I am beginner with Deep learning CNN models, I am trying to classify the image boats categories below, which is a folder that contain these file names:

dataset_path = 'boat_type_classification_dataset'

# Load the dataset and split it into training (80%) and validation (20%)
train_dataset = tf.keras.preprocessing.image_dataset_from_directory(
    dataset_path,
    validation_split=0.2,  
    subset="training",
    seed=43,
    image_size=(128, 128), 
    batch_size=32,
    shuffle=True
)

val_dataset = tf.keras.preprocessing.image_dataset_from_directory(
    dataset_path,
    validation_split=0.2,
    subset="validation",
    seed=43,
    image_size=(128, 128),
    batch_size=32,
    shuffle=True
)


Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 126, 126, 32)      896       
                                                                 
 max_pooling2d (MaxPooling2  (None, 63, 63, 32)        0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 61, 61, 32)        9248      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 30, 30, 32)        0         
 g2D)                                                            
                                                                 
 global_average_pooling2d (  (None, 32)                0         
 GlobalAveragePooling2D)                                         
                                                                 
 dense (Dense)               (None, 128)               4224      
                                                                 
 dense_1 (Dense)             (None, 128)               16512     
                                                                 
 dense_2 (Dense)             (None, 9)                 1161      
                                                                 
=================================================================
Total params: 32041 (125.16 KB)
Trainable params: 32041 (125.16 KB)
Non-trainable params: 0 (0.00 Byte)

I am getting this error while fitting the model
ValueError: Shapes (None, 9) and (None, 1) are incompatible

Note: I checked the labels of the categories which are integers

model.compile(
    optimizer=tf.keras.optimizers.Adam(),  # Adam optimizer
    loss = 'sparse_categorical_crossentropy',  # For integer labels
    metrics=[
        tf.keras.metrics.SparseCategoricalAccuracy(name='accuracy'),  # Use Sparse for integer labels
        tf.keras.metrics.Precision(name='precision'),
        tf.keras.metrics.Recall(name='recall')
    ]
)

try:
    history = model.fit(
        train_dataset,
        validation_data=val_dataset,
        epochs=20
    )
except Exception as e:
    print("Error occurred:", e)