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- Fine-tuning is a technique that uses a small training set of labeled data to produce a model for a specific downstream application1. Here are some examples of fine-tuning:
- Natural language processing, such as question answering (SQuAD) and GLUE benchmark1
- Vision and speech1
- Cosmic constants, such as gravitational force constant, electromagnetic force constant, strong nuclear force constant, weak nuclear force constant, and cosmological constant2
- Setting the style, tone, format, or other qualitative aspects3
- Improving reliability at producing a desired output3
- Correcting failures to follow complex prompts3
- Handling many edge cases in specific ways3
- Performing a new skill or task that’s hard to articulate in a prompt3
Learn more:✕This summary was generated using AI based on multiple online sources. To view the original source information, use the "Learn more" links.Fine-tuning starts with a general purpose base (foundation) model and uses a small training set of labeled data to produce a model for a specific downstream application. There are many examples of fine-tuning in natural language processing (question answering (SQuAD) and GLUE benchmark), as well as vision and speech.www.cambridge.org/core/journals/natural-languag…(A Brief History of Time, p. 125) Here are the most celebrated and widely accepted examples of fine-tuning for the existence of life: Cosmic Constants Gravitational force constant Electromagnetic force constant Strong nuclear force constant Weak nuclear force constant Cosmological constantintelligentdesign.org/articles/list-of-fine-tuning-para…Some common use cases where fine-tuning can improve results:
- Setting the style, tone, format, or other qualitative aspects
- Improving reliability at producing a desired output
platform.openai.com/docs/guides/fine-tuning - People also ask
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