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

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

Question #: 13
Topic #: 3

What does "Loss" measure in the evaluation of OCI Generative AI fine-tuned models?

The difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

AThe difference between the accuracy of the model at the beginning of training and the accuracy of the deployed model

BThe percentage of incorrect predictions made by the model compared with the total number of predictions in the evaluation

CThe improvement in accuracy achieved by the model during training on the user-uploaded data set

DThe level of incorrectness in the models predictions, with lower values indicating better performance

Show Suggested Answer

Suggested Answer: D

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

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Janna

2 months ago

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

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Lorrie

2 months ago

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

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Ben

2 months ago

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

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Janna

2 months ago

I agree with Lorrie, lower values indicate better performance.

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Diane

3 months ago

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

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Norah

3 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.

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Lorrie

1 months ago

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

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Daron

1 months ago

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

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Viola

1 months ago

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

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Shaun

1 months ago

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

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Lorrie

3 months ago

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

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Pete

3 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.

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Denny

2 months ago

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

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Gerald

3 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

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