final

app.py

@@ -127,13 +127,13 @@ st.title("🚫 Offensive Speech Detection")
 st.markdown("""
 This application helps identify potentially offensive oontent in text provided by an user. 
 
-It uses a machine learning model to analyze text and determine if it contains offensive speech. 
+It uses a trained neural network to analyze text and determine if it contains offensive speech. 
 
 
 **How it works:**
 1. Enter your text in the input box below
-2. The model will analyze the content and provide a prediction
-3. Results show both the classification and confidence level
+2. The model will analyze the content and provide a prediction based on the model
+3. Results show both the classification and value predicted by the model
 """)
 
 
@@ -160,6 +160,9 @@ with st.expander("❓ Frequently Asked Questions"):
     **Q: What is considered offensive speech?**
     - A: The model is using a dataset of tweets, which were tagged as offensive or not. More information on the dataset can be found here : https://huggingface.co/datasets/christophsonntag/OLID
 
+    **Q: What type of model it is?**
+    - A: It is a neural network with an initial preprocessing, a vectorization, an embedding layers and GRU layers 
+                
     **Q: How is the prediction done?**
     - A: The model predicts a value between 1 and 0. The closer it is to 1, the more offensive is the prediction.  When the prediction is higher than 0.5, the text is considered as offensive