Oracle Exam 1Z0-1127-24 Topic 2 Question 10 Discussion

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

Question #: 10
Topic #: 2

[All 1Z0-1127-24 Questions]

How does the utilization of T-Few transformer layers contribute to the efficiency of the fine-tuning process?

ABy incorporating additional layers to the base model

BBy allowing updates across all layers of the model

CBy excluding transformer layers from the fine-tuning process entirely

DBy restricting updates to only a specific croup of transformer Layers

Show Suggested Answer

Suggested Answer: D

by Luther at Jul 16, 2024, 11:21 AM

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Eulah

4 months ago

I reckon option B is the way to go. Allowing updates across all layers ensures the model can adjust to the new task properly. Efficiency be damned, we want accuracy!

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Santos

4 months ago

I believe allowing updates across all layers of the model can provide more flexibility and better results in the fine-tuning process.

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Pearlie

4 months ago

Ha! Excluding the transformer layers? That's like trying to fine-tune a car by removing the engine. Gotta keep those layers in the mix, folks.

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Wilson

4 months ago

But wouldn't restricting updates to only a specific group of transformer layers be more efficient?

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Jenise

4 months ago

I'm not sure about that. Excluding the transformer layers entirely, as in option C, could be a more efficient approach. Might be worth exploring that further.

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Caitlin

3 months ago

What about option D, where updates are restricted to specific groups of transformer layers? That could be a good middle ground.

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Chun

3 months ago

I'm not sure about that. I feel like excluding transformer layers completely, as in option C, might be a better approach.

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Dalene

4 months ago

I think adding more layers, like in option A, could help improve the fine-tuning process.

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Margart

4 months ago

I agree, adding more layers can improve the model's performance during fine-tuning.

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Cortney

5 months ago

Option D seems to be the way to go. Restricting updates to a specific group of transformer layers helps maintain the model's overall efficiency during fine-tuning.

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