From 984f094134654cdaa58030170029867a282ac87e Mon Sep 17 00:00:00 2001
From: PatReis <pat.reiser@web.de>
Date: Wed, 3 Jan 2024 16:21:34 +0100
Subject: [PATCH] Update training results.

---
 ...iNN_MatProjectDielectricDataset_score.yaml | 156 ++++++++++++++++++
 .../PAiNN_make_crystal_model/PAiNN_hyper.json |   1 +
 ...PN_MatProjectPerovskitesDataset_score.yaml | 156 ++++++++++++++++++
 .../NMPN_make_crystal_model/NMPN_hyper.json   |   1 +
 .../CGCNN_MatProjectPhononsDataset_score.yaml | 156 ++++++++++++++++++
 .../CGCNN_make_crystal_model/CGCNN_hyper.json |   1 +
 ...eNetPP_MatProjectPhononsDataset_score.yaml | 138 ++++++++++++++++
 .../DimeNetPP_hyper.json                      |   1 +
 ...Megnet_MatProjectPhononsDataset_score.yaml | 156 ++++++++++++++++++
 .../Megnet_hyper.json                         |   1 +
 .../NMPN_MatProjectPhononsDataset_score.yaml  | 156 ++++++++++++++++++
 .../NMPN_make_crystal_model/NMPN_hyper.json   |   1 +
 .../PAiNN_MatProjectPhononsDataset_score.yaml | 156 ++++++++++++++++++
 .../PAiNN_make_crystal_model/PAiNN_hyper.json |   1 +
 14 files changed, 1081 insertions(+)
 create mode 100644 training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_MatProjectDielectricDataset_score.yaml
 create mode 100644 training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_hyper.json
 create mode 100644 training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_MatProjectPerovskitesDataset_score.yaml
 create mode 100644 training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_hyper.json
 create mode 100644 training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_MatProjectPhononsDataset_score.yaml
 create mode 100644 training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_hyper.json
 create mode 100644 training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_MatProjectPhononsDataset_score.yaml
 create mode 100644 training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_hyper.json
 create mode 100644 training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_MatProjectPhononsDataset_score.yaml
 create mode 100644 training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_hyper.json
 create mode 100644 training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_MatProjectPhononsDataset_score.yaml
 create mode 100644 training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_hyper.json
 create mode 100644 training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_MatProjectPhononsDataset_score.yaml
 create mode 100644 training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_hyper.json

diff --git a/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_MatProjectDielectricDataset_score.yaml b/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_MatProjectDielectricDataset_score.yaml
new file mode 100644
index 00000000..f6a7db88
--- /dev/null
+++ b/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_MatProjectDielectricDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: ''
+date_time: '2024-01-02 16:13:43'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 800
+- 800
+- 800
+- 800
+- 800
+execute_folds: null
+kgcnn_version: 4.0.0
+learning_rate:
+- 2.1409230612334795e-05
+- 2.1409230612334795e-05
+- 2.1409230612334795e-05
+- 2.1409230612334795e-05
+- 2.1409230612334795e-05
+loss:
+- 0.008343053050339222
+- 0.007415709085762501
+- 0.010438678786158562
+- 0.006397827062755823
+- 0.006797634530812502
+max_learning_rate:
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+max_loss:
+- 0.3743226230144501
+- 0.3785216212272644
+- 0.3962166905403137
+- 0.4328046143054962
+- 0.35603174567222595
+max_scaled_mean_absolute_error:
+- 0.832730770111084
+- 0.8200618028640747
+- 0.7539911866188049
+- 0.8445661067962646
+- 0.7975484728813171
+max_scaled_root_mean_squared_error:
+- 2.241159439086914
+- 2.168581485748291
+- 1.9145407676696777
+- 1.9570283889770508
+- 2.2431771755218506
+max_val_loss:
+- 0.1483222395181656
+- 0.1832215040922165
+- 0.20100706815719604
+- 0.23863278329372406
+- 0.17070074379444122
+max_val_scaled_mean_absolute_error:
+- 0.3327166736125946
+- 0.3960125148296356
+- 0.38261353969573975
+- 0.4667319357395172
+- 0.3815496861934662
+max_val_scaled_root_mean_squared_error:
+- 1.2442364692687988
+- 1.7240126132965088
+- 2.6579506397247314
+- 2.520660400390625
+- 1.3745040893554688
+min_learning_rate:
+- 9.99999993922529e-09
+- 9.99999993922529e-09
+- 9.99999993922529e-09
+- 9.99999993922529e-09
+- 9.99999993922529e-09
+min_loss:
+- 0.006864224560558796
+- 0.0067525943741202354
+- 0.007798410952091217
+- 0.006203407421708107
+- 0.006412183865904808
+min_scaled_mean_absolute_error:
+- 0.015403984114527702
+- 0.014682323671877384
+- 0.014871788211166859
+- 0.012126419693231583
+- 0.014398567378520966
+min_scaled_root_mean_squared_error:
+- 0.07728196680545807
+- 0.05676349997520447
+- 0.06881851702928543
+- 0.07449829578399658
+- 0.07499721646308899
+min_val_loss:
+- 0.10685255378484726
+- 0.1370280534029007
+- 0.16552644968032837
+- 0.19828854501247406
+- 0.13007348775863647
+min_val_scaled_mean_absolute_error:
+- 0.239999920129776
+- 0.29708120226860046
+- 0.31591737270355225
+- 0.3882957696914673
+- 0.2904556095600128
+min_val_scaled_root_mean_squared_error:
+- 1.1581988334655762
+- 1.5400705337524414
+- 2.608130931854248
+- 2.4554412364959717
+- 1.1494797468185425
+model_class: make_crystal_model
+model_name: PAiNN
+model_version: '2023-10-04'
+multi_target_indices: null
+number_histories: 5
+scaled_mean_absolute_error:
+- 0.01876545511186123
+- 0.01617487147450447
+- 0.0198748130351305
+- 0.012547771446406841
+- 0.015281754545867443
+scaled_root_mean_squared_error:
+- 0.08240760117769241
+- 0.06557603180408478
+- 0.07439026981592178
+- 0.08728229254484177
+- 0.0879431739449501
+seed: 42
+time_list:
+- '0:20:49.277263'
+- '0:20:51.259861'
+- '0:21:07.760770'
+- '0:20:45.797749'
+- '0:20:35.374779'
+val_loss:
+- 0.12743614614009857
+- 0.1601962298154831
+- 0.19087393581867218
+- 0.21565459668636322
+- 0.15698392689228058
+val_scaled_mean_absolute_error:
+- 0.2856501042842865
+- 0.34770697355270386
+- 0.3635082244873047
+- 0.42160239815711975
+- 0.35084113478660583
+val_scaled_root_mean_squared_error:
+- 1.2183345556259155
+- 1.704131841659546
+- 2.6451714038848877
+- 2.4885034561157227
+- 1.2744284868240356
diff --git a/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_hyper.json b/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_hyper.json
new file mode 100644
index 00000000..109527cc
--- /dev/null
+++ b/training/results/MatProjectDielectricDataset/PAiNN_make_crystal_model/PAiNN_hyper.json
@@ -0,0 +1 @@
+{"model": {"module_name": "kgcnn.literature.PAiNN", "class_name": "make_crystal_model", "config": {"name": "PAiNN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 128}, "equiv_initialize_kwargs": {"dim": 3, "method": "eye"}, "bessel_basis": {"num_radial": 20, "cutoff": 5.0, "envelope_exponent": 5}, "pooling_args": {"pooling_method": "mean"}, "conv_args": {"units": 128, "cutoff": null, "conv_pool": "sum"}, "update_args": {"units": 128}, "depth": 2, "verbose": 10, "equiv_normalization": false, "node_normalization": false, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true], "units": [128, 1], "activation": ["swish", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 32, "epochs": 800, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearWarmupLinearLearningRateScheduler", "config": {"learning_rate_start": 0.0001, "learning_rate_stop": 1e-06, "epo_warmup": 25, "epo": 1000, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {"data_unit": ""}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectDielectricDataset", "module_name": "kgcnn.data.datasets.MatProjectDielectricDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_MatProjectPerovskitesDataset_score.yaml b/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_MatProjectPerovskitesDataset_score.yaml
new file mode 100644
index 00000000..a5413241
--- /dev/null
+++ b/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_MatProjectPerovskitesDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: eV/unit_cell
+date_time: '2024-01-03 15:52:10'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 700
+- 700
+- 700
+- 700
+- 700
+execute_folds: null
+kgcnn_version: 4.0.0
+learning_rate:
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+loss:
+- 0.006932865362614393
+- 0.005952408537268639
+- 0.0054324958473443985
+- 0.005202374421060085
+- 0.005437558051198721
+max_learning_rate:
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+- 9.999999747378752e-05
+max_loss:
+- 0.4531893730163574
+- 0.4429142475128174
+- 0.4406983554363251
+- 0.4538939893245697
+- 0.47312670946121216
+max_scaled_mean_absolute_error:
+- 0.335816890001297
+- 0.3273136615753174
+- 0.32770025730133057
+- 0.33756428956985474
+- 0.35288602113723755
+max_scaled_root_mean_squared_error:
+- 0.4639325737953186
+- 0.456274151802063
+- 0.4510149657726288
+- 0.46401575207710266
+- 0.480268269777298
+max_val_loss:
+- 0.15461614727973938
+- 0.16434505581855774
+- 0.17289485037326813
+- 0.15996496379375458
+- 0.16088221967220306
+max_val_scaled_mean_absolute_error:
+- 0.11454213410615921
+- 0.12140224874019623
+- 0.12856562435626984
+- 0.11897993087768555
+- 0.12006698548793793
+max_val_scaled_root_mean_squared_error:
+- 0.1518266499042511
+- 0.16154775023460388
+- 0.16712376475334167
+- 0.1560198813676834
+- 0.15944355726242065
+min_learning_rate:
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+min_loss:
+- 0.006682931911200285
+- 0.005884940270334482
+- 0.0054324958473443985
+- 0.005202374421060085
+- 0.005429239012300968
+min_scaled_mean_absolute_error:
+- 0.004952264484018087
+- 0.0043501476757228374
+- 0.004039786756038666
+- 0.003869774052873254
+- 0.004050583578646183
+min_scaled_root_mean_squared_error:
+- 0.013786262832581997
+- 0.010175243020057678
+- 0.00982213020324707
+- 0.008825990371406078
+- 0.011821199208498001
+min_val_loss:
+- 0.0513911098241806
+- 0.05351201072335243
+- 0.04997345060110092
+- 0.04981572926044464
+- 0.05114368349313736
+min_val_scaled_mean_absolute_error:
+- 0.038059163838624954
+- 0.03956983610987663
+- 0.037180110812187195
+- 0.03702397644519806
+- 0.03810892999172211
+min_val_scaled_root_mean_squared_error:
+- 0.06310626864433289
+- 0.06860072910785675
+- 0.06758585572242737
+- 0.06064404174685478
+- 0.06464245170354843
+model_class: make_crystal_model
+model_name: NMPN
+model_version: '2023-11-22'
+multi_target_indices: null
+number_histories: 5
+scaled_mean_absolute_error:
+- 0.0051377518102526665
+- 0.004398857243359089
+- 0.004039786756038666
+- 0.003869774052873254
+- 0.0040563964284956455
+scaled_root_mean_squared_error:
+- 0.013905107975006104
+- 0.010181010700762272
+- 0.00982213020324707
+- 0.008825990371406078
+- 0.011821199208498001
+seed: 42
+time_list:
+- '5:24:52.913470'
+- '5:26:28.538504'
+- '5:24:54.249343'
+- '5:26:42.453377'
+- '5:23:43.570943'
+val_loss:
+- 0.0513911098241806
+- 0.053858283907175064
+- 0.05017431080341339
+- 0.049983710050582886
+- 0.05114368349313736
+val_scaled_mean_absolute_error:
+- 0.038059163838624954
+- 0.03982764855027199
+- 0.03732907399535179
+- 0.037146057933568954
+- 0.03810892999172211
+val_scaled_root_mean_squared_error:
+- 0.06339479982852936
+- 0.06905113905668259
+- 0.06779690831899643
+- 0.061015576124191284
+- 0.06472626328468323
diff --git a/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_hyper.json b/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_hyper.json
new file mode 100644
index 00000000..b8674a01
--- /dev/null
+++ b/training/results/MatProjectPerovskitesDataset/NMPN_make_crystal_model/NMPN_hyper.json
@@ -0,0 +1 @@
+{"model": {"class_name": "make_crystal_model", "module_name": "kgcnn.literature.NMPN", "config": {"name": "NMPN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "input_edge_embedding": {"input_dim": 5, "output_dim": 64}, "set2set_args": {"channels": 32, "T": 3, "pooling_method": "sum", "init_qstar": "0"}, "pooling_args": {"pooling_method": "mean"}, "use_set2set": true, "depth": 3, "node_dim": 128, "verbose": 10, "geometric_edge": true, "make_distance": true, "expand_distance": true, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true, false], "units": [25, 25, 1], "activation": ["selu", "selu", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 16, "epochs": 700, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.0001, "learning_rate_stop": 1e-05, "epo_min": 50, "epo": 700, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPerovskitesDataset", "module_name": "kgcnn.data.datasets.MatProjectPerovskitesDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_MatProjectPhononsDataset_score.yaml b/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_MatProjectPhononsDataset_score.yaml
new file mode 100644
index 00000000..725e36f9
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_MatProjectPhononsDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: eV/atom
+date_time: '2024-01-02 12:43:43'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 1000
+- 1000
+- 1000
+- 1000
+- 1000
+execute_folds: null
+kgcnn_version: 4.0.0
+learning_rate:
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+loss:
+- 0.004317963030189276
+- 0.004601033870130777
+- 0.004553907085210085
+- 0.00346244964748621
+- 0.004772838670760393
+max_learning_rate:
+- 0.0010000000474974513
+- 0.0010000000474974513
+- 0.0010000000474974513
+- 0.0010000000474974513
+- 0.0010000000474974513
+max_loss:
+- 0.6415535807609558
+- 0.6290432214736938
+- 0.631635308265686
+- 0.6275734901428223
+- 0.6211722493171692
+max_scaled_mean_absolute_error:
+- 315.7041015625
+- 310.7929382324219
+- 306.69293212890625
+- 299.6334228515625
+- 321.651123046875
+max_scaled_root_mean_squared_error:
+- 501.0257263183594
+- 503.564208984375
+- 493.1729736328125
+- 482.9405517578125
+- 524.8811645507812
+max_val_loss:
+- 0.23609495162963867
+- 0.25098127126693726
+- 0.27506160736083984
+- 0.30150172114372253
+- 0.19292637705802917
+max_val_scaled_mean_absolute_error:
+- 116.31764221191406
+- 124.20046997070312
+- 133.51927185058594
+- 143.6338653564453
+- 99.8260269165039
+max_val_scaled_root_mean_squared_error:
+- 303.0132141113281
+- 302.0243225097656
+- 316.3451843261719
+- 335.3147277832031
+- 200.20040893554688
+min_learning_rate:
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+- 1.1979999726463575e-05
+min_loss:
+- 0.004317963030189276
+- 0.004601033870130777
+- 0.004553907085210085
+- 0.003436138154938817
+- 0.004772838670760393
+min_scaled_mean_absolute_error:
+- 2.1319825649261475
+- 2.2878987789154053
+- 2.2219271659851074
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+- 2.4791715145111084
+min_scaled_root_mean_squared_error:
+- 7.3439226150512695
+- 8.690505027770996
+- 6.702782154083252
+- 5.027475833892822
+- 7.077595233917236
+min_val_loss:
+- 0.07277223467826843
+- 0.08435291051864624
+- 0.09066420048475266
+- 0.09786166995763779
+- 0.0737776979804039
+min_val_scaled_mean_absolute_error:
+- 35.93081283569336
+- 41.74771499633789
+- 44.029117584228516
+- 46.60277557373047
+- 38.213836669921875
+min_val_scaled_root_mean_squared_error:
+- 61.992671966552734
+- 93.23509979248047
+- 83.88030242919922
+- 113.3333740234375
+- 82.26461791992188
+model_class: make_crystal_model
+model_name: CGCNN
+model_version: '2023-11-28'
+multi_target_indices: null
+number_histories: 5
+scaled_mean_absolute_error:
+- 2.1319825649261475
+- 2.2878987789154053
+- 2.2219271659851074
+- 1.6550911664962769
+- 2.4791715145111084
+scaled_root_mean_squared_error:
+- 7.3439226150512695
+- 8.690505027770996
+- 6.702782154083252
+- 5.027475833892822
+- 7.077595233917236
+seed: 42
+time_list:
+- '0:03:49.164667'
+- '0:03:43.402438'
+- '0:03:43.143548'
+- '0:03:44.756334'
+- '0:03:46.732962'
+val_loss:
+- 0.0742277055978775
+- 0.08452695608139038
+- 0.09299201518297195
+- 0.10481196641921997
+- 0.07657171785831451
+val_scaled_mean_absolute_error:
+- 36.64948654174805
+- 41.84267044067383
+- 45.15475082397461
+- 49.90903854370117
+- 39.667606353759766
+val_scaled_root_mean_squared_error:
+- 65.66608428955078
+- 94.41028594970703
+- 84.87903594970703
+- 130.73086547851562
+- 85.12699127197266
diff --git a/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_hyper.json b/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_hyper.json
new file mode 100644
index 00000000..0dfabe67
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/CGCNN_make_crystal_model/CGCNN_hyper.json
@@ -0,0 +1 @@
+{"model": {"class_name": "make_crystal_model", "module_name": "kgcnn.literature.CGCNN", "config": {"name": "CGCNN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_frac_coordinates", "dtype": "float64", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "float32", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float64", "ragged": false}], "input_tensor_type": "ragged", "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "representation": "unit", "expand_distance": true, "make_distances": true, "gauss_args": {"bins": 60, "distance": 6, "offset": 0.0, "sigma": 0.4}, "conv_layer_args": {"units": 128, "activation_s": "kgcnn>shifted_softplus", "activation_out": "kgcnn>shifted_softplus", "batch_normalization": true}, "node_pooling_args": {"pooling_method": "mean"}, "depth": 4, "output_mlp": {"use_bias": [true, true, false], "units": [128, 64, 1], "activation": ["kgcnn>shifted_softplus", "kgcnn>shifted_softplus", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 128, "epochs": 1000, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.001, "learning_rate_stop": 1e-05, "epo_min": 500, "epo": 1000, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {"data_unit": "eV/atom"}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPhononsDataset", "module_name": "kgcnn.data.datasets.MatProjectPhononsDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 6.0}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_MatProjectPhononsDataset_score.yaml b/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_MatProjectPhononsDataset_score.yaml
new file mode 100644
index 00000000..1c701240
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_MatProjectPhononsDataset_score.yaml
@@ -0,0 +1,138 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: 1/cm
+date_time: '2024-01-02 17:47:33'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 780
+- 780
+- 780
+- 780
+- 780
+execute_folds: null
+kgcnn_version: 4.0.0
+loss:
+- 0.012277409434318542
+- 0.01385531947016716
+- 0.019343309104442596
+- 0.014073886908590794
+- 0.015026000328361988
+max_loss:
+- 0.6322934031486511
+- 0.615519106388092
+- 0.6325305104255676
+- 0.6393851637840271
+- 0.6236222982406616
+max_scaled_mean_absolute_error:
+- 312.4471740722656
+- 304.6333312988281
+- 308.8045349121094
+- 306.36981201171875
+- 324.79498291015625
+max_scaled_root_mean_squared_error:
+- 470.322998046875
+- 456.9356384277344
+- 621.3822021484375
+- 462.42425537109375
+- 500.4608459472656
+max_val_loss:
+- 0.20502236485481262
+- 0.18209712207317352
+- 0.20234858989715576
+- 0.18142670392990112
+- 0.12047617882490158
+max_val_scaled_mean_absolute_error:
+- 101.62972259521484
+- 90.70671844482422
+- 97.42705535888672
+- 87.16777038574219
+- 62.73728561401367
+max_val_scaled_root_mean_squared_error:
+- 244.14108276367188
+- 211.4296417236328
+- 196.45420837402344
+- 169.61941528320312
+- 122.7680435180664
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+- 0.009329065680503845
+- 0.009968476369976997
+- 0.01010506134480238
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+- 4.7192254066467285
+- 4.521144390106201
+- 4.771760940551758
+- 5.224360466003418
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+- 10.803009986877441
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+- 9.325139999389648
+- 9.207273483276367
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+- 0.0734875500202179
+- 0.0802382230758667
+- 0.06757279485464096
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+- 39.410888671875
+- 34.75796890258789
+- 37.913761138916016
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+- 58.737186431884766
+- 82.2968521118164
+- 64.97298431396484
+- 69.51397705078125
+- 64.42816925048828
+model_class: make_crystal_model
+model_name: DimeNetPP
+model_version: '2023-12-04'
+multi_target_indices: null
+number_histories: 5
+scaled_mean_absolute_error:
+- 6.082247734069824
+- 6.8491363525390625
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+- 6.747756481170654
+- 7.801123142242432
+scaled_root_mean_squared_error:
+- 11.646354675292969
+- 11.611915588378906
+- 17.117422103881836
+- 12.880290031433105
+- 13.191210746765137
+seed: 42
+time_list:
+- '0:41:59.891056'
+- '0:42:11.136256'
+- '0:42:05.184558'
+- '0:41:49.355133'
+- '0:42:12.683356'
+val_loss:
+- 0.0717245489358902
+- 0.09114867448806763
+- 0.08039277791976929
+- 0.08655380457639694
+- 0.07680327445268631
+val_scaled_mean_absolute_error:
+- 35.41286849975586
+- 44.99383544921875
+- 38.379112243652344
+- 40.610862731933594
+- 40.049747467041016
+val_scaled_root_mean_squared_error:
+- 63.584259033203125
+- 108.71158599853516
+- 68.31204223632812
+- 76.1466293334961
+- 71.13330078125
diff --git a/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_hyper.json b/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_hyper.json
new file mode 100644
index 00000000..c8f23e38
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/DimeNetPP_make_crystal_model/DimeNetPP_hyper.json
@@ -0,0 +1 @@
+{"model": {"class_name": "make_crystal_model", "module_name": "kgcnn.literature.DimeNetPP", "config": {"name": "DimeNetPP", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 2], "name": "angle_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 128, "embeddings_initializer": {"class_name": "RandomUniform", "config": {"minval": -1.7320508075688772, "maxval": 1.7320508075688772}}}, "emb_size": 128, "out_emb_size": 256, "int_emb_size": 64, "basis_emb_size": 8, "num_blocks": 4, "num_spherical": 7, "num_radial": 6, "cutoff": 5.0, "envelope_exponent": 5, "num_before_skip": 1, "num_after_skip": 2, "num_dense_output": 3, "num_targets": 1, "extensive": false, "output_init": "zeros", "activation": "swish", "verbose": 10, "output_embedding": "graph", "use_output_mlp": false, "output_mlp": {}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 16, "epochs": 780, "validation_freq": 10, "verbose": 2, "callbacks": [], "validation_batch_size": 8}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": {"class_name": "kgcnn>LinearWarmupExponentialDecay", "config": {"learning_rate": 0.001, "warmup_steps": 3000.0, "decay_steps": 4000000.0, "decay_rate": 0.01}}, "use_ema": true, "amsgrad": true}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPhononsDataset", "module_name": "kgcnn.data.datasets.MatProjectPhononsDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0, "max_neighbours": 17}}, {"map_list": {"method": "set_angle", "allow_multi_edges": true, "allow_reverse_edges": true}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_MatProjectPhononsDataset_score.yaml b/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_MatProjectPhononsDataset_score.yaml
new file mode 100644
index 00000000..8a682cfa
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_MatProjectPhononsDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: eV/atom
+date_time: '2024-01-02 14:13:32'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 1000
+- 1000
+- 1000
+- 1000
+- 1000
+execute_folds: null
+kgcnn_version: 4.0.0
+learning_rate:
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+loss:
+- 0.007051141932606697
+- 0.009602206759154797
+- 0.00854513980448246
+- 0.00923719722777605
+- 0.005817021243274212
+max_learning_rate:
+- 0.0005000000237487257
+- 0.0005000000237487257
+- 0.0005000000237487257
+- 0.0005000000237487257
+- 0.0005000000237487257
+max_loss:
+- 0.6134491562843323
+- 0.5803906917572021
+- 0.5985342860221863
+- 0.5868727564811707
+- 0.5833007097244263
+max_scaled_mean_absolute_error:
+- 304.2678527832031
+- 288.7700500488281
+- 292.4873352050781
+- 280.8934020996094
+- 303.9534912109375
+max_scaled_root_mean_squared_error:
+- 501.2316589355469
+- 497.31817626953125
+- 495.1467590332031
+- 479.2837219238281
+- 522.7138061523438
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+- 0.27771422266960144
+- 0.19908109307289124
+- 0.16109409928321838
+max_val_scaled_mean_absolute_error:
+- 115.29080963134766
+- 128.34786987304688
+- 134.52682495117188
+- 94.76787567138672
+- 83.42739868164062
+max_val_scaled_root_mean_squared_error:
+- 284.72662353515625
+- 286.8963623046875
+- 315.0444641113281
+- 169.9178924560547
+- 129.64157104492188
+min_learning_rate:
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+- 5.549999968934571e-06
+min_loss:
+- 0.007051141932606697
+- 0.009540339931845665
+- 0.008533337153494358
+- 0.009215925820171833
+- 0.005817021243274212
+min_scaled_mean_absolute_error:
+- 3.4444379806518555
+- 4.760561943054199
+- 4.182170391082764
+- 4.397786617279053
+- 3.041186571121216
+min_scaled_root_mean_squared_error:
+- 8.007569313049316
+- 11.406128883361816
+- 9.011688232421875
+- 11.438080787658691
+- 7.548813819885254
+min_val_loss:
+- 0.05744650959968567
+- 0.05399136245250702
+- 0.062204014509916306
+- 0.07156132906675339
+- 0.049049001187086105
+min_val_scaled_mean_absolute_error:
+- 28.383956909179688
+- 26.74627113342285
+- 30.11005210876465
+- 34.17634582519531
+- 25.217519760131836
+min_val_scaled_root_mean_squared_error:
+- 48.88201141357422
+- 50.5336799621582
+- 49.440189361572266
+- 81.16988372802734
+- 42.893272399902344
+model_class: make_crystal_model
+model_name: Megnet
+model_version: '2023-12-05'
+multi_target_indices: null
+number_histories: 5
+scaled_mean_absolute_error:
+- 3.4444379806518555
+- 4.79186487197876
+- 4.186429023742676
+- 4.410150527954102
+- 3.041186571121216
+scaled_root_mean_squared_error:
+- 8.007569313049316
+- 11.433576583862305
+- 9.016125679016113
+- 11.438080787658691
+- 7.548813819885254
+seed: 42
+time_list:
+- '0:17:38.652550'
+- '0:17:42.397000'
+- '0:17:53.701224'
+- '0:18:06.680776'
+- '0:17:47.542460'
+val_loss:
+- 0.062438301742076874
+- 0.055045727640390396
+- 0.06562171131372452
+- 0.07418853044509888
+- 0.0547359362244606
+val_scaled_mean_absolute_error:
+- 30.832012176513672
+- 27.21445655822754
+- 31.73149871826172
+- 35.41242218017578
+- 28.119686126708984
+val_scaled_root_mean_squared_error:
+- 53.64649200439453
+- 51.25674057006836
+- 51.920631408691406
+- 95.12718200683594
+- 52.415287017822266
diff --git a/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_hyper.json b/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_hyper.json
new file mode 100644
index 00000000..34ead4a9
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/Megnet_make_crystal_model/Megnet_hyper.json
@@ -0,0 +1 @@
+{"model": {"module_name": "kgcnn.literature.Megnet", "class_name": "make_crystal_model", "config": {"name": "Megnet", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [1], "name": "charge", "dtype": "float32", "ragged": false}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "make_distance": true, "expand_distance": true, "gauss_args": {"bins": 25, "distance": 5, "offset": 0.0, "sigma": 0.4}, "meg_block_args": {"node_embed": [64, 32, 32], "edge_embed": [64, 32, 32], "env_embed": [64, 32, 32], "activation": "kgcnn>softplus2"}, "set2set_args": {"channels": 16, "T": 3, "pooling_method": "sum", "init_qstar": "0"}, "node_ff_args": {"units": [64, 32], "activation": "kgcnn>softplus2"}, "edge_ff_args": {"units": [64, 32], "activation": "kgcnn>softplus2"}, "state_ff_args": {"units": [64, 32], "activation": "kgcnn>softplus2"}, "nblocks": 3, "has_ff": true, "dropout": null, "use_set2set": true, "verbose": 10, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true, true], "units": [32, 16, 1], "activation": ["kgcnn>softplus2", "kgcnn>softplus2", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 32, "epochs": 1000, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.0005, "learning_rate_stop": 5e-06, "epo_min": 100, "epo": 1000, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0005}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {"data_unit": "eV/atom"}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPhononsDataset", "module_name": "kgcnn.data.datasets.MatProjectPhononsDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_MatProjectPhononsDataset_score.yaml b/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_MatProjectPhononsDataset_score.yaml
new file mode 100644
index 00000000..c11a85b3
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_MatProjectPhononsDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: 1/cm
+date_time: '2024-01-02 19:44:44'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 700
+- 700
+- 700
+- 700
+- 700
+execute_folds: null
+kgcnn_version: 4.0.0
+learning_rate:
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+- 1.0138461220776662e-05
+loss:
+- 0.011240478605031967
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+number_histories: 5
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diff --git a/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_hyper.json b/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_hyper.json
new file mode 100644
index 00000000..1c0c64ac
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/NMPN_make_crystal_model/NMPN_hyper.json
@@ -0,0 +1 @@
+{"model": {"class_name": "make_crystal_model", "module_name": "kgcnn.literature.NMPN", "config": {"name": "NMPN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 64}, "input_edge_embedding": {"input_dim": 5, "output_dim": 64}, "set2set_args": {"channels": 32, "T": 3, "pooling_method": "sum", "init_qstar": "0"}, "pooling_args": {"pooling_method": "mean"}, "use_set2set": true, "depth": 3, "node_dim": 128, "verbose": 10, "geometric_edge": true, "make_distance": true, "expand_distance": true, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true, false], "units": [25, 25, 1], "activation": ["selu", "selu", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 16, "epochs": 700, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearLearningRateScheduler", "config": {"learning_rate_start": 0.0001, "learning_rate_stop": 1e-05, "epo_min": 50, "epo": 700, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPhononsDataset", "module_name": "kgcnn.data.datasets.MatProjectPhononsDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}]}}
\ No newline at end of file
diff --git a/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_MatProjectPhononsDataset_score.yaml b/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_MatProjectPhononsDataset_score.yaml
new file mode 100644
index 00000000..2c4a1a53
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_MatProjectPhononsDataset_score.yaml
@@ -0,0 +1,156 @@
+OS: posix_linux
+backend: tensorflow
+cuda_available: 'True'
+data_unit: eV/atom
+date_time: '2024-01-02 20:12:13'
+device_id: '[LogicalDevice(name=''/device:CPU:0'', device_type=''CPU''), LogicalDevice(name=''/device:GPU:0'',
+  device_type=''GPU'')]'
+device_memory: '[]'
+device_name: '[{}, {''compute_capability'': (8, 0), ''device_name'': ''NVIDIA A100
+  80GB PCIe''}]'
+epochs:
+- 800
+- 800
+- 800
+- 800
+- 800
+execute_folds: null
+kgcnn_version: 4.0.0
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+model_version: '2023-10-04'
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+number_histories: 5
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+- '0:04:59.256798'
+- '0:04:55.463463'
+- '0:04:57.663193'
+- '0:04:54.369220'
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diff --git a/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_hyper.json b/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_hyper.json
new file mode 100644
index 00000000..82b05af3
--- /dev/null
+++ b/training/results/MatProjectPhononsDataset/PAiNN_make_crystal_model/PAiNN_hyper.json
@@ -0,0 +1 @@
+{"model": {"module_name": "kgcnn.literature.PAiNN", "class_name": "make_crystal_model", "config": {"name": "PAiNN", "inputs": [{"shape": [null], "name": "node_number", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "node_coordinates", "dtype": "float32", "ragged": true}, {"shape": [null, 2], "name": "range_indices", "dtype": "int64", "ragged": true}, {"shape": [null, 3], "name": "range_image", "dtype": "int64", "ragged": true}, {"shape": [3, 3], "name": "graph_lattice", "dtype": "float32", "ragged": false}], "input_tensor_type": "ragged", "input_embedding": null, "input_node_embedding": {"input_dim": 95, "output_dim": 128}, "equiv_initialize_kwargs": {"dim": 3, "method": "eye"}, "bessel_basis": {"num_radial": 20, "cutoff": 5.0, "envelope_exponent": 5}, "pooling_args": {"pooling_method": "mean"}, "conv_args": {"units": 128, "cutoff": null, "conv_pool": "sum"}, "update_args": {"units": 128}, "depth": 2, "verbose": 10, "equiv_normalization": false, "node_normalization": false, "output_embedding": "graph", "output_mlp": {"use_bias": [true, true], "units": [128, 1], "activation": ["swish", "linear"]}}}, "training": {"cross_validation": {"class_name": "KFold", "config": {"n_splits": 5, "random_state": 42, "shuffle": true}}, "fit": {"batch_size": 32, "epochs": 800, "validation_freq": 10, "verbose": 2, "callbacks": [{"class_name": "kgcnn>LinearWarmupLinearLearningRateScheduler", "config": {"learning_rate_start": 0.0001, "learning_rate_stop": 1e-06, "epo_warmup": 25, "epo": 1000, "verbose": 0}}]}, "compile": {"optimizer": {"class_name": "Adam", "config": {"learning_rate": 0.0001}}, "loss": "mean_absolute_error"}, "scaler": {"class_name": "StandardLabelScaler", "module_name": "kgcnn.data.transform.scaler.standard", "config": {"with_std": true, "with_mean": true, "copy": true}}, "multi_target_indices": null}, "data": {"data_unit": "eV/atom"}, "info": {"postfix": "", "postfix_file": "", "kgcnn_version": "4.0.0"}, "dataset": {"class_name": "MatProjectPhononsDataset", "module_name": "kgcnn.data.datasets.MatProjectPhononsDataset", "config": {}, "methods": [{"map_list": {"method": "set_range_periodic", "max_distance": 5.0}}]}}
\ No newline at end of file