What is pretraining and why is it critical?
Pretraining teaches models the basics before specialization.
How It Works:
Pretraining exposes models to vast unlabeled data, learning general patterns that form the foundation for later fine-tuning on specific tasks.
Key Benefits:
- Data efficiency: Fine-tune with fewer labels.
- Robustness: Learns broad language or vision priors.
- Speed: Shortens downstream training time.
Real-World Use Cases:
- BERT: Pretrained on Wikipedia before NLP tasks.
- Vision Transformers: Pretrained on ImageNet for image tasks.
FAQs
Can I skip pretraining?
How long does it take?
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