example of transfer learning with tf hub models

vgg.py

from tensorflow.keras.applications import VGG16
from tensorflow.keras import layers, models
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.losses import BinaryCrossentropy
from tensorflow.keras.metrics import BinaryAccuracy

# Load the pre-trained VGG16 model without the top layer
pretrained = VGG16(input_shape=(256, 256, 3), include_top=False, weights="imagenet")
pretrained.trainable = False

# Build the new model architecture
model = models.Sequential([
    pretrained,
    layers.Dropout(0.4),
    layers.Flatten(),
    layers.Dense(1024, activation='relu'),
    layers.Dropout(0.3),
    layers.Dense(1, activation='sigmoid')
])

# Compile the model
model.compile(optimizer=Adam(learning_rate=0.001),
              loss=BinaryCrossentropy(),
              metrics=[BinaryAccuracy()])

from tensorflow.keras.callbacks import EarlyStopping

# Set up early stopping
callback = EarlyStopping(monitor='val_loss', patience=3)

# Train the model
history = model.fit(train_flow, epochs=20, validation_data=valid_flow, verbose=1, callbacks=[callback])