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README.md
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@@ -38,13 +38,12 @@ It achieves the following results on the evaluation set:
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Multilingual Named Entity Recognition across several languages
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For this project's token classification, I built a unique custom model head
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WikiANN or PAN-X.2, a subset of the Cross-lingual TRansfer Evaluation of Multilingual
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Encoders (XTREME) benchmark, was applied. This project was completed for a customer based
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in switzerland, where the four languages that are most frequently spoken are
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German (62.9% of articles), French (22.9%), Italian (8.4%), and English (5.9%).
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PER (person), and ORG (organization).
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## Intended uses & limitations
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Multilingual Named Entity Recognition across several languages
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For this project's token classification, I built a unique custom model head and the
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+
WikiANN or PAN-X.2, which is a subset of the Cross-lingual TRansfer Evaluation of Multilingual
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Encoders (XTREME) benchmark, was applied. This project was completed for a customer based
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44 |
in switzerland, where the four languages that are most frequently spoken are
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German (62.9% of articles), French (22.9%), Italian (8.4%), and English (5.9%).
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## Intended uses & limitations
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