Preparing and Analyzing Chat Datasets for Effective Model Fine-Tuning
This notebook is your essential toolkit for preprocessing and analyzing chat datasets before fine-tuning chat models. It detects format errors, delivers key statistics, and estimates token counts to predict costs accurately. Designed for the latest gpt-3.5-turbo fine-tuning method—see legacy docs for babbage-002 and davinci-002.
This notebook functions as a comprehensive utility for preprocessing and analyzing the chat dataset utilized in fine-tuning a chat model.
It identifies format errors, delivers essential statistics, and estimates token counts to forecast fine-tuning costs.
The techniques presented here align with the current fine-tuning process for gpt-3.5-turbo.
See legacy fine-tuning for models like babbage-002 and davinci-002.
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