Bert-base-cased-ner-conll2003 Open-source Named Entity Recognition Model

Bert Base Cased Ner Conll2003

Developed by kamalkraj

A named entity recognition model fine-tuned on the CoNLL2003 dataset based on bert-base-cased

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Release Time : 4/24/2022

Model Overview

This model is a fine-tuned version of bert-base-cased on the CoNLL2003 dataset, primarily used for named entity recognition tasks.

High-precision Named Entity Recognition

Achieved 94.38% precision and 95.25% recall on the CoNLL2003 dataset

Based on BERT Architecture

Uses bert-base-cased as the base model, with strong contextual understanding capabilities

Efficient Training

Only requires 3 epochs of training to achieve excellent performance

Named Entity Recognition

Text Token Classification

Natural Language Processing

News Text Entity Recognition

Identify entities such as person names, locations, and organization names from news texts

F1 score reached 0.9482

Document Information Extraction

Extract key entity information from structured documents

Property	Details
Model Type	Fine - tuned version of bert - base - cased
Training Data	conll2003
Metrics	Precision, Recall, F1, Accuracy, Loss

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