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Xlm Roberta Large Ner Hrl Finetuned Ner

Developed by kinanmartin
A named entity recognition model fine-tuned on a toy dataset based on the xlm-roberta-large-ner-hrl model
Sequence Labeling
Transformers
#Multilingual Named Entity Recognition#High-precision NER#RoBERTa Fine-tuning
Downloads 29
Release Time : 7/11/2022

Model Overview

This model is a multilingual model optimized for named entity recognition tasks, demonstrating excellent performance on toy datasets

Model Features

High-precision Named Entity Recognition
Achieves 91.32% precision and 92.06% recall on the evaluation set
Multilingual Support
Based on the XLM-RoBERTa architecture, capable of processing multilingual text
Efficient Fine-tuning
Requires only 3 training epochs on toy datasets to achieve excellent performance

Model Capabilities

Text Token Classification
Named Entity Recognition
Multilingual Text Processing

Use Cases

Information Extraction
Document Entity Recognition
Identify and classify named entities from documents
97.85% accuracy
Data Annotation
Automated Data Annotation
Automatically annotate named entities for NLP training data
91.69% F1 score
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