BERT_NER_Ep6_PAD_50 Open-Source Named Entity Recognition Model - Fine-Tuning Training for Information Extraction

BERT NER Ep6 PAD 50 Finetuned Ner

Developed by suwani

A named entity recognition (NER) model fine-tuned based on bert-base-cased, trained for 6 epochs on an unknown dataset with moderate performance

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Release Time : 3/2/2022

Model Overview

This model is a BERT-based named entity recognition model, specifically designed to identify and classify named entities from text

Moderate Performance

Achieves an F1 score of 0.6926 and accuracy of 0.9020 on the evaluation set

BERT-based Architecture

Utilizes BERT's powerful contextual understanding capabilities for entity recognition

6 Epochs of Fine-tuning

Fine-tuned for 6 epochs on the base model

Text Entity Recognition

Named Entity Classification

Information Extraction

News Entity Recognition

Identify entities such as person names, locations, and organizations from news text

Biomedical Text Processing

Recognize specialized terms like diseases and drugs in medical literature

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	288	0.3648	0.5949	0.5907	0.5928	0.8792
0.4815	2.0	576	0.3400	0.5860	0.7390	0.6536	0.8867
0.4815	3.0	864	0.3217	0.6404	0.7129	0.6747	0.8992
0.2206	4.0	1152	0.3430	0.6413	0.7321	0.6837	0.8995
0.2206	5.0	1440	0.3560	0.6464	0.7377	0.6890	0.9010
0.1487	6.0	1728	0.3741	0.6510	0.7399	0.6926	0.9020

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