Session 4 - Training and Evaluating LLMs On Custom Datasets¶

Session 4

This session aims to equip you with the knowledge to train Large Language Models (LLMs) by exploring techniques like unsupervised pretraining and supervised fine-tuning with various preference optimization methods. It will also cover efficient fine-tuning techniques, retrieval-based approaches, and language agent fine-tuning. Additionally, the session will discuss LLM training frameworks and delve into evaluation methods for LLMs, including evaluation-driven development and using LLMs for evaluation itself.

This session is aimed to help:

People who are already familiar basics of LLMs and Transformers
People who already knows how to use pre-trained LLMs prompt engineering and RAG
People who want train or finetune their own LLMs on custom data.
People who want to lear how to evaluate LLMs

Outline¶

Part 1: Training Foundational LLMs¶

Coming soon...

Part 2: Finetuning LMs To Human Preferences ¶

Details¶

Date: 14 March, 2024
Speaker: Abhor Gupta
Location: Infocusp Innovations LLP

Material¶

Recording: TODO

Part 3: LLM Training Frameworks¶