Fine
term_id: fine
Category: basic_concepts
Definition
Fine-tuning involves taking a general-purpose model trained on large datasets and further training it on a smaller, specialized dataset to improve performance on specific tasks. This technique leverages existing knowledge while adjusting weights to fit new contexts, making it cost-effective and efficient. It is widely used in natural language processing and computer vision to achieve high accuracy without training models from scratch.
Summary
Fine-tuning refers to the process of adapting a pre-trained AI model to a specific task or domain with additional data.
Key Concepts
- Transfer Learning
- Pre-trained Models
- Domain Adaptation
- Weight Adjustment
Use Cases
- Medical image diagnosis
- Legal document analysis
- Custom sentiment analysis