bert-conll2003-ner – AI Model by ZaharHR | AlphaNeural AI

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ZaharHR/
bert-conll2003-ner

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token-classification

google-bert/bert-base-cased

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BERT fine-tuned on CoNLL-2003 (NER)

bert-base-cased fine-tuned for Named Entity Recognition on CoNLL-2003.

Recognizes 4 entity types: PER, ORG, LOC, MISC.

Evaluation results

Metric	Score
Precision	0.7058
Recall	0.5080
F1	0.5908
Accuracy	0.9015

Evaluated with seqeval on the CoNLL-2003 test split.

Usage

python

from transformers import pipeline

ner = pipeline("ner", model="ZaharHR/bert-conll2003-ner", aggregation_strategy="simple")
ner("Elon Musk founded SpaceX in California.")

Training details

Base model: bert-base-cased
Dataset: CoNLL-2003
Epochs: 1
Effective batch size: 16 (gradient accumulation)
Optimizer: AdamW, weight decay 0.01
Warmup steps: 500

Label scheme

O, B-PER, I-PER, B-ORG, I-ORG, B-LOC, I-LOC, B-MISC, I-MISC