Oracle Exam 1Z0-1127-24 Topic 3 Question 13 Discussion

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

Question #: 13
Topic #: 3

[All 1Z0-1127-24 Questions]

What is the purpose of Retrievers in LangChain?

ATo break down complex tasks into smaller steps

BTo retrieve relevant information from knowledge bases

CTo train Large Language Models

DTo combine multiple components into a single pipeline

Show Suggested Answer

Suggested Answer: D

by Camellia at Sep 13, 2024, 12:24 AM

Limited Time Offer

25%

Off

Get Premium 1Z0-1127-24 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Janna

7 months ago

Exactly, it helps us understand how well the model is performing overall.

upvoted 0 times

...

Lorrie

7 months ago

Yes, that's correct. It shows the difference between the predicted values and the actual values.

upvoted 0 times

...

Ben

7 months ago

So, 'Loss' is basically a measure of how accurate the model is, right?

upvoted 0 times

...

Janna

7 months ago

I agree with Lorrie, lower values indicate better performance.

upvoted 0 times

...

Diane

7 months ago

Haha, I'll just go with whatever the AI says is the correct answer. Can't argue with the experts, right?

upvoted 0 times

...

Norah

8 months ago

I think D is the right choice. Loss indicates the level of incorrectness in the model's predictions, and lower values mean better performance.

upvoted 0 times

Lorrie

6 months ago

Exactly, it's important to monitor loss to ensure the model is performing well.

upvoted 0 times

...

Daron

6 months ago

So, the lower the loss, the more accurate the model's predictions are.

upvoted 0 times

...

Viola

6 months ago

Yes, that's right. Loss measures the level of incorrectness in the model's predictions.

upvoted 0 times

...

Shaun

6 months ago

I agree, D is the correct choice. Lower loss values indicate better performance.

upvoted 0 times

...

Lorrie

8 months ago

I think 'Loss' measures the level of incorrectness in the model's predictions.

upvoted 0 times

...

Pete

8 months ago

Option A seems to be the correct answer. Loss measures the difference in accuracy between the initial model and the fine-tuned deployed model.

upvoted 0 times

Denny

7 months ago

That makes sense, it's important to measure the improvement in accuracy from the initial model to the fine-tuned one

upvoted 0 times

...

Gerald

7 months ago

I think the answer is A) The difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

upvoted 0 times

...