Fine-Tuning GPT-4o for Revolutionary Performance

TL;DR:

• Fine-tuning GPT-4o allows developers to customise AI models for specific tasks, enhancing performance and accuracy.
• Cosine’s Genie achieved a state-of-the-art score of 43.8% on the SWE-bench Verified benchmark using fine-tuned GPT-4o.
• Distyl ranked 1st on the BIRD-SQL benchmark with a 71.83% execution accuracy using fine-tuned GPT-4o.

In the rapidly evolving world of artificial intelligence (AI), the ability to fine-tune models has become a game-changer. Today, we’re thrilled to announce the launch of fine-tuning for GPT-4o, a feature that developers have been eagerly awaiting. This new capability allows developers to customise GPT-4o models with their own datasets, leading to higher performance and lower costs for specific use cases. Let’s dive into what this means for the future of AI in Asia and beyond.

What is Fine-Tuning and Why Does It Matter?

Fine-tuning is the process of training a pre-trained AI model on a new dataset to adapt it to a specific task. For GPT-4o, this means developers can now tailor the model to their unique needs, whether it’s coding, creative writing, or any other domain-specific application. This customisation can significantly improve the model’s performance and accuracy, making it more efficient and cost-effective.

Getting Started with GPT-4o Fine-Tuning

To start fine-tuning GPT-4o, developers can visit the fine-tuning dashboard and select the base model they want to customise. GPT-4o fine-tuning is available to all developers on paid usage tiers, with costs starting at $25 per million tokens for training and $3.75 per million input tokens for inference.

For those looking to experiment without a significant investment, GPT-4o mini fine-tuning is also available. This version offers 2 million training tokens per day for free until September 23, making it an excellent starting point for developers to test the waters.

Achieving State-of-the-Art Performance

Over the past few months, we’ve collaborated with trusted partners to test fine-tuning on GPT-4o. The results have been impressive. Here are a couple of success stories:

Cosine’s Genie: A Software Engineering Marvel

Cosine’s Genie is an AI software engineering assistant that can autonomously identify and resolve bugs, build features, and refactor code. Powered by a fine-tuned GPT-4o model, Genie has achieved a state-of-the-art score of 43.8% on the new SWE-bench Verified benchmark. This is a significant improvement over previous models, demonstrating the power of fine-tuning.

“Genie is powered by a fine-tuned GPT-4o model trained on examples of real software engineers at work, enabling the model to learn to respond in a specific way.”

• Cosine

Distyl: Leading the Way in Text-to-SQL

Distyl, an AI solutions partner to Fortune 500 companies, recently placed 1st on the BIRD-SQL benchmark. Their fine-tuned GPT-4o model achieved an execution accuracy of 71.83%, excelling in tasks like query reformulation, intent classification, and SQL generation. This achievement highlights the versatility and effectiveness of fine-tuned models.

Ensuring Data Privacy and Safety

Fine-tuned models remain entirely under the control of the developers, ensuring full ownership of business data, including all inputs and outputs. This means your data is never shared or used to train other models. Additionally, we’ve implemented layered safety mitigations to prevent misuse of fine-tuned models. Automated safety evaluations and usage monitoring ensure that applications adhere to our usage policies.

Prompt: Customising GPT-4o for Your Needs

Before diving into fine-tuning, it’s crucial to understand the specific needs of your application. Here’s a prompt to help you get started:

“Imagine you are a developer working on a project that requires high accuracy in text-to-SQL conversion. How would you fine-tune GPT-4o to achieve the best results for this specific task?”

This prompt encourages you to think about the unique requirements of your project and how fine-tuning can help you achieve your goals. By customising GPT-4o, you can create a model that is tailored to your specific needs, leading to better performance and efficiency.

Comment and Share:

We’d love to hear your thoughts on fine-tuning GPT-4o and how it’s transforming the AI landscape. Share your experiences and insights in the comments below. Don’t forget to subscribe for updates on AI and AGI developments.

You may also like:

• Get Access to OpenAI’s New GPT-4o Now!
• 10 Amazing GPT-4o Use Cases
• 7 GPT-4o Prompts That Will Blow Your Mind!

• To learn more about fine tuning ChatGPT tap here.