import streamlit as st

st.title("🧠 Model Training & Evaluation")

st.markdown("""

### 🛠️ **Text Vectorization**

Used **TF-IDF Vectorizer** with:

🔢 **max_features** = 10000 to limit dimensionality

---

### 🤖 **Model Selection**

Chose **Logistic Regression** as baseline model

Applied **GridSearchCV** to optimize parameters

Training pipeline saved using **pickle** for direct deployment



---

### 📊 **Model Evaluation**

📈 **Accuracy Achieved: 0.75**


**Key Metrics:**

**Accuracy**    0.75

**Precision**   0.81

**Recall**      0.77

**F1-Score**    0.75


This trained pipeline is now integrated into the final deployment page below.


---

""")

if st.button("Next"):
    st.switch_page("pages/3_Deployment.py")

if st.button("Go to Data Overview"):
    st.switch_page("pages/1_Data_Overview.py")