Update README.md

README.md

@@ -20,12 +20,9 @@ language:
 - ru
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # ukraine-war-pov
 
-This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on a dataset of 30K social media posts (a balanced set of 15K for each label) from Ukraine manually annotated for pro-Ukrainian or pro-Russian point of view on the war.
+This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on a dataset of 30K social media posts (a balanced set of 15K for each label) from Ukraine manually annotated for pro-Ukrainian or pro-Russian point of view on the war after the 2022 invasion.
 It achieves the following results on a balanced test set (2K):
 - Loss: 0.2166
 - Accuracy: 0.9315
@@ -34,17 +31,9 @@ It achieves the following results on a balanced test set (2K):
 - Recall: 0.9315
 - AUC: 0.9774 (self-report)
 
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
 ## Training and evaluation data
 
-More information needed
+The training and evaluation data was compiled and labeled by the Center for Content Analysis in Ukraine: Artem Zakharchenko and his team, including Yevhen Luzan, Olena Zakharchenko, Olexiy Rogalyov, Olena Zinenko, Yuliia Maksymtsova, Maryna Fursenko, Valeriia Molotsiian, and Anhelika Machula. 
 
 ## Training procedure