English Version
What Is Pretraining
Pretraining builds the core knowledge of a large language model. The model learns from large text datasets. It learns grammar, facts, reasoning patterns, and general language skills. It learns next word prediction during this phase. Pretraining shapes the base model behavior.
What Is Fine Tuning
Fine tuning adjusts the pretrained model for a specific task. It uses a smaller dataset. It shapes the model toward targeted outputs like support answers, coding help, or medical text analysis. Fine tuning changes the model goals to match the task.
Main Differences
- Goal: Pretraining builds general language ability. Fine tuning adapts this ability to a task.
- Data size: Pretraining uses huge datasets. Fine tuning uses focused datasets.
- Cost: Pretraining is heavy and expensive. Fine tuning is lighter.
- Output behavior: Pretrained models respond in a generic way. Fine tuned models behave in a controlled way.
- Training signals: Pretraining uses next token prediction. Fine tuning uses labeled data or preference data.
Why This Matters
Understanding both steps helps you design better AI systems. You know when to use a base model. You know when to fine tune for accuracy, control, or reliability.
Moroccan Darija Version
Ash kayn f Pretraining
Pretraining kaybni l asasi dyal l model. L model kayt3llam men dbara dyal nass kbira. Kayt3llam l grammar, l info, w l patterns dyal reasoning. Kayt3llam kifash ykml l kalma jaya. Pretraining kaydir l base dyal l model.
Ash kayn f Fine Tuning
Fine tuning kaywajja l model l chi task mo3ayan. Kayst3ml data sghira w mkhasssa. Kaykhelli l model yjib jawabat mkhasssin b7al support, code, ola tahlil dyal nass tibi. Fine tuning kaybdl hadaf l model bach yntawej l task.
Farqu binathom
- Goal: Pretraining kaydir l skills l 3amma. Fine tuning kaywajja had skills l task.
- Data: Pretraining kayst3ml data kbira. Fine tuning kayst3ml data mkhasssa.
- Cost: Pretraining ghali. Fine tuning ahwan.
- Behavior: Model pretrained kayjib jawab 3amm. Model fine tuned kayjib jawab mkhassas.
- Training: Pretraining kayst3ml next token prediction. Fine tuning kayst3ml data labeled ola preference.
3lach hadi mohemma
Ila fhamti pretraining w fine tuning ghat3rf kifash tsawb systems zwinin f AI. Ghatsst3ml base model f wa9t mo3ayan. W ghatt fine tune ila bghiti accuracy w control kbar.