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MLA-C01 ML Model Development Practice Question

A company wants to use SageMaker to fine-tune a foundation model for a text generation task using RLHF (Reinforcement Learning from Human Feedback). Which THREE components are required in the RLHF pipeline?

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

A pre-trained base model

RLHF typically requires: a pre-trained base model to start, a reward model trained on human preferences, and a reinforcement learning algorithm (like PPO) to update the base model. A LoRA adapter is optional but not required. A classifier is not the same as a reward model.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • A LoRA adapter for parameter-efficient fine-tuning

    Why it's wrong here

    LoRA is optional and not a required component of RLHF.

  • A pre-trained base model

    Why this is correct

    The base model is the starting point for RLHF fine-tuning.

  • A classifier to distinguish generated text from real text

    Why it's wrong here

    A classifier is not part of standard RLHF; a reward model is used instead.

  • A reward model trained on human preferences

    Why this is correct

    The reward model provides feedback during RL training.

  • A reinforcement learning algorithm such as PPO

    Why this is correct

    PPO is commonly used to update the policy based on reward signals.

About these practice questions

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Same concept, more angles

1 more way this is tested on MLA-C01

These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.

Variation 1. A company is fine-tuning a large language model using reinforcement learning from human feedback (RLHF). Which THREE components are typically required?

hard
  • A.A discriminative classifier
  • B.A reference model
  • C.A reward model
  • D.A policy model (the LLM)
  • E.A value function
JA

Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

This MLA-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the MLA-C01 exam.