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@ -24,7 +24,7 @@ With this model, you can classify emotions in English text data. The model was t
6) sadness
7) surprise
The model is a fine-tuned checkpoint of DistilRoBERTa-base.
The model is a fine-tuned checkpoint of DistilRoBERTa-base. The emotions reflect Ekman's 6 universal emotions, plus a neutral class.
## Application
@ -44,7 +44,7 @@ Thanks to Samuel Domdey and chrsiebert for their support in making this model av
## Appendix
Please find an overview of the datasets used for training below. The table summarizes which emotions are available in each of the datasets.
Please find an overview of the datasets used for training below. All datasets contain English text. The table summarizes which emotions are available in each of the datasets.
|Name|anger|disgust|fear|joy|neutral|sadness|surprise|
|---|---|---|---|---|---|---|---|
@ -53,4 +53,4 @@ Please find an overview of the datasets used for training below. The table summa
|GoEmotions, Demszky et al. (2020)|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|ISEAR, Vikash (2018)|Yes|Yes|Yes|Yes|-|Yes|-|
|MELD, Poria et al. (2019)|Yes|Yes|Yes|Yes|Yes|Yes|Yes|
|SemEval-18|Yes|-|Yes|Yes|-|Yes|-|
|SemEval-2018, EI-reg (Mohammad et al. 2018) |Yes|-|Yes|Yes|-|Yes|-|