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).
π 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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