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@@ -54,7 +54,9 @@ This model is case-sensitive: it makes a difference between English and English.
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  The model has 6 layers, 768 dimension and 12 heads, totalizing 82M parameters (compared to 125M parameters for RoBERTa-base).
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  On average DistilRoBERTa is twice as fast as Roberta-base.
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- ## Training and evaluation data
 
 
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  ## Training procedure
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  The model has 6 layers, 768 dimension and 12 heads, totalizing 82M parameters (compared to 125M parameters for RoBERTa-base).
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  On average DistilRoBERTa is twice as fast as Roberta-base.
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+ ## Training Data
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+ Polar sentiment dataset of sentences from financial news. The dataset consists of 4840 sentences from English language financial news categorised by sentiment. The dataset is divided by agreement rate of 5-8 annotators.
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  ## Training procedure
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