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xlm-roberta-base-multilingual-text-genre-classifier

Text Classification

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Taja Kuzman commited on May 29

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@@ -150,7 +150,7 @@ We set up a benchmark for evaluating robustness of automatic genre identificatio
 for the automatic enrichment of large text collections with genre information. The benchmark comprises 11 European languages and two test datasets.
 You are welcome to submit your entry at the [benchmark's GitHub repository](https://github.com/TajaKuzman/AGILE-Automatic-Genre-Identification-Benchmark/tree/main).
-The model outperforms all other technologies, including GPT models (used in a zero-shot scenario).
 Results on the English test dataset (EN-GINCO):

 for the automatic enrichment of large text collections with genre information. The benchmark comprises 11 European languages and two test datasets.
 You are welcome to submit your entry at the [benchmark's GitHub repository](https://github.com/TajaKuzman/AGILE-Automatic-Genre-Identification-Benchmark/tree/main).
+The model outperforms all other technologies, including GPT models that are used in a zero-shot scenario.
 Results on the English test dataset (EN-GINCO):