Update models.py

apps/models.py

@@ -3,4 +3,17 @@ import streamlit as st
 
 
 def app():
-    st.title("Models")
+    st.title("Model")
+
+    st.write("""
+
+## Behavioral Analysis of the Model 
+
+We employed 15000 samples of data from 21 distinct types of job categories to train the model, which was was constructed via a transfer learning approach using the open-source **DistilBERT** transformer developed by researchers at Hugging Face
+
+Model Limitation: One of the main limitations of the model is the dataset it was trained on. The original dataset had 62 categories, but due to insufficient data in many categories, some of them were combined, resulting in 21 categories. This approach of combining categories can make accurate CV segmentation more difficult. Additionally, the model was trained on an unbalanced dataset, which may lead to bias in certain situations. To overcome this limitation, larger and balanced datasets for each category would allow for more precise CV segmentation and lead to better output.
+
+### The model is scalable for other countries; however, country-specific data will be required to retrain the model.
+
+
+    """)