How to Boost Kaggle NLP Scores with BERT, Tree Models, and Smart Post‑Processing

The article analyzes a recent Kaggle essay‑segmentation competition, explains why standard BERT‑based models plateau, and shows how a two‑stage pipeline that combines coarse BERT filtering with a feature‑rich tree model and post‑processing scaling can push scores well beyond the 70‑point barrier.

BERTKaggleNLP

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How to Boost Kaggle NLP Scores with BERT, Tree Models, and Smart Post‑Processing