Train your model
Train
is a part of DeepH-pack, which is used to train a deep
learning model using the processed dataset.
Prepare a configuration in the format of ini, setting up the
file referring to the default DeepH-pack/deeph/default.ini
.
The meaning of the keywords can be found in the INPUT KEYWORDS section.
For a quick start, you must set up graph_dir, save_dir,
raw_dir and orbital, other keywords can stay default and
be adjusted later.
With the configuration file prepared, run
deeph-train --config ${config_path}
with ${config_path}
replaced by the path of your configuration file.
Tips:
Name your dataset. Use dataset_name to name your dataset, the same names may overwrite each other.
Hyperparameters of the neural network. The neural network here contains some hyperparameters. For a specific problem your should try adjusting the hyperparameters to obtain better results.
The keyword orbital. The keyword orbital states which orbitals or matrix elements are predicted. It is a little complicated to understand its data structure. To figure out it, you can refer to the INPUT KEYWORDS section or the method make_mask in class
DeepHKernel
defined inDeepH-pack/deeph/kernel.py
.Alternatively, a Python script at
DeepH-pack/tools/get_all_orbital_str.py
can be used to generate a default configuration to predict all orbitals with one model.Use TensorBoard for visualizations. You can track and visualize the training process through TensorBoard by running
tensorboard --logdir=./tensorboard
in the output directory (save_dir):