How to Fine-tune a ChatGPT 3.5 Turbo Model - Step by Step Guide | Summary and Q&A

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August 27, 2023
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All About AI
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How to Fine-tune a ChatGPT 3.5 Turbo Model - Step by Step Guide

TL;DR

This video provides a step-by-step guide on how to prepare, create, and use a fine-tuned chat GPT 3.5 Turbo model, along with information on pricing and pros and cons.

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Questions & Answers

Q: Why would someone consider fine-tuning a model?

Fine-tuning a model can improve reliable output formatting, allow custom tone, and shorten prompts, leading to potential cost and time savings in inference.

Q: How many examples are required for fine-tuning?

At least 10 examples are required for fine-tuning, but clear improvements are typically seen with 50 to 100 training examples, although the ideal number varies depending on the use case.

Q: Can the prompt be shortened by fine-tuning?

Yes, fine-tuning can help shorten prompts, as early testers have reduced prompt size by up to 90% by fine-tuning instructions into the model itself, which can speed up API calls and cut costs.

Q: What is the cost of fine-tuning the GPT 3.5 Turbo model?

The pricing for fine-tuning the GPT 3.5 Turbo model is $0.0016 per thousand tokens for outputs, which is relatively low and cost-effective compared to other options.

Summary & Key Takeaways

  • Fine-tuning a model can improve output formatting, enable custom tone, and shorten prompts, resulting in cost and time savings.

  • The first step is to prepare the data set in a specific JSON format with system prompts, user prompts, and desired responses.

  • At least 10 examples are required for fine-tuning, but the exact number depends on the use case. A Python script can be used to collect the examples.

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