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Roberta Large Wechsel Ukrainian
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Roberta Large Wechsel Ukrainian
Developed by benjamin
RoBERTa-large model migrated to Ukrainian using the WECHSEL method, excelling in NER and POS tagging tasks
Downloads 75
Release Time : 4/3/2022
Model Overview
This model is a Ukrainian version of RoBERTa-large migrated via the WECHSEL method, specifically optimized for Ukrainian natural language processing tasks, particularly excelling in named entity recognition (NER) and part-of-speech tagging.
Model Features
Cross-lingual transfer optimization
Uses the WECHSEL method for effective subword embedding initialization, enabling efficient model transfer from English to Ukrainian
High performance
Outperforms comparable models in Ukrainian NER and POS tagging tasks, including models trained from scratch for Ukrainian and cross-lingual models like XLM-RoBERTa
Stable performance
Multiple runs with random seeds show stable model performance with small standard deviations
Model Capabilities
Ukrainian text understanding
Named entity recognition
Part-of-speech tagging
Use Cases
Text analysis
Ukrainian named entity recognition
Identify entities such as person names, locations, and organizations in Ukrainian text
Achieves 91.24 F1 score on the lang-uk NER test set
Ukrainian part-of-speech tagging
Tag each word in Ukrainian text with its part of speech
Achieves 98.74% accuracy on the UD Ukrainian IU test set
Linguistic research
Ukrainian linguistic studies
Supports Ukrainian grammar analysis and linguistic feature research
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