3# Interview Questions on Large Language Models (LLMs)

❓ Question: Can you provide a high-level overview of the training process of ChatGPT?

Can you provide a high-level overview of the training process of ChatGPT?

Answer:

ChatGPT is trained in 3 steps:

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1. 📚 𝗣𝗿𝗲-𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴:
   • ChatGPT undergoes an initial phase called pre-training.
   • During this phase, Large Language Models (LLMs) like ChatGPT, such as GPT-3, are trained on an extensive dataset sourced from the internet.
   • The data is subjected to cleaning, preprocessing, and tokenization.
   • Transformer architectures, a best practice in natural language
   processing, are widely used during this phase.
   • The primary objective here is to enable the model to predict the next
   word in a given sequence of text.
   • This phase equips the model with the capability to understand language patterns but does not yet provide it with the ability to comprehend instructions or questions.
2. 🛠️ 𝗦𝘂𝗽𝗲𝗿𝘃𝗶𝘀𝗲𝗱 𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 𝗼𝗿 𝗜𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻 𝗧𝘂𝗻𝗶𝗻𝗴:
   • The next step is supervised fine-tuning or instruction tuning.
   • During this stage, the model is exposed to user messages as input and
   AI trainer responses as targets.
   • The model learns to generate responses by minimizing the difference between its predictions and the provided responses.
   • This phase marks the transition of the model from merely understanding language patterns to understanding and responding to instructions.
3. 🔄 𝗥𝗲𝗶𝗻𝗳𝗼𝗿𝗰𝗲𝗺𝗲𝗻𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗳𝗿𝗼𝗺 𝗛𝘂𝗺𝗮𝗻 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 (𝗥𝗛𝗙𝗟):
   • Reinforcement Learning from Human Feedback (RHFL) is employed as a subsequent fine-tuning step.
   • RHFL aims to align the model’s behavior with human preferences, with a focus on being helpful, honest, and harmless (HHH).
   • RHFL consists of two crucial sub-steps:
   • 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗥𝗲𝘄𝗮𝗿𝗱 𝗠𝗼𝗱𝗲𝗹 𝗨𝘀𝗶𝗻𝗴 𝗛𝘂𝗺𝗮𝗻 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸: In this sub-step,
   multiple model outputs for the same prompt are generated and ranked by human labelers to create a reward model. This model learns human
   preferences for HHH content.
   • 𝗥𝗲𝗽𝗹𝗮𝗰𝗶𝗻𝗴 𝗛𝘂𝗺𝗮𝗻𝘀 𝘄𝗶𝘁𝗵 𝗥𝗲𝘄𝗮𝗿𝗱 𝗠𝗼𝗱𝗲𝗹 𝗳𝗼𝗿 𝗟𝗮𝗿𝗴𝗲-𝗦𝗰𝗮𝗹𝗲 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴: Once the reward model is trained, it can replace humans in labeling data, streamlining the feedback loop. Feedback from the reward model is used to further fine-tune the LLM at a large scale.
   • RHFL plays a pivotal role in enhancing the model’s behavior and ensuring alignment with human values, thereby guaranteeing useful, truthful, and safe responses.

ChatGPT Training Process — https://medium.com/@masteringllm/llm-training-a-simple-3-step-guide-you-wont-find-anywhere-else-98ee218809e5

#𝗖𝗼𝗺𝗺𝗲𝗻𝘁 𝗼𝗻 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁 𝗽𝗼𝗶𝗻𝘁𝘀 𝘆𝗼𝘂 𝗳𝗲𝗲𝗹 𝘆𝗼𝘂 𝘀𝗵𝗼𝘂𝗹𝗱 𝗮𝗱𝗱 𝗶𝗻 𝗮𝗻 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝗳𝗼𝗿 𝘁𝗵𝗶𝘀 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻.

A detailed blog about the training process can be found in the comments below.

LLM Training: A Simple 3-Step Guide You Won’t Find Anywhere Else!

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1# Interview Questions on Large Language models (LLMs

2# Interview Questions on Large Language Models (LLMs)

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