Open-source model xlm-roberta-base-finetuned-panx-de: Accurately implement German tagging and classification functions

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Xlm Roberta Base Finetuned Panx De

Developed by haesun

German token classification model fine-tuned on the xtreme dataset based on XLM-RoBERTa-base

Sequence Labeling

Transformers

Open Source License:MIT #Multilingual Tag Classification #German Entity Recognition #High F1 Score

Downloads 25

Release Time : 6/30/2022

Model Overview

This model is a token classification model fine-tuned on the PAN-X German dataset based on the XLM-RoBERTa-base architecture, primarily used for named entity recognition tasks in German text.

Model Features

Multilingual Pre-trained Foundation

Based on the XLM-RoBERTa-base model with strong cross-language understanding capabilities

High-Precision German NER

Achieves an F1 score of 0.8657 on the PAN-X German validation set

Lightweight Fine-tuning

Only requires 3 training epochs to achieve good performance

Model Capabilities

German Text Processing

Named Entity Recognition

Token Classification

Use Cases

Natural Language Processing

German Text Entity Recognition

Identify entities such as person names, place names, and organization names from German text

F1 score 0.8657

Multilingual Application Integration

Serve as the German processing component in a multilingual NLP system

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

Training Loss	Epoch	Step	Validation Loss	F1
0.257	1.0	525	0.1557	0.8218
0.126	2.0	1050	0.1460	0.8521
0.0827	3.0	1575	0.1338	0.8657

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Xlm Roberta Base Finetuned Panx De

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