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Gigabert V4 Arabic And English

Developed by lanwuwei
GigaBERT-v4 is a model further pretrained on code-mixed data based on GigaBERT-v3, demonstrating improved zero-shot transfer performance from English to Arabic in information extraction (IE) tasks.
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Release Time : 3/2/2022

Model Overview

GigaBERT-v4 is a pretrained language model focused on English and Arabic information extraction tasks, enhanced with code-mixed data to improve its zero-shot transfer capabilities.

Model Features

Zero-shot transfer learning
Demonstrates excellent zero-shot transfer performance in information extraction tasks from English to Arabic.
Code-mixed data pretraining
Further pretrained on code-mixed data based on GigaBERT-v3, enhancing the model's multilingual processing capabilities.

Model Capabilities

English information extraction
Arabic information extraction
Cross-lingual zero-shot transfer

Use Cases

Information extraction
Cross-lingual named entity recognition
Directly applied to Arabic text for named entity recognition tasks after training on English
Improved zero-shot transfer performance
Relation extraction
Extracting relationships between entities in English and Arabic texts
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