Shap library for model explanation gives values outside range of 0 to 1

Question

I have a catboost model and I am trying to draw a decision plot for some of the sample records to see which features are driving the prediction towards 0 or 1. However, I noticed that the range of the model output value is not 0-1 but rather it ranges from negative 2 to positive 2

Here is a screenshot of 1 such example where the prediction probability is 0.82 but the model output value shows 1.5 ( I have redacted my feature names because of privacy reasons)

Why does the range not match with the probability range of 0-1?

Here is my code snippet -

explainer = shap.TreeExplainer(model)
shap_values = explainer.shap_values(transformer_pipeline)
# generate decision plot for 1st record as an example
shap.decision_plot(explainer.expected_value, shap_values[0,:], transformer_pipeline.iloc[0,:])