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Xlm Roberta Base Finetuned Panx All

Developed by okite97
A multilingual named entity recognition model fine-tuned on the PANX dataset based on the xlm-roberta-base model
Large Language Model
Transformers
Open Source License:MIT#Multilingual NLP#High F1 Score#Text Classification
Downloads 15
Release Time : 7/9/2022

Model Overview

This model is a fine-tuned version of the XLM-RoBERTa base model on the PANX multilingual named entity recognition dataset, suitable for entity recognition tasks in multilingual texts.

Model Features

Multilingual Support
Based on the XLM-RoBERTa architecture, it supports named entity recognition in multiple languages.
High Performance
Achieves an F1 score of 0.8538 on the evaluation set, demonstrating excellent performance.
Transfer Learning
Fine-tuned after pre-training on large-scale multilingual corpora, it has strong generalization capabilities.

Model Capabilities

Multilingual text processing
Named entity recognition
Sequence labeling

Use Cases

Natural Language Processing
Multilingual Document Entity Extraction
Identify and extract entities such as person names, locations, and organization names from multilingual documents.
Achieves an F1 score of 85.38% on the PANX dataset.
Cross-Language Information Extraction
Supports entity recognition in texts of different languages, facilitating cross-language information integration.
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