LLM Coursera Background Research Week 2

[Elliott-Hendrickson]

As a LLM researcher I need to develop standardized testing protocols for fine-tuning LLMs So that I can evaluate the effectiveness and efficiency of different fine-tuning strategies

Details and Assumptions

• I have completed 94 minutes of material focused on fine-tuning LLMs and parameter-efficient fine-tuning techniques.
• I understand the key concepts and methods for improving LLM performance through fine-tuning.
• I recognize the importance of evaluating how different fine-tuning approaches impact model performance and efficiency.
• I aim to apply insights from the material to create a robust testing framework for various fine-tuning methods

  Acceptance Criteria

  Given I have completed the material on fine-tuning LLMs
  When I develop and apply standardized testing protocols for assessing fine-tuned models
  Then I should be able to consistently measure and compare the effectiveness of various fine-tuning strategies

[Elliott-Hendrickson]

Proof: At this point there is no proof except for the screenshots found at this google doc: https://docs.google.com/document/d/1QfcPppRI0SIkrBfM6MxU1ThmOiV4R-gMcgqRe3LQgYQ/edit?usp=sharing What it taught: What LoRA is for LLM's, and how to Fine tune an LLM through prompt engineering.