Bert Finetuned Ner 0
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Bert Finetuned Ner 0
Developed by mariolinml
This model is a fine-tuned version of bert-base-cased on an unknown dataset, primarily used for Named Entity Recognition (NER) tasks.
Downloads 15
Release Time : 6/17/2022
Model Overview
A BERT-based Named Entity Recognition model that performs exceptionally well on specific datasets after fine-tuning.
Model Features
High Accuracy
Achieved an accuracy of 92.46% on the evaluation set.
Balanced Performance
Achieved a good balance between precision (51.19%) and recall (42.22%).
BERT Architecture
Fine-tuned based on the powerful bert-base-cased model, inheriting BERT's excellent feature extraction capabilities.
Model Capabilities
Named Entity Recognition
Text Analysis
Information Extraction
Use Cases
Text Processing
Document Entity Recognition
Identify and extract entity information such as person names, place names, and organization names from documents.
F1 score reached 0.4627
Information Extraction System
Serves as the core component of an information extraction system to identify key entities in text.
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