Question
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?
- A. Provide labeled data with the prompt field and the completion field. Correct
- B. Prepare the training dataset by creating a .txt file that contains multiple lines in .csv format.
- C. Purchase Provisioned Throughput for Amazon Bedrock.
- D. Train the model on journals and textbooks.
Explanation
According to AWS documentation, fine-tuning a foundation model from Amazon Bedrock involves providing labeled data where the 'prompt' field contains the input text and the 'completion' field contains the desired output or response. This method allows the model to learn from specific examples provided by the company, thereby improving its accuracy for the particular use case.
