main model's responses via reinforcement learning.
David considers practical implementation details, such as how to incorporate reward signals into JSONL-format data, suggesting that this feedback effectively trains a reward model that predicts positive or negative responses.
Multiple Specialized Models: Main, Reward, and User Simulation
Recognizing the complexity of human-like dialogue, the planning includes deploying three interconnected models:
Main Chatbot: The primary language model responsible for generating responses.
Reward Model: Predicts response quality, guiding further training.