Fine Tuning And Domain Adaptation For Custom Entity Types

via “fine-tuning and domain adaptation for custom entity types”

token-classification model by undefined. 18,78,235 downloads.

Unique: Provides a strong pre-trained encoder (BERT base with 110M parameters) that captures general English language patterns, enabling efficient transfer to new NER tasks with minimal labeled data. Fine-tuning only requires updating the task-specific classification head (768 → num_classes) while freezing or lightly updating the encoder, reducing training time and data requirements.

vs others: Requires 10-100x fewer labeled examples than training a BERT model from scratch, and outperforms CRF or BiLSTM baselines on small datasets due to stronger pre-trained representations.