Fine-Tune Vision AI Models That Beat GPT-4 | Fine Tuning Gemma 3 4B with Datawizz

Datawizz · Beginner ·🛠️ AI Tools & Apps ·6mo ago
Learn how to train specialized vision models that outperform GPT-4.1 while being faster and cheaper! In this comprehensive tutorial, I'll show you how to fine-tune the Gemma 3 4B model on the Datawizz platform to create a food recognition AI that extracts dish names, ingredients, nutritional info, and portion sizes from images. We'll use the MMFood100K dataset and create custom evaluators to benchmark our model against GPT-4.1, proving that smaller, specialized models can deliver better results for domain-specific tasks. 🚀 What You'll Learn: - Fine-tuning vision models on custom datasets - …
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Chapters (12)

Introduction & Demo Overview
0:45 Dataset Overview (MMFood100K from Hugging Face)
1:33 Creating the Prompt Template in Datawizz
4:10 Importing & Preparing the Dataset
7:10 Fine Tuning the Model
9:09 Training Results & Loss Curves
10:20 Manually Testing the Model
12:44 Creating Custom Evaluators
19:36 Running Full Evaluation Suite
21:10 Benchmark Results & Analysis
24:00 Creating Production Endpoints
25:04 Summary & Conclusion
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Neil Patel