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Xlm Roberta Large Ner Spanish
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Xlm Roberta Large Ner Spanish
Developed by MMG
A Spanish named entity recognition model fine-tuned based on the XLM-Roberta-large architecture, with excellent performance on the CoNLL-2002 dataset.
Downloads 767.35k
Release Time : 3/2/2022
Model Overview
This model is specifically designed for named entity recognition tasks in Spanish text, capable of identifying entities such as person names, place names, and organization names.
Model Features
High Performance
Achieves an F1 score of 89.17 on the CoNLL-2002 Spanish test set, making it one of the best Spanish NER models available.
Based on XLM-Roberta
Leverages the powerful pre-training capabilities of XLM-Roberta-large, with excellent cross-language representation abilities.
Optimized for Spanish
Specifically optimized for the characteristics of Spanish text, accurately identifying various named entities in Spanish.
Model Capabilities
Spanish text processing
Named Entity Recognition
Entity classification
Use Cases
Text Analysis
News Text Analysis
Extracting key information such as person names, place names, and organization names from Spanish news articles
Accurately identifies various named entities with an F1 score of 89.17
Business Document Processing
Processing entity information in Spanish business contracts or reports
Efficiently extracts key information such as company names and locations from contracts
Information Extraction
Knowledge Graph Construction
Extracting entities from Spanish text for building knowledge graphs
Provides high-quality entity recognition results
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