Writing an LLM from scratch, part 25 -- instruction fine-tuning
SMRTR summary
A tutorial guide walks through instruction fine-tuning a GPT-2 model using techniques from Sebastian Raschka's book, explaining the Alpaca input format designed for one-shot interactions due to early LLMs' short context lengths. The fine-tuning process completed in 48 seconds, with validation loss rising after two epochs indicating overfitting.
SMRTR provides this summary for quick context. The original article belongs to Giles Thomas Blog.
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