1Z0-1127-25 Using OCI Generative AI Service Practice Question
A data scientist is using OCI Generative AI Service to generate product descriptions. They notice that the output often repeats phrases. Which parameter adjustment would MOST directly address this issue?
⚠ Common exam trap
Oracle often tests the distinction between frequency penalty and temperature, where candidates mistakenly think increasing randomness (temperature) will reduce repetition, but temperature actually increases variability without targeting repetition directly.
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
The frequency penalty directly reduces the likelihood of the model repeating the same phrases by penalizing tokens that have already appeared in the generated text. In OCI Generative AI Service, this parameter subtracts a fixed value from the log-probability of each token each time it is generated, making repeated tokens less likely to be chosen again. This is the most direct mechanism to address repetitive output.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the temperature
Why it's wrong here
Higher temperature increases randomness but does not directly reduce repetition.
- ✗
Increase the max tokens
Why it's wrong here
Max tokens limits output length, does not affect repetition.
- ✓
Increase the frequency penalty
Why this is correct
Frequency penalty penalizes tokens that have already appeared, reducing repetition.
- ✗
Decrease the top-p value
Why it's wrong here
Lower top-p reduces the set of candidate tokens, may increase repetition.
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