Update README.md

README.md

@@ -45,10 +45,9 @@ It achieves the following results on the evaluation set:
 ## Model description
 
 This model implements a novel approach to classifying climate change skepticism arguments 
-    by utilizing Large Language Models (LLMs) for synthetic data. The base architecture uses ModernBERT with 
-    only synthetic data used for training. The model achieves exceptional performance with an accuracy of 99.45% on the validation dataset which is therefore the [QuotaClimat](QuotaClimat/frugalaichallenge-text-train) dataset.
+    by using only synthetic data. The base architecture uses ModernBERT with an accuracy of 99.45% on the validation dataset which is the entire [QuotaClimat](QuotaClimat/frugalaichallenge-text-train) dataset.
 
-    The model categorizes text into the following skepticism types:
+    The model categorizes text into the following climate change denial types:
 
 - `label`: Following categories:
   - `0_not_relevant`: No relevant claim detected or claims that don't fit other categories