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Developed by shank250
This model is a fine-tuned version based on bert-base-uncased, focusing on improving recall performance for specific tasks
Large Language Model
Transformers
Open Source License:Apache-2.0#BERT fine-tuning#High recall rate#Text classification
Downloads 23
Release Time : 4/11/2025

Model Overview

A text processing model based on the BERT architecture, demonstrating excellent recall performance after fine-tuning for specific tasks

Model Features

High recall performance
Achieves a recall rate of 0.9020 on the evaluation set, suitable for applications with high recall requirements
Powerful foundation based on BERT
Built on bert-base-uncased, inheriting the powerful text understanding capabilities of the BERT model
Efficient fine-tuning
Only requires 3 training epochs to achieve good results, with training loss decreasing from 0.6766 to 0.27

Model Capabilities

Text classification
Natural language understanding
Contextual feature extraction

Use Cases

Text analysis
Sensitive content detection
Identify sensitive content or specific category information in text
High recall ensures minimal missed detections
Intent recognition
Analyze user input for intent classification
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