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# How to fine-tune ChatGPT - A real world example
- URL: https://airabbit.blog/how-to-fine-tune-chatgpt-a-real-world-example/
- Published: 2024-08-20T14:28:44.000Z
- Updated: 2025-03-21T16:13:00.000Z
- Description: Ever felt overwhelmed by too much information when asking a simple question? In this guide, learn how to fine-tune GPT-4o-mini for more tailored and conversational responses. With just a few steps, you can adjust the model to focus on your unique situation, making AI consultations feel more perso...
- Author: AiRabbit

Have you ever asked GPT a simple question and gotten a ton of information, much of which is irrelevant or simply overwhelming?

Here’s an example:

You: "**How do I lose weight?**"

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-43.png)

I do not know how you feel when you receive this amount of information, but I personally feel **overwhelmed😄**

Instead, what I expect from a human knowledgeable human consultant is to try to reduce the search radius before making recommendations.

Maybe something like this:

"Losing weight can be tough. **Are you looking for diet tips, or maybe some exercise routines?** Let me know so I can give you the best advice for your situation."

This is something we can improve with fine-tuning techniques.

In this guide I'll show you how to fine-tune gpt-4o-mini to do just that in four simple steps. 

To demonstrate the concept, I used a **small dataset** that I created using ChatGPT. In a real world scenario, you would use a **larger datase**t to reflect your domain and conversational patterns.

**Step 1:** Open the fine-tuning dashboard and hit "Create"

[https://platform.openai.com/assistants](https://platform.openai.com/assistants?ref=airabbit.blog)

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-38.png)

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-39.png)

**Step 2**: Download the Dataset 

[https://huggingface.co/datasets/airabbitX/gpt-consultant/resolve/main/gpt\_consultant.json](https://huggingface.co/datasets/airabbitX/gpt-consultant/resolve/main/gpt%5Fconsultant.jsonl?ref=airabbit.blog)l

**Step 3**: Create a new tuning job with the downloaded dataset

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-41.png)

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-40.png)

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-42.png)

Wait until the fine tuning is complete. 

If all goes well, you should see something like this: 

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-45.png)

Remember the name of the fine-tuned model, we will use it in the next step.

**Step 4**: Test the fine tuned model

[https://platform.openai.com/playground/chat?models=gpt-4o](https://platform.openai.com/playground/chat?models=gpt-4o&ref=airabbit.blog)

Let's see how the base model responds before fine-tuning:

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-46.png)

Then test with the fine-tuned model by selecting the model from the previous step.

![](https://storage.ghost.io/c/b6/58/b65880bb-2a06-491e-bb4d-a6abeb13a649/content/images/2024/08/image-48.png)

As you can see, it will first try to figure out your background and situation before jumping into conclusions. And not just for health concerns.

### Conclusion

By fine-tuning GPT-4o-mini, we can make the model more conversational and behave more like an advisor than a Wikipedia machine😄  
  
We can significantly improve the dialog of the model by adjusting the **hyperparameters** like the number of **epochs**, **batch size**, etc. and adding more conversations to the dataset.

Of course, this is just scratching the surface of what is possible. I hope that in this tutorial I was able to demonstrate what **fine-tuning ChatGPT** is and how it can be used to improve the conversation style and output of ChatGPT.  
  
If you are also interested in **fine-tuning open source models**, please check out my [other tutorial.](https://airabbit.ghost.io/ghost/?ref=airabbit.blog#/editor/post/66c485c3b6fb080001d22410)