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Mbert Bengali Ner
A multilingual BERT-based named entity recognition model for Bengali, used to identify entities such as person names, organization names, and locations in Bengali text.
Downloads 69
Release Time : 3/2/2022
Model Overview
This model is a Bengali named entity recognition Transformer model built on the bert-base-multilingual-uncased pre-trained model and the Wikiann dataset, capable of accurately identifying various named entities in Bengali text.
Model Features
Multilingual Support
Based on the multilingual BERT architecture, it supports processing multiple languages including Bengali.
High-precision Recognition
Trained on the Wikiann dataset, it achieves an F1 score of 0.97105, demonstrating high recognition accuracy.
Rich Entity Types
Capable of identifying three main types of named entities: person names (B-PER), organization names (B-ORG), and locations (B-LOC).
Model Capabilities
Bengali text processing
Named Entity Recognition
Entity classification
Use Cases
Natural Language Processing
Bengali Text Analysis
Extracting key information such as person names, organization names, and locations from Bengali text.
Accurately identifies various named entities with an F1 score of 0.97105
Information Extraction System
A foundational component for building a Bengali information extraction system.
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