Crax Rat 🆕 Deluxe

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])

# Fine-tune. Make all layers trainable. for layer in model.layers: layer.trainable = True crax rat

x = base_model.output x = GlobalAveragePooling2D()(x) x = Dense(1024, activation='relu')(x) predictions = Dense(1, activation='sigmoid')(x) activation='relu')(x) predictions = Dense(1

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']) crax rat