Electra-small-discriminator-finetuned-ner Open-source Named Entity Recognition Model - Precise Recognition Based on Fine-tuned Data

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Electra Small Discriminator Finetuned Ner

Developed by dbsamu

A named entity recognition model based on ELECTRA-small architecture, fine-tuned on the wikiann dataset

Sequence Labeling

Transformers

Open Source License:Apache-2.0 #Named Entity Recognition #High Accuracy NER #Small-scale ELECTRA

Downloads 16

Release Time : 3/2/2022

Model Overview

This model is a discriminator based on the ELECTRA-small architecture, specifically fine-tuned for Named Entity Recognition (NER) tasks, capable of identifying named entities in text.

Model Features

Efficient Small Model

Based on the ELECTRA-small architecture, it maintains high performance while having a compact model size

Accurate Entity Recognition

Achieves an F1 score of 0.74 on the wikiann dataset, accurately identifying named entities in text

Fast Inference

The small model design enables quick inference, suitable for real-time applications

Model Capabilities

Named Entity Recognition

Text Token Classification

English Text Processing

Use Cases

Information Extraction

News Article Entity Extraction

Extract entities such as person names, locations, and organization names from news articles

F1 score reaches 0.74

Document Automation Processing

Automatically process documents and tag key entities within them

Knowledge Graph Construction

Knowledge Graph Entity Extraction

Extract entities from unstructured text for building knowledge graphs

Property	Details
Model Type	Fine - tuned version of google/electra-small-discriminator
Training Data	wikiann
Metrics	precision, recall, f1, accuracy

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.5465	1.0	1250	0.4158	0.6932	0.7201	0.7064	0.8735
0.4037	2.0	2500	0.3817	0.7191	0.7470	0.7328	0.8828
0.3606	3.0	3750	0.3685	0.7331	0.7543	0.7435	0.8883

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Electra Small Discriminator Finetuned Ner

Model Overview

Model Features

Model Capabilities

Use Cases

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