Week 9 of Naver Boostcamp AI Tech covering NLP competition setup, model experimentation, and leaderboard submissions.

Token-level classification tasks with BERT, covering Named Entity Recognition (NER) and POS tagging for Korean text.

Overview of Korean dependency parsing and single sentence classification tasks in KLUE, including BERT-based model architecture and training pipeline.

BERT-based sentence pair classification covering NLI, semantic text pair similarity, and information retrieval QA.

BERT training pipeline details: tokenizer creation, dataset construction with NSP, masking strategies, segment handling, and truncation.

Practical applications of BERT for sentiment analysis, relation extraction, semantic similarity, NER, and machine reading comprehension.