BERT (base-cased) for CoNLL-2003 NER β€” Full Fine-Tune

This repository contains a BERT base cased model fine-tuned on CoNLL-2003 (parquet version). Evaluated with seqeval (entity-level F1).

πŸ“Š Result (this run)

  • Entity Macro F1: 0.9192

Usage

from transformers import pipeline
clf = pipeline("token-classification", model="starkdv123/conll2003-bert-ner-full", aggregation_strategy="simple")
clf("Chris Hoiles hit his 22nd homer for Baltimore.")

Training summary

  • Base: bert-base-cased
  • Epochs: 3, LR: 3e-5, batch 16/32, max_len 256, weight_decay 0.01, fp16
  • Label alignment: -100 for subword continuations
  • Metric: seqeval F1 (entity-level)

Confusion Matrix

         LOC    MISC       O     ORG     PER
   LOC    411       6      21      32       3
  MISC      9    2213      51      76      14
     O     67     110   38063      58      17
   ORG     31      77      32    2353      10
   PER      3      42      15      24    2689
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Model size
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Tensor type
F32
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Dataset used to train starkdv123/conll2003-bert-ner-full