How Fine-Tuning Supercharges GPT-3.5 Turbo’s Capabilities


According to a blog post by OpenAI, they have rolled out the fine-tuning capability for their GPT-3.5 Turbo model, with an extension of this feature to GPT-4 planned for the upcoming fall. This enhancement, as OpenAI states, allows developers to modify models to better cater to specific use cases and to deploy these custom models on a larger scale.

OpenAI’s preliminary tests suggest that a fine-tuned GPT-3.5 Turbo might match or even exceed the base GPT-4’s performance in certain specialized tasks. OpenAI emphasizes that data exchanged via the fine-tuning API remains the property of the customer and is not repurposed by OpenAI or any other entity for training subsequent models.

Fine-Tuning Use Cases

Since the introduction of GPT-3.5 Turbo, OpenAI reports that there has been a significant demand from developers and businesses to tailor the model for distinct user experiences. OpenAI highlights the following benefits of the recent update:

  1. Improved Steerability: OpenAI suggests that fine-tuning enhances the model’s ability to adhere to specific instructions, such as generating concise outputs or consistently responding in a designated language.
  2. Reliable Output Formatting: According to OpenAI, fine-tuning can bolster the model’s consistency in response formatting, which is crucial for applications like code completion or API call generation.
  3. Custom Tone: OpenAI mentions that businesses can adjust the model’s tone to resonate more with their brand voice.

OpenAI also notes that fine-tuning allows for a reduction in prompt lengths while maintaining similar performance levels. They claim that GPT-3.5 Turbo, when fine-tuned, can manage up to 4k tokens, which is double the capacity of their previous models.

Safety Considerations

OpenAI places a strong emphasis on the safe deployment of fine-tuning. They state that to ensure the model’s inherent safety features remain intact during the fine-tuning process, the training data undergoes scrutiny via OpenAI’s Moderation API and a GPT-4 powered moderation system.

Pricing Breakdown

OpenAI provides a detailed cost structure associated with fine-tuning, categorized into initial training and usage:

  • Training: $0.008 per 1K Tokens
  • Usage input: $0.012 per 1K Tokens
  • Usage output: $0.016 per 1K Tokens

Featured Image Credit: Photo by “ilgmyzin” via Unsplash

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