Fine-tuning GPT-3.5-turbo for natural language to SQL
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Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#2A tutorial on how to fine-tune a GPT3.5 model for Natural Language to SQL tasks and a comparison of its performance vs Retrieval Augmented Generation.
Based on the results, fine-tuning can match and outperform RAG (the approach matches the state of the art on accuracy while being far faster and cheaper). The big challenge for fine-tuning tasks like this is building the training datasets. Things should get even more interesting when GPT-4 is opened for fine-tuning.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#3The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#4The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
Really? I sure can. I can even imagine a single API request that triggers a job that costs $100,000. These APIs exist. They're not for individuals.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#5The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
It's about 0.2 cents right?
It's hard for something you interact with manually to provide positive value less than 0.2c.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#6The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
> I can't even think of an API where a single call would cost $1cent.
paying engineer for the same job will be many factors more expensive.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#7The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
It's about 0.2 cents right? It's hard for something you interact with manually to provide positive value less than 0.2c.
That's for the non-finetuned GPT3.5turbo model.
Finetuned is 1.2cents/1k in and 1.6cents/1k out. So it'll likely be closer to 2cents depending on what you're doing.
I'm not saying it's not useful, at 2c per query you have to be more "purposeful" as they could certainly add up depending on how you use it compared to 0.2c.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#8A tutorial on how to fine-tune a GPT3.5 model for Natural Language to SQL tasks and a comparison of its performance vs Retrieval Augmented Generation. Based on the results, fine-tuning can match and outperform RAG (the approach matches the state of the art on accuracy while being far faster and cheaper). The big challenge for fine-tuning tasks like this is building the training datasets. Things should get even more i…
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Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#9The cost per question seems super high. I can't even think of an API where a single call would cost $1cent. You better have a good pricing model to follow up on this.
If your app is able to function better for the cost of the API calls the value might just be there.
Re: Fine-tuning GPT-3.5-turbo for natural language to SQL
#10I believe this article underscores the significance and efficacy of fine-tuning for specific tasks. Looking ahead, I envision the integration of fine-tuned models with RAG agents and models, further enhancing overall performance.