1Z0-1127-25 Prompt Engineering Practice Question
An OCI Generative AI user notices that a model generates repetitive phrases when summarizing technical articles. Which parameter adjustment is MOST likely to reduce this repetition?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the frequency penalty
Frequency penalty reduces the likelihood of repeating tokens that have already appeared, directly targeting repetition. Presence penalty also helps but frequency penalty is stronger for repeated phrases.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Decrease max tokens
Why it's wrong here
Max tokens only limits output length; it does not directly address repetition.
- ✓
Increase the frequency penalty
Why this is correct
Frequency penalty penalizes tokens that have already appeared, discouraging the model from repeating phrases.
- ✗
Set top-p to 0.95
Why it's wrong here
Top-p controls nucleus sampling breadth; it does not specifically target repetition.
- ✗
Increase temperature to 0.9
Why it's wrong here
Higher temperature increases randomness, which may reduce repetition but also risks incoherence; not the most direct solution.
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