xlm-roberta-base-finetuned-panx-en Open-Source Model - Free Deployment to Assist in Named Entity Recognition Tasks

Xlm Roberta Base Finetuned Panx En

Developed by V3RX2000

A tag classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base for named entity recognition tasks.

Sequence Labeling

Transformers

Open Source License:MIT #Multilingual Tag Classification #PAN-X Dataset #F1 Optimization

Downloads 15

Release Time : 4/10/2022

Model Overview

This model is a tag classification model fine-tuned on the PAN-X.en dataset based on the XLM-RoBERTa-base architecture, primarily used for named entity recognition (NER) tasks.

Model Features

Multilingual Pre-training Foundation

Based on the XLM-RoBERTa-base architecture with strong cross-lingual representation capabilities

Domain-specific Fine-tuning

Fine-tuned specifically for named entity recognition tasks on the PAN-X.en dataset

Moderate Performance

Achieved an F1 score of 0.7075 on the evaluation set

Model Capabilities

Named Entity Recognition

Text Tag Classification

Use Cases

Information Extraction

News Entity Recognition

Identify entities such as person names, locations, and organization names from news texts

Document Automation Processing

Automatically extract key entity information from documents

Property	Details
Model Type	Fine - tuned version of xlm - roberta - base
Training Data	xtreme dataset
Metrics	F1

Training Loss	Epoch	Step	Validation Loss	F1
1.1493	1.0	50	0.5884	0.4748
0.5135	2.0	100	0.4088	0.6623
0.3558	3.0	150	0.3925	0.7075

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Xlm Roberta Base Finetuned Panx En

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