Explain the prerequisite for synthetic data to improve model training.
Question: According to the source, what specific requirement must synthetic data meet before it has a significant effect on a model, and what is the reward for meeting this requirement?
Sample answer: Synthetic data must have details that are close enough to the actual distribution. When this is achieved, the reward is suddenly gaining access to a far larger training set.
Key points:
- Synthetic data details must be close enough to the actual distribution.
- The reward is access to a far larger training set.
Rubric: Give full credit for stating that the synthetic data must match or be close to the actual distribution, and that the reward is a much larger training set.
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