From the course: Hands-On AI: Building Your First Conversational AI Chatbot
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Fine-tuning essentials: Datasets, overfitting, and generalization
From the course: Hands-On AI: Building Your First Conversational AI Chatbot
Fine-tuning essentials: Datasets, overfitting, and generalization
- [Instructor] In this video, we'll explore the foundational ideas behind fine-tuning your chat bot, focusing on how to prepare your dataset and how to understand crucial training concepts like overfitting, underfitting, and generalization. Let's begin with the dataset. Think of your dataset as a customized training manual designed for your chat bot. This dataset isn't just any random collection of text. It should reflect the types of conversations you want your chat bot to participate in. If you're building a mental health support chat bot, for example, your data set should contain thoughtful, compassionate exchanges that mirror the dialogue between a trained counselor and someone seeking help. Every example in your dataset serves as a learning opportunity for your model. So the more precisely these examples reflect your chat bot's purpose, the more effective your fine-tuning will be. But precision is only part of the picture. A strong fine-tuning dataset also needs to be diverse…
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