Post training - Reinforcement Learning
The post on post-training SFT covered four finetuning experiments on direct and reasoning tasks using LoRA and full-finetuning approaches. This post covers different reinforcement learning (RL) approaches used in post-training. SFT teaches a model by giving it examples to imitate. The training data contains target responses, and the model learns to generate tokens from the target distribution. RL takes a different approach. Instead of showing the model exactly how to solve a problem, we let it generate solutions, evaluate how good those solutions are, and update the model so that successful behaviour becomes more likely. ...