How to manually specify class labels in keras flow_from_directory?

Question

Problem: I am training a model for multilabel image recognition. My images are therefore associated with multiple y labels. This is conflicting with the conveni

Answer 1

# Training the model
history = model.fit(train_generator, steps_per_epoch=steps_per_epoch, epochs=3, validation_data=val_generator,validation_steps=validation_steps, verbose=1,
                    callbacks= keras.callbacks.ModelCheckpoint(filepath='/content/results',monitor='val_accuracy', save_best_only=True,save_weights_only=False))

The validation_steps or the steps_per_epoch might be exceeding than that of the original parameters.

steps_per_epoch= (int(num_of_training_examples/batch_size) might help. Similarly validation_steps= (int(num_of_val_examples/batch_size) will help