Update app.py

app.py

@@ -102,23 +102,24 @@ num_classes = 12
 model = Sequential([
     data_augmentation,
     layers.Rescaling(1./255),
-    layers.Conv2D(16, 3, padding='same', activation='relu'),
-    layers.MaxPooling2D(),
     layers.Conv2D(32, 3, padding='same', activation='relu'),
     layers.MaxPooling2D(),
     layers.Conv2D(64, 3, padding='same', activation='relu'),
     layers.MaxPooling2D(),
+    layers.Conv2D(128, 3, padding='same', activation='relu'),
+    layers.MaxPooling2D(),
     layers.Dropout(0.2),
     layers.Flatten(),
-    layers.Dense(128, activation='relu'),
+    layers.Dense(256, activation='relu'),
     layers.Dense(num_classes, name="outputs")
 ])
 
+
 model.compile(optimizer='adam',
               loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
               metrics=['accuracy'])
 
-epochs = 10
+epochs = 20
 history = model.fit(
     train_ds,
     validation_data=val_ds,