Oracle Exam 1Z0-1127-24 Topic 2 Question 20 Discussion

Actual exam question for Oracle's 1Z0-1127-24 exam

Question #: 20
Topic #: 2

Which is a distinguishing feature of "Parameter-Efficient Fine-tuning (PEFT)" as opposed to classic Tine- tuning" in Large Language Model training?

APEFT involves only a few or new parameters and uses labeled, task-specific data.

BPEFT modifies all parameters and uses unlabeled, task-agnostic data.

CPEFT does not modify any parameters but uses soft prompting with unlabeled data. PEFT modifies

DPEFT parameters and b typically used when no training data exists.

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Suggested Answer: A

by Joseph at Nov 19, 2024, 06:57 AM

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Junita

4 months ago

I bet the exam writers were laughing their heads off when they came up with that last answer choice. 'No training data? Really?'

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Loreen

4 months ago

D) Wait, did they really just throw in an answer about no training data? That's just gotta be a trick question.

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Shawna

4 months ago

D) Yeah, that does seem like a tricky option. It's probably not the right choice.

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Shawna

4 months ago

A) PEFT involves only a few or new parameters and uses labeled, task-specific data.

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Nathalie

5 months ago

B) This one seems to be the opposite of what PEFT is supposed to do. Modifying all parameters and using unlabeled data doesn't sound very parameter-efficient to me.

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Glen

3 months ago

A) That makes sense, PEFT is supposed to be parameter-efficient after all.

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In

4 months ago

C) PEFT does not modify any parameters but uses soft prompting with unlabeled data.

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Rochell

4 months ago

B) I agree, modifying all parameters and using unlabeled data doesn't sound efficient at all.

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Jess

4 months ago

A) PEFT involves only a few or new parameters and uses labeled, task-specific data.

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Xochitl

5 months ago

Actually, I think PEFT does not modify any parameters but uses soft prompting with unlabeled data.

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Myong

5 months ago

C) Hmm, I'm not sure that's correct. Doesn't PEFT actually modify the model parameters, not just use soft prompting?

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Claribel

4 months ago

A) PEFT involves only a few or new parameters and uses labeled, task-specific data.

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Charlene

4 months ago

C) Hmm, I'm not sure that's correct. Doesn't PEFT actually modify the model parameters, not just use soft prompting?

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Launa

5 months ago

B) PEFT modifies all parameters and uses unlabeled, task-agnostic data.

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Annabelle

5 months ago

A) PEFT involves only a few or new parameters and uses labeled, task-specific data.

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Bernadine

5 months ago

I disagree, I believe PEFT modifies all parameters and uses unlabeled data.

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Jaime

5 months ago

A) Looks like the right answer to me. Modifying only a few parameters and using labeled data sounds like a smart way to fine-tune large language models.

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Vi

4 months ago

C) Definitely, using soft prompting with unlabeled data while not modifying any parameters doesn't sound very effective.

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Makeda

5 months ago

B) I agree, it seems like a more efficient approach compared to modifying all parameters and using unlabeled data.

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Tanesha

5 months ago

A) Looks like the right answer to me. Modifying only a few parameters and using labeled data sounds like a smart way to fine-tune large language models.

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Janna

6 months ago

I think the distinguishing feature of PEFT is that it involves only a few new parameters and uses labeled data.

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