Update app.py

app.py

@@ -21,36 +21,40 @@ def simulate_training(epochs, learning_rate):
     accuracies = []
     logs = []
 
-    # start lower for visible climb
+    # Start lower for visible climb
     current_acc = 0.55 + random.uniform(0, 0.05)
 
     for epoch in range(epochs):
         time.sleep(0.3)
 
-        # scale improvement more aggressively
-        improvement = learning_rate * random.uniform(200, 400)
+        # Improvement scaled for realistic visible growth
+        improvement = learning_rate * random.uniform(20, 80)
         current_acc += improvement
 
-        # plateau effect
+        # Add small random noise and plateau effect
         if epoch > epochs * 0.6:
-            current_acc += random.uniform(-0.01, 0.003)
+            current_acc += random.uniform(-0.015, 0.005)
 
-        current_acc = max(min(current_acc, 0.98), 0.55)
+        # Clamp values between 0.55 and 0.95
+        current_acc = max(min(current_acc, 0.95), 0.55)
         accuracies.append(round(current_acc, 3))
         logs.append(f"Epoch {epoch+1}: Validation Accuracy = {current_acc:.3f}")
 
-    # plot exaggerated climb
+    # Create the chart
     plt.figure(figsize=(4, 2))
     plt.plot(range(1, epochs + 1), accuracies, marker="o", color="tab:blue")
+    plt.axhline(y=accuracies[0], color="gray", linestyle="--", linewidth=1, label="Starting accuracy")
     plt.title("Simulated Validation Accuracy per Epoch")
     plt.xlabel("Epoch")
     plt.ylabel("Accuracy")
     plt.ylim(0.5, 1.0)
     plt.grid(True)
+    plt.legend()
 
     final_acc = round(accuracies[-1], 3)
     return plt, "\n".join(logs), final_acc
 
+
 # -------- Real Inference Function --------
 def analyze_text(text):
     if not sentiment_analyzer: