AWS Certified AI Practitioner AIF-C01 Practice Question
A startup wants its foundation model to better understand industry-specific jargon. The team plans to keep training the model on a large collection of unlabeled industry documents using the same self-supervised objective that was used during the model's original pre-training. What is this training approach called?
Continuing to train a foundation model on new, unlabeled domain data with the same self-supervised objective is known as continuous pre-training (sometimes called domain-adaptive pre-training). It extends the model's general knowledge by exposing it to additional in-domain text before any supervised fine-tuning. Supervised fine-tuning, RLHF, and prompt engineering all require labeled examples or interaction feedback, which are not part of this scenario.
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What is self-supervised learning?
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AWS Certified AI Practitioner AIF-C01
Applications of Foundation Models
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