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Indobertnews
Indonesian text classification model fine-tuned based on indolem/indobert-base-uncased, achieving 79.54% accuracy on the evaluation set
Downloads 42
Release Time : 2/12/2023
Model Overview
This model is a classification model for Indonesian news texts, fine-tuned based on the BERT architecture, suitable for text classification tasks
Model Features
Indonesian language optimization
BERT model specifically optimized for Indonesian text
Efficient fine-tuning
Achieves 79.54% accuracy with just 3 training rounds on the base model
Lightweight
Based on the base version of BERT model, suitable for deployment in resource-limited environments
Model Capabilities
Indonesian text classification
News content analysis
Use Cases
News media
News classification
Automatically classify Indonesian news into predefined categories
79.54% accuracy
Content moderation
Content classification
Classify and manage user-generated content in Indonesian
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