Update app.py

app.py

@@ -11,12 +11,23 @@ from bert_strim import bert_model_page
 
 
 def app_description_page():
-    st.markdown("<h1 style='text-align: center;'>Welcome to My App!</h1>", unsafe_allow_html=True)
+    st.title("Welcome to My App!")
     st.markdown("<h3 style='font-size: 18px;'>This is a Streamlit application where you can explore four different models.</h3>", unsafe_allow_html=True)
     st.markdown("<h3 style='font-size: 18px;'>About the project:</h3>", unsafe_allow_html=True)
     st.markdown("<h3 style='font-size: 18px;'>The task is to train 3 different models on a dataset that contains reviews about the clinic.</h3>", unsafe_allow_html=True)
     st.markdown("<h3 style='font-size: 18px;'>You can write text and the model will classify it as “Negative” or “Positive”</h3>", unsafe_allow_html=True)
-
+    data = {
+    "Model": ["CatBoostClassifier", "LSTM", "Rubert-tiny2", "Rubert-tiny-toxicity"],
+    "F1 metric": [0.87, 0.94, 0.90, 0.84]
+    }
+    df = pd.DataFrame(data)
+    st.markdown("<h3 style='font-size: 18px;'>Models:</h3>", unsafe_allow_html=True)
+    st.markdown("<h3 style='font-size: 18px;'>1. CatBoostClassifier trained on TF-IDF </h3>", unsafe_allow_html=True)
+    st.markdown("<h3 style='font-size: 18px;'>2. LSTM with BahdanauAttention </h3>", unsafe_allow_html=True)
+    st.markdown("<h3 style='font-size: 18px;'>3. Rubert-tiny2 </h3>", unsafe_allow_html=True)
+    st.markdown("<h3 style='font-size: 18px;'>4. Rubert-tiny-toxicity </h3>", unsafe_allow_html=True)
+    st.dataframe(df)
+    st.image('20182704132259.jpg', use_column_width=True)
 
 def model_selection_page():
     st.sidebar.title("Model Selection")