Update README.md

README.md

@@ -7,12 +7,11 @@ f1-score: 0.83
 ---
 # Model Card for A&ttack2
 
-Text classification model that determines whether a not a short text contains an attack.
-
+A text classification model for determining if a social media post in Danish or Norwegian contains a verbal attack.
 
 # Model Description
 
-The model is based on the [North-T5-NCC Large](https://huggingface.co/north/t5_large_NCC) (developed by Per E. Kummervold) which is a Scandinavian language built upon [T5](https://github.com/google-research/text-to-text-transfer-transformer) and [T5X](https://github.com/google-research/t5x). The model is further trained on ~70k Norwegian and ~67k Danish social media posts which have been classified as either 'attack' or 'not attack', making it a text-to-text model manipulated to do classification. The model is described in Danish in [this report](https://strapi.ogtal.dk/uploads/966f1ebcfa9942d3aef338e9920611f4.pdf).
+The model is based on the [North-T5-NCC Large](https://huggingface.co/north/t5_large_NCC) (developed by Per E. Kummervold) which is a Scandinavian language built upon [T5](https://github.com/google-research/text-to-text-transfer-transformer) and [T5X](https://github.com/google-research/t5x). The model is further trained on ~70k Norwegian and ~67k Danish social media posts which have been classified as either 'verbal attack' or 'nothing', making it a text-to-text model restricted to do classification. The model is described in Danish in [this report](https://strapi.ogtal.dk/uploads/966f1ebcfa9942d3aef338e9920611f4.pdf).
 
 
 - **Developed by:** The development team at Analyse & Tal
@@ -32,7 +31,7 @@ This model can be used for classifying Danish and Norwegian social media posts o
 [More Information Needed]
 
 # Training Data
-A collection of ~70k Norwegian and ~67k Danish social media posts have been manually annotated as 'attack' or 'not attack' by six individual coders. 5% of the posts have been annotated by more then one annotator, with the annotators in agreement for 83% of annotations.
+A collection of ~70k Norwegian and ~67k Danish social media posts have been manually annotated as 'verbal attack' or 'nothing' by annotators. 5% of the posts have been annotated by more then one annotator, with the annotators in agreement for 83% of annotations.
 
 [More information needed on the data split method and the training-validation-test split.]