model1.py

model = Sequential([
    Input(shape=(96,96,3)),
    ZeroPadding2D((5,5)),
    Conv2D(32, 3, activation='relu'),
    BatchNormalization(),
    MaxPool2D(pool_size=(2,2)),
    Dropout(0.3),
    Conv2D(32, 3, activation='relu'),
    MaxPool2D(pool_size=(2,2)),
    Dropout(0.3),
    Conv2D(32, 3, activation='relu'),
    MaxPool2D(pool_size=(2,2)),
    Dropout(0.4),
    Conv2D(32, 3, activation='relu'),
    MaxPool2D(pool_size=(2,2)),
    Dropout(0.3),
    Conv2D(32, 3, activation='relu'),
    MaxPool2D(pool_size=(2,2)),
    Dropout(0.3),
    Flatten(),
    Dense(64, activation='relu'),
    Dropout(0.5),
    Dense(5, activation='softmax')
])

model.summary()