Microsoft Azure AI Engineer Associate AI-102 Practice Question
You need to fine-tune the gpt-35-turbo model in Azure OpenAI so that it produces legal citations in a specific format. You prepare a training file in JSONL format where each line contains the keys "prompt" and "completion". When you submit the job with the Azure OpenAI fine-tuning REST API, the request is rejected during data validation. What is the most likely cause of the failure?
The JSONL file is larger than 100 MB, exceeding the maximum size supported for fine-tuning.
The file uses Windows (CRLF) line endings instead of Unix (LF) line endings.
Chat models such as gpt-35-turbo require a "messages" array per record; using "prompt" and "completion" causes validation to fail.
The training dataset contains more than 50 000 tokens across all examples.
Chat models such as gpt-35-turbo expect each training record to be a JSON object that contains a "messages" array, where each element has a "role" and "content" field. The older "prompt" / "completion" schema is valid only for completion-style models (for example, text-davinci-003). Because the training file uses the wrong schema, Azure OpenAI cannot parse the data and the job is rejected. The other options describe conditions that would not automatically fail validation for gpt-35-turbo: line-ending style is ignored, the per-file token limit is higher than 50 000, and the maximum file size for fine-tuning is currently well above 100 MB.
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What is the 'messages' array schema required by gpt-35-turbo?
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What are completion-style models and how are they different?
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Why can’t gpt-35-turbo use the 'prompt' / 'completion' format?
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