Create README.md

README.md

@@ -0,0 +1,26 @@
+---
+language:
+- 'no'
+---
+## Model Description
+This model builds upon the pre-trained NB-BERT model developed by Nasjonalbibloteket, which is designed to handle the nuances of the Norwegian language. The fine-tuning process tailored the model to understand and classify the sentiment of Norwegian governmental communications, particularly during the COVID-19 pandemic
+
+
+## Use cases
+Sentiment Analysis of Governmental Communication:
+Objective: Analyze and classify the sentiment of official governmental communications from Norwegian authorities.
+Example: Categorizing tweets from the Norwegian health department and government announcements to understand public sentiment trends.
+
+## Limitations
+The model is fine-tuned specifically for Norwegian
+
+The model is only trained for government specific sentiment analysis 
+
+## Training data
+Source: The datasets used include:
+Twitter data from the Norwegian Health Department (Folkehelseinstituttet) and the government (Rejeringen).
+A timeline dataset of the Norwegian government's handling of the COVID-19 pandemic.
+The labeling process utilized a combination of Chatgpt4 and manuel corrections, the fine-tuning is included
+
+## Credit 
+This work builds upon the NB-BERT model. For more information on the original NB-BERT model, please refer to the Nasjonalbibloteket community’s publication: https://github.com/NBAiLab/notram