Indonesian Roberta Base Posp Tagger
This is a POS tagging model fine-tuned based on the Indonesian RoBERTa model, trained on the indonlu dataset for Indonesian text POS tagging tasks.
Downloads 2.2M
Release Time : 3/2/2022
Model Overview
This model is a fine-tuned version of flax-community/indonesian-roberta-base on the indonlu dataset, specifically designed for Indonesian text POS tagging tasks.
Model Features
High-precision POS Tagging
Achieved an F1 score of 96.25% on the test set, demonstrating excellent performance.
Based on RoBERTa Architecture
Utilizes the powerful RoBERTa-base architecture as the foundation model, with superior text comprehension capabilities.
Optimized for Indonesian Language
The model is specifically trained and optimized for Indonesian text.
Model Capabilities
Indonesian POS Tagging
Text Token Classification
Use Cases
Natural Language Processing
Indonesian Text Analysis
Can be used for POS tagging and analysis of Indonesian text
Accuracy reached 96.25%
Linguistic Research
Supports Indonesian linguistic research and teaching applications
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