AIREVOLUTION

Model Evaluation and Performance Measurement: Methods for Determining Effectiveness in Language Model Creation

Creating effective large language models (LLMs) involves two critical stages: pre-training and fine-tuning. These stages enable models to progress from capturing broad linguistic knowledge to excelling in specific tasks, powering applications such as automated translation, sentiment analysis, and conversational agents. Rigorous evaluation and performance measurement ensure LLMs meet general and

by Miklós Sebők - Rebeka Kiss • Apr 20, 2025

GenAI textbook Part 5 Chapter 2

Fine-tuning: Adapting General Models for Specific Tasks and Applications

The evolution of machine learning has led to the development of powerful general models, such as BERT, GPT-3, and Vision Transformers (ViT), which have transformed artificial intelligence applications across diverse domains. These models, pre-trained on extensive datasets like Common Crawl for natural language processing or ImageNet for computer vision, demonstrate

by Miklós Sebők - Rebeka Kiss • Apr 15, 2025

GenAI textbook Part 5 Chapter 1

The Pre-Training Process: Principles, Methods, and Mechanisms of Language Pattern Acquisition

Pre-training underpins the capabilities of large-scale language models like BERT and GPT, enabling them to capture linguistic patterns from extensive text corpora. This process equips models with versatile language understanding, adaptable through fine-tuning for tasks such as translation or sentiment analysis. The principles, methods, and mechanisms of pre-training reveal how

by Miklós Sebők - Rebeka Kiss • Apr 10, 2025

Stages of Language Model creation: Pre-training and Fine-tuning