Datasets:

s-nlp
/

paradetox

@@ -39,7 +39,7 @@ In addition to all ParaDetox dataset, we also make public [samples](https://hugg
 # Detoxification evaluation
 The automatic evaluation of the model were produced based on three parameters:
-* *style transfer accuracy* (**STA**): percentage of nontoxic outputs identified by a style classifier. We pretrained toxicity classifier on Jigsaw data and put it online in HuggingFace🤗 [repo](https://huggingface.co/s-nlp/roberta_toxicity_classifier).
 * *content preservation* (**SIM**): cosine similarity between the embeddings of the original text and the output computed with the model of [Wieting et al. (2019)](https://aclanthology.org/P19-1427/).
 * *fluency* (**FL**): percentage of fluent sentences identified by a RoBERTa-based classifier of linguistic acceptability trained on the [CoLA dataset](https://nyu-mll.github.io/CoLA/).

 # Detoxification evaluation
 The automatic evaluation of the model were produced based on three parameters:
+* *style transfer accuracy* (**STA**): percentage of nontoxic outputs identified by a style classifier. We pretrained [toxicity classifier](https://huggingface.co/s-nlp/roberta_toxicity_classifier) on Jigsaw data and put it online in HuggingFace🤗 [repo](https://huggingface.co/s-nlp/roberta_toxicity_classifier).
 * *content preservation* (**SIM**): cosine similarity between the embeddings of the original text and the output computed with the model of [Wieting et al. (2019)](https://aclanthology.org/P19-1427/).
 * *fluency* (**FL**): percentage of fluent sentences identified by a RoBERTa-based classifier of linguistic acceptability trained on the [CoLA dataset](https://nyu-mll.github.io/CoLA/).