Update README.md

README.md

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 ## Model Name
-ConfliBERT
+ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence
 
 ## Developers
 Yibo Hu, MohammadSaleh Hosseini, Erick Skorupa Parolin, Javier Osorio, Latifur Khan, Patrick Brandt, Vito D’Orazio
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 ## Model Description
 ConfliBERT is a transformer model pretrained on a vast corpus of texts related to political conflict and violence. This model is based on the BERT architecture and is specialized for analyzing texts within its domain, using masked language modeling (MLM) and next sentence prediction (NSP) as its main pretraining objectives. It is designed to improve performance in tasks like event extraction, and entity recognition for texts dealing with political subjects.
 
+Analyzing conflicts and political violence around the world is a persistent challenge in the political science and policy communities due in large part to the vast volumes of specialized text needed to monitor conflict and violence on a global scale. To help advance research in political science, we introduce ConfliBERT, a domain-specific pre-trained language model for conflict and political violence. We first gather a large domain-specific text corpus for language modeling from various sources. We then build ConfliBERT using two approaches: pre-training from scratch and continual pre-training. To evaluate ConfliBERT, we collect 12 datasets and implement 18 tasks to assess the models’ practical application in conflict research. Finally, we evaluate several versions of ConfliBERT in multiple experiments. Results consistently show that ConfliBERT outperforms BERT when analyzing political violence and conflict. 
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 ## Model Variants
 ConfliBERT has several variants, each fine-tuned on specific datasets to cater to different use cases within the domain of political conflict and violence:
 - **ConfliBERT-scr-uncased-BBC_News** (Binary Classification)