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Bert Finetuned Ner

Developed by ankitsharma
BERT-base-cased fine-tuned Named Entity Recognition (NER) model
Downloads 14
Release Time : 7/9/2022

Model Overview

This model is a fine-tuned version of bert-base-cased for NER tasks, suitable for named entity recognition.

Model Features

Based on BERT architecture
Uses the powerful bert-base-cased as the base model with excellent text understanding capabilities
Efficient fine-tuning
Achieved good results with only 2 training epochs, validation loss of 0.0554
Mixed precision training
Trained with mixed_float16 precision to improve training efficiency

Model Capabilities

Named Entity Recognition
Text sequence labeling

Use Cases

Text information extraction
Document entity recognition
Identify entities such as person names, locations, and organization names from documents
Biomedical text processing
Identify professional terms and entities in medical literature
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