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MEVZU N°128ISTANBUL

MEVZU N° TAG / VOL. 160

#training

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Wiki

10
§01Glossary

Synthetic Data

Training data generated by another model rather than (or in addition to) real-world data.

EN
Synthetic Data
TR
Sentetik Veri
§02Glossary

RLHF — Reinforcement Learning from Human Feedback

An alignment technique that trains a reward model from human preferences and then optimises the LLM against it.

EN
RLHF (Reinforcement Learning from Human Feedback)
TR
RLHF — İnsan Geri Bildirimiyle Pekiştirmeli Öğrenme
§03Glossary

LoRA (Low-Rank Adaptation)

A fine-tuning technique that trains only small low-rank matrices instead of every weight, dramatically cutting memory.

EN
LoRA (Low-Rank Adaptation)
TR
LoRA (Düşük-Mertebeli Adaptasyon)
§04Glossary

DPO — Direct Preference Optimization

An RLHF alternative that directly optimises a model on preference data, skipping the explicit RL loop.

EN
DPO (Direct Preference Optimization)
TR
DPO — Doğrudan Tercih Optimizasyonu
§05Glossary

Pre-training

The initial training phase where a model learns general language ability from trillions of tokens of generic data.

EN
Pre-training
TR
Ön Eğitim
§06Glossary

Masked Language Modeling

A training objective where the model learns to predict tokens that have been masked out of a sentence.

EN
Masked Language Modeling
TR
Maskeli Dil Modelleme
§07Glossary

Model FLOPs Utilization (MFU)

How much of a model's theoretical peak FLOPs is actually delivered during real training — a key efficiency metric.

EN
Model FLOPs Utilization (MFU)
TR
Model FLOPs Kullanımı (MFU)
§08Glossary

Post-training

The stage after pre-training that turns a raw model into a helpful, safe, instruction-following assistant.

EN
Post-training
TR
Sonrası-Eğitim
§09Glossary

Fine-tuning

Adapting a pre-trained model to a specific task using smaller, targeted data.

EN
Fine-tuning
TR
İnce Ayar (Fine-tuning)
§10Glossary

QLoRA

A LoRA variant combined with quantisation that lets you fine-tune 65B models on a single consumer GPU.

EN
QLoRA
TR
QLoRA