Glossary › Training

Batch Size

Number of training examples processed in one forward/backward pass. Larger batches give stable gradients but use more memory. Common: 16-512 for fine-tuning, 1-8 for LLM training.

Where this is taught

• Serving LLMs: vLLM, Batching & Throughput — Phase 9: LLMOps & Production Deployment
• Gradient Descent & Optimization — Phase 2: Classical Machine Learning
• CLIP and Contrastive Vision-Language Pretraining — Phase 0: Multimodal Foundations

Related terms

Gradient Accumulation · Learning Rate

More in Training

Backpropagation · Fine-Tuning · Gradient Descent · LoRA (Low-Rank Adaptation) · RLHF · DPO (Direct Preference Optimization) · QLoRA · Learning Rate

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