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Xlm Roberta Base Ft Udpos28 La

Developed by wietsedv
A multilingual POS tagging model based on XLM-RoBERTa, specifically optimized for Latin, supporting POS tagging tasks in multiple languages.
Downloads 14
Release Time : 3/2/2022

Model Overview

This model is a multilingual POS tagging model based on the XLM-RoBERTa architecture, trained on the Universal Dependencies dataset v2.8, with special optimization for Latin.

Model Features

Multilingual support
Supports POS tagging tasks in multiple languages, including Latin, English, German, French, etc.
High accuracy
Achieves 92.9% accuracy in Latin POS tagging tasks, demonstrating excellent performance.
Based on Universal Dependencies dataset
Trained on the Universal Dependencies dataset v2.8, ensuring generalization across multiple languages.

Model Capabilities

POS tagging
Multilingual text processing
Token classification

Use Cases

Natural Language Processing
Latin text analysis
Performs POS tagging on Latin texts, assisting linguists and researchers in analyzing text structures.
Accuracy up to 92.9%
Multilingual text processing
Supports POS tagging in multiple languages, suitable for multilingual text processing tasks.
Performs well across multiple languages
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