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Finance Ner V0.0.8 Finetuned Ner
This model is a named entity recognition model fine-tuned on a financial domain dataset, capable of accurately identifying named entities in financial texts.
Downloads 116
Release Time : 8/22/2023
Model Overview
A financial domain named entity recognition model fine-tuned based on dslim/bert-base-NER, optimized specifically for financial information processing.
Model Features
High-precision Recognition
Achieved nearly perfect accuracy (1.0000) and extremely low loss (0.0001) on the evaluation set.
Excellent Performance in Multiple Metrics
Precision of 0.9994, recall of 0.9997, and an F1 score of 0.9995, with excellent performance in all metrics.
Optimized for the Financial Domain
Specifically fine-tuned for financial texts, suitable for financial information processing scenarios.
Model Capabilities
Financial Text Entity Recognition
Named Entity Classification
Use Cases
Financial Information Processing
Financial News Analysis
Extract entities such as company names, person names, and financial products from financial news.
Identify financial-related entities with high accuracy.
Financial Report Processing
Automatically identify key entity information in financial reports.
Quickly and accurately extract entities related to financial data.
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