Final Training of a Large Language Model from Scratch: Chapter 5 Completion
By
gpjt
Sesame, salt, and substance. A flagship bake.
Summary
This article concludes a 22-part series documenting the author's journey through Chapter 5 of Sebastian Raschka's book "Build a Large Language Model (from Scratch)". The author reflects on the challenges of understanding cross entropy loss and perplexity, while noting that the remaining implementation was more straightforward. The post describes the final training of an LLM on real text and includes comparisons with OpenAI's GPT-2 weights. Despite the technical nature of the content, the author expresses some disappointment that this concluding post feels anticlimactic after the extensive series.
Key quotes
· 3 pulledThis post wraps up my notes on chapter 5 of Sebastian Raschka's book "Build a Large Language Model (from Scratch)".
Understanding cross entropy loss and perplexity were the hard bits for me in this chapter -- the remaining 28 pages were more a case of plugging bits together and running the code, to see what happens.
The shortness of this post almost feels like a damp squib. After writing so much in the last 22 posts, there's really not all that much to say -- but that hides the fact that this part of the book is probably the most exc
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