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arabert_c19

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@@ -10,13 +10,12 @@ The model can achieve better results for the tasks that deal with multi-dialect
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  # Classification results for multiple tasks including fake-news and hate speech detection when using arabert_c19 and mbert_ar_c19:
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  For more details refer to the paper (link)
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  | | arabert | mbert | distilbert multi | arabert Covid-19 | mbert Covid-19 |
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  |------------------------------------|----------|----------|------------------|------------------|----------------|
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- | Contains hate (Binary) | 0.8346 | 0.6675 | 0.7145 | 0.8649 | 0.8492 |
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- | Talk about a cure (Binary) | 0.8193 | 0.7406 | 0.7127 | 0.9055 | 0.9176 |
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- | News or opinion (Binary) | 0.8987 | 0.8332 | 0.8099 | 0.9163 | 0.9116 |
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- | Contains fake information (Binary) | 0.6415 | 0.5428 | 0.4743 | 0.7739 | 0.7228 |
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  # Preprocessing
 
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  # Classification results for multiple tasks including fake-news and hate speech detection when using arabert_c19 and mbert_ar_c19:
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  For more details refer to the paper (link)
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  | | arabert | mbert | distilbert multi | arabert Covid-19 | mbert Covid-19 |
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  |------------------------------------|----------|----------|------------------|------------------|----------------|
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+ | Contains hate (Binary) | 0.8346 | 0.6675 | 0.7145 | `0.8649` | 0.8492 |
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+ | Talk about a cure (Binary) | 0.8193 | 0.7406 | 0.7127 | 0.9055 | `0.9176` |
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+ | News or opinion (Binary) | 0.8987 | 0.8332 | 0.8099 | `0.9163` | 0.9116 |
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+ | Contains fake information (Binary) | 0.6415 | 0.5428 | 0.4743 | `0.7739` | 0.7228 |
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  # Preprocessing