Answer-first summary for fast verification
Answer: All of the above.
To fine-tune an Azure OpenAI model effectively, you need to follow a series of steps. First, selecting a pre-trained model that is closely related to the target task (A) can provide a good starting point and improve the model's performance on the specific task. Next, preparing a dataset that is representative of the target task and contains a variety of examples (B) is crucial for training the model to understand the nuances of the task. Finally, training the model on the prepared dataset using appropriate hyperparameters (C) allows you to optimize the model's performance for the specific task. Therefore, all of the above steps (D) are necessary for effective fine-tuning.
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As an AI engineer, you have been asked to fine-tune an Azure OpenAI model for a specific use case. Your goal is to improve the model's performance on a particular task. Which of the following steps should you take to fine-tune the model effectively?
A
Select a pre-trained model that is closely related to the target task.
B
Prepare a dataset that is representative of the target task and contains a variety of examples.
C
Train the model on the prepared dataset using appropriate hyperparameters.
D
All of the above.
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