Topic 1 Question 19
A company uses a foundation model (FM) from Amazon Bedrock for an AI search tool. The company wants to fine-tune the model to be more accurate by using the company's data. Which strategy will successfully fine-tune the model?
Provide labeled data with the prompt field and the completion field.
Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
Purchase Provisioned Throughput for Amazon Bedrock.
Train the model on journals and textbooks.
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- 正解だと思う選択肢: A
Labeled Data: Fine-tuning requires labeled data
👍 3jove2024/11/05 Why is it not C? Finetuning cannot be done without provisioned throughput mode active.
👍 3aldricstormcloak2024/11/19- 正解だと思う選択肢: A
Fine-tuning a foundation model involves providing labeled training data where each example consists of a prompt (the input to the model) and a completion (the desired output). This structure helps the model learn specific patterns or behaviors tailored to the company’s data and use case. In Amazon Bedrock, fine-tuning relies on a structured dataset that aligns with the model's learning requirements to improve its accuracy for domain-specific tasks.
👍 3ap64912024/12/27
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