Save batches of images for each epochs in Tensorflow via ImageDataGenerator

Question

I create batches of images using ImageDataGenerator function in Tensorflow.
I know that each batch of images for each epochs is slightly different according to the different transformations that ImageDataGenerator randomly applies to my dataset.

datagen_full_data_aug = ImageDataGenerator(**data_full_aug)

train_generator_images=datagen_full_data_aug.flow_from_dataframe(
    dataframe=train,
    directory=folder_images,
    x_col='filename',
    class_mode=None,
    shuffle=True,
    seed = seed,
    batch_size=batch_size,
    target_size=(image_size,image_size))

This is how I train/fit my model.

history=model.fit(train_generator,
                  steps_per_epoch=steps_per_epoch,
                  epochs=EPOCHS,
                  verbose=2,
                  validation_data=validation_generator,
                  validation_steps=val_steps_per_epoch,
                  callbacks=[checkpoint],
                  batch_size = batch_size)

I sometimes have a few variations of my accuracy during training during specific epochs.
IoU-Accuracy fluctuation

I would like to save individual batches of images for each epochs in different folders (like epoch_1, epoch_2...etc.) so that I can analyse which images might have made the accuracy fluctuate so much.
And I would be able to conlude which transformations might have influenced the model for a specific epochs.

If each image could reuse the name it was given in my dataset for sorting puproses it would be great.

How should I proceed ?

I tried the save function :

    save_to_dir=None,
    save_prefix='',
    save_format='png',

But this saves all the images of all epochs into one folder. And we can't distinguish the images from the 1st epochs from the 2nd...etc.