In Fig. 2 The pie chart shows positive, negative, neutral sentiment score sentence of the Overall News Article along with a wordcloud figure of important terms appeared in the application. Sentences are highlighted as per color scheme to denote model predictions (good for Probe Model Prediction).
Model Building:
Simple Transformer is used to finetune pretrained RoBERTa model on Hindi language. Data distribution among annotated labels is positive— 3040,
negative — 3104, neutral — 2591 sentences. After training for 3 epochs model gave best result (triggered due to early stopping).