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Indobert Lite Large P1

Developed by indobenchmark
IndoBERT is an advanced language model for Indonesian, based on the BERT architecture, trained using masked language modeling and next sentence prediction objectives.
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Release Time : 3/2/2022

Model Overview

IndoBERT is a pre-trained language model specifically designed for Indonesian, primarily used for natural language understanding tasks. The model is trained on a large-scale Indonesian corpus and can effectively handle semantic understanding tasks for Indonesian text.

Model Features

Optimized for Indonesian
Specially designed and trained for Indonesian, enabling better understanding and processing of Indonesian text.
Lightweight Model
Compared to the full version of IndoBERT, the Lite version has fewer parameters, making it suitable for resource-limited environments.
Large-scale Training Data
Trained using the Indo4B dataset (23.43GB of Indonesian text).

Model Capabilities

Indonesian text understanding
Masked language modeling
Next sentence prediction

Use Cases

Natural Language Processing
Text Classification
Classifying Indonesian text
Named Entity Recognition
Identifying named entities in Indonesian text
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