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For more information about Stanford’s graduate programs, visit: https://online.stanford.edu/graduate-educationTo follow along with the course schedule and syllabus, visit: https://cme295.stanford.edu/syllabus/Chapters:00:00:00 Introduction00:03:36 Pretraining00:10:33 Cross-entropy loss00:17:15 Data mixtures00:22:18 Midtraining00:23:41 Long context training00:31:47 Supervised finetuning (SFT)00:40:15 Low-Rank Adaptation (LoRA)00:46:37 Preference tuning00:54:44 Bradley-Terry formulation01:01:49 Reinforcement Learning from Human Feedback (RLHF)01:05:38 Direct Preference Preference Optimization (DPO)01:12:08 Reasoning01:20:56 Group Relative Policy Optimization (GRPO)01:23:31 On-Policy Distillation (OPD)01:27:47 End-to-end exampleUploaded 15-10-26Afshine Amidi is an Adjunct Professor at Stanford University.Shervine Amidi is an Adjunct Professor at Stanford University.Follow the playlist: https://youtube.com/playlist?list=PLakGfbKCei80&si=HF2tNywj7nXIQq8X Learn more about your ad choices. Visit megaphone.fm/adchoices
