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clincolnoz/mmbert-small-ner

sourceHugging Faceupdated 18d agoView on Hugging Face

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Model Card

mmBERT-small fine-tuned for multilingual NER

Token classification (PER / ORG / LOC, IOB2) fine-tuned from `jhu-clsp/mmBERT-small` on a 32-language news NER dataset.

Training

—lr 8e-5, up to 10 epochs with early stopping (patience 3) on validation F1, warmup 0.1, weight decay 0.01, max length 256
—Training labels denoised by masking contradictory repeat mentions from the loss
—Uniform weight average of 3 seeds

Validation results

Leak-free, stratified validation split, seqeval micro scores at 256-token truncation.

metric	value
F1	0.7347
precision	0.6662
recall	0.8189

Per class F1: LOC 0.7804, ORG 0.6953, PER 0.7876.

Usage

python

from transformers import pipeline

ner = pipeline("token-classification", model="clincolnoz/mmbert-small-ner", aggregation_strategy="simple")
ner("Angela Merkel met executives from Siemens in Munich.")