BERT Base

BERT Base is a foundational bidirectional transformer encoder model used extensively in natural language processing. Current research focuses on improving its efficiency through techniques like model compression (e.g., pruning, knowledge distillation), optimized training procedures, and architectural modifications to accelerate both pre-training and inference. These efforts aim to reduce computational costs and memory requirements while maintaining or even improving accuracy on downstream tasks, making BERT Base more accessible for resource-constrained applications and broadening its impact across the NLP community.