BERT_NER_Ep5-finetuned-ner Open Source Model - Precise Named Entity Recognition, a Practical Choice for Free Deployment

BERT NER Ep5 Finetuned Ner

Developed by suwani

A named entity recognition (NER) model fine-tuned based on bert-base-cased, achieving an F1 score of 0.6868 on the evaluation set

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Release Time : 3/2/2022

Model Overview

This model is a fine-tuned version of bert-base-cased on an unknown dataset, primarily used for named entity recognition tasks.

High-performance NER Recognition

Achieves an F1 score of 0.6868 and accuracy of 0.9004 on the evaluation set

Based on BERT Architecture

Uses bert-base-cased as the base model, with strong contextual understanding capabilities

Fine-tuned

After 5 rounds of fine-tuning, the model's performance has gradually improved

Named Entity Recognition

Text Analysis

Entity Classification

Text Processing

Document Entity Extraction

Extract entities such as person names, place names, and organization names from documents

F1 score 0.6868

Information Extraction

Extract structured information from unstructured text

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	288	0.3675	0.5906	0.5854	0.5880	0.8802
0.4803	2.0	576	0.3456	0.5863	0.7371	0.6531	0.8864
0.4803	3.0	864	0.3273	0.6478	0.7091	0.6771	0.8987
0.2233	4.0	1152	0.3441	0.6539	0.7226	0.6865	0.9001
0.2233	5.0	1440	0.3553	0.6526	0.7248	0.6868	0.9004

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