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@@ -16,7 +16,7 @@ Data were collected from three main sources: [Reliefweb](https://reliefweb.int/)
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  Although XLM-Roberta was trained on 100 different languages, this fine-tuning was performed on three languages, English, French and Spanish, due to the impossibility of finding a good amount of such kind of humanitarian data in other languages.
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- ## Intended uses & limitations
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  To the best of our knowledge, HumBert is the first language model adapted on humanitarian topics, which often use a very specific language, making adaptation to downstream tasks (such as dister responses text classification) more effective.
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  This model is primarily aimed at being fine-tuned on tasks such as sequence classification or token classification.
 
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  Although XLM-Roberta was trained on 100 different languages, this fine-tuning was performed on three languages, English, French and Spanish, due to the impossibility of finding a good amount of such kind of humanitarian data in other languages.
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+ ## Intended uses
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  To the best of our knowledge, HumBert is the first language model adapted on humanitarian topics, which often use a very specific language, making adaptation to downstream tasks (such as dister responses text classification) more effective.
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  This model is primarily aimed at being fine-tuned on tasks such as sequence classification or token classification.