AI Terms Dictionary

Definition

Fine-tuning involves taking a model already trained on a large, general dataset and further training it on a specialized dataset. This allows the model to retain general knowledge while acquiring task-specific features. It is computationally cheaper than training from scratch and typically requires less data, making it the standard approach for deploying large language models in niche applications like legal analysis or medical diagnosis.

Summary

The process of adapting a pre-trained model to a specific downstream task using a smaller dataset.

Key Concepts

• Transfer Learning
• Pre-trained Model
• Task-Specific Adaptation
• Learning Rate

Use Cases

• Adapting LLMs for customer service chatbots
• Specializing image classifiers for medical diagnostics
• Customizing speech recognition for specific accents

Code Example

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from transformers import AutoModelForSequenceClassification
model = AutoModelForSequenceClassification.from_pretrained('bert-base-uncased')
# Freeze base layers
for param in model.bert.parameters():
    param.requires_grad = False
# Train only classification head

Related Terms

• Pre-training
• Prompt Engineering
• LoRA
• Supervised Learning