Open-source xlm-roberta-base-finetuned-panx-en model - Free deployment to support named entity recognition tasks

Xlm Roberta Base Finetuned Panx En

Developed by Eleven

A token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base, used for named entity recognition tasks

Sequence Labeling

Transformers

Open Source License:MIT #Multilingual NER #XLM-RoBERTa Fine-tuning #PAN-X Dataset

Downloads 15

Release Time : 7/5/2022

Model Overview

This model is a fine-tuned version of XLM-RoBERTa-base on the PAN-X.en dataset, primarily used for token classification tasks such as named entity recognition. It achieved an F1 score of 0.692 on the evaluation set.

Model Features

Multilingual Foundation

Based on the XLM-RoBERTa model, it has the potential to handle multilingual text

Domain Adaptation

Specially fine-tuned for the PAN-X.en dataset, improving performance in specific domains

Efficient Training

Achieves good results with just 3 training epochs

Model Capabilities

Named Entity Recognition

Text Token Classification

Sequence Labeling

Use Cases

Information Extraction

News Entity Recognition

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

F1 score 0.692

Knowledge Graph Construction

Entity Extraction

Extract entities from unstructured text for knowledge graph construction

Property	Details
Model Type	Fine - tuned version of xlm - roberta - base
Training Data	xtreme dataset
Metrics	F1 (0.6922 on evaluation set)

Training Loss	Epoch	Step	Validation Loss	F1
1.1465	1.0	50	0.5838	0.4777
0.5055	2.0	100	0.4477	0.6374
0.3713	3.0	150	0.3921	0.6922

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご

Xlm Roberta Base Finetuned Panx En

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 xlm-roberta-base-finetuned-panx-en

🚀 Quick Start

📚 Documentation

Model Information

Training and Evaluation

Training Hyperparameters

Training Results

Framework Versions

📄 License