B

Bert Spam Classification Model

Developed by fzn0x
This is an English spam SMS classification model fine-tuned from the bert-base-uncased model, capable of accurately distinguishing between spam and legitimate SMS messages.
Downloads 209
Release Time : 4/9/2025

Model Overview

This BERT-based model is specifically designed for English SMS spam classification tasks, effectively identifying marketing, scam, and other spam messages.

Model Features

High Accuracy Classification
Leveraging BERT's powerful semantic understanding to accurately distinguish spam from legitimate SMS messages.
Easy to Use
Provides out-of-the-box prediction interfaces, requiring only a few lines of code to integrate into applications.
Lightweight Model
Based on BERT-base rather than larger variants, maintaining performance while reducing resource consumption.

Model Capabilities

English Text Classification
Spam SMS Detection
Natural Language Understanding

Use Cases

Communication Security
SMS Filtering System
Integrated into mobile SMS applications to automatically filter spam messages.
Reduces the number of spam messages received by users.
Customer Support Protection
Identifies and blocks spam messages sent to customer support systems.
Improves customer support efficiency.
Data Analysis
Spam SMS Analysis
Batch analysis of spam message ratios in SMS databases.
Helps understand spam SMS trends.
Featured Recommended AI Models
ยฉ 2025AIbase