AIF-C01 · Question #169
Which technique involves training AI models on labeled datasets to adapt the models to specific industry terminology and requirements?
The correct answer is B. Fine-tuning. Fine-tuning involves training a pre-trained AI model on a labeled dataset specific to a particular task or domain, adapting it to industry terminology and requirements. This process adjusts the model's parameters to better fit the target use case, such as understanding…
Question
Which technique involves training AI models on labeled datasets to adapt the models to specific industry terminology and requirements?
Options
- AData augmentation
- BFine-tuning
- CModel quantization
- DContinuous pre-training
How the community answered
(59 responses)- A5% (3)
- B90% (53)
- C3% (2)
- D2% (1)
Explanation
Fine-tuning involves training a pre-trained AI model on a labeled dataset specific to a particular task or domain, adapting it to industry terminology and requirements. This process adjusts the model's parameters to better fit the target use case, such as understanding specialized vocabulary or meeting domain-specific needs. Fine-tuning allows you to adapt a pre-trained foundation model to your specific use case by training it on a labeled dataset. This technique is commonly used to customize models forindustry-specific terminology, improving their accuracy for specialized tasks.
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