keras-dreambooth/dreambooth-galaxy-mergers

Model description

This is a Keras Dreambooth model fine-tuned to images of galaxy mergers taken with the Hubble Space Telescope. In particular, I selected mergers at intermediate stages (3-4 here), where the two bodies of the merging galaxies are still recognizeable and/or a bridge of material connecting the two galaxies is clearly visible. Credit for the training images goes to ESA/Hubble: images can be found on their website selecting the category of interacting galaxies.

Sample Outputs

A few ouput samples of the Dreambooth model below.

prompt: image of sks galaxies merging in space

prompt: painting of sks galaxies merging in van gogh style, 8k, high quality, trending on artstation

Cosmic Hugs: an artistic rendition of galaxy collisions

Intended uses & limitations

This model has similar intended uses & limitations as any Stable Diffusion and Dreambooth models (see e.g. this model). In particular, this model should be used with a prompt containing sks galaxies merging.

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Hyperparameters	Value
inner_optimizer.class_name	Custom>RMSprop
inner_optimizer.config.name	RMSprop
inner_optimizer.config.weight_decay	None
inner_optimizer.config.clipnorm	None
inner_optimizer.config.global_clipnorm	None
inner_optimizer.config.clipvalue	None
inner_optimizer.config.use_ema	False
inner_optimizer.config.ema_momentum	0.99
inner_optimizer.config.ema_overwrite_frequency	100
inner_optimizer.config.jit_compile	True
inner_optimizer.config.is_legacy_optimizer	False
inner_optimizer.config.learning_rate	0.0010000000474974513
inner_optimizer.config.rho	0.9
inner_optimizer.config.momentum	0.0
inner_optimizer.config.epsilon	1e-07
inner_optimizer.config.centered	False
dynamic	True
initial_scale	32768.0
dynamic_growth_steps	2000
training_precision	mixed_float16