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Xlm Roberta Base Finetuned Panx En

Developed by cj-mills
A token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base, primarily used for named entity recognition tasks.
Sequence Labeling
Transformers
Open Source License:MIT#Multilingual Tag Classification#XLM-RoBERTa Fine-tuning#PAN-X Dataset
Downloads 14
Release Time : 4/8/2022

Model Overview

This model is a token classification model fine-tuned on the PAN-X.en dataset based on the XLM-RoBERTa-base architecture, suitable for multilingual named entity recognition tasks.

Model Features

Multilingual Support
Based on the XLM-RoBERTa architecture, it has multilingual processing capabilities.
Efficient Fine-tuning
Fine-tuned for 3 epochs on the PAN-X.en dataset, achieving an F1 score of 0.5794.
Token Classification
Specifically designed for token classification tasks such as named entity recognition.

Model Capabilities

Named Entity Recognition
Text Token Classification
Multilingual Text Processing

Use Cases

Natural Language Processing
Named Entity Recognition
Identify and classify named entities (such as person names, locations, organization names, etc.) from text.
Achieved an F1 score of 0.5794 on the PAN-X.en dataset.
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