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diegoodd
/
Graficos
forked from PythonFZ/LiCl_900K_ACSF

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params.yaml 1.8 KB
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  1. data:
    2. 

  2.   split:
    3. 

  3.   - 0.7
    4. 

  4.   - 0.25
    5. 

  5.   - 0.05
    6. 

  6.   train_data_settings:  # this  does not belong to data!
    7. 

  7.     repeat: true
    8. 

  8.     shuffle: 2000
    9. 

  9.     steps_per_epoch: 32
    10. 

  10. descriptors:
    11. 

  11.   ACSF_0:
    12. 

  12.     g2_params:
    13. 

  13.     - - 0.01
    14. 

  14.       - 1.5
    15. 

  15.     - - 0.01
    16. 

  16.       - 2.5
    17. 

  17.     - - 0.01
    18. 

  18.       - 3.5
    19. 

  19.     - - 0.01
    20. 

  20.       - 4.5
    21. 

  21.     - - 0.01
    22. 

  22.       - 5.5
    23. 

  23.     - - 1.0
    24. 

  24.       - 1.5
    25. 

  25.     - - 1.0
    26. 

  26.       - 2.5
    27. 

  27.     - - 1.0
    28. 

  28.       - 3.5
    29. 

  29.     - - 1.0
    30. 

  30.       - 4.5
    31. 

  31.     - - 1.0
    32. 

  32.       - 5.5
    33. 

  33.     - - 2.0
    34. 

  34.       - 1.5
    35. 

  35.     - - 2.0
    36. 

  36.       - 2.5
    37. 

  37.     - - 2.0
    38. 

  38.       - 3.5
    39. 

  39.     - - 2.0
    40. 

  40.       - 4.5
    41. 

  41.     - - 2.0
    42. 

  42.       - 5.5
    43. 

  43.     g4_params:
    44. 

  44.     - - 0.01
    45. 

  45.       - 1
    46. 

  46.       - 1
    47. 

  47.     - - 0.01
    48. 

  48.       - 6
    49. 

  49.       - 1
    50. 

  50.     - - 0.01
    51. 

  51.       - 1
    52. 

  52.       - -1
    53. 

  53.     - - 0.01
    54. 

  54.       - 6
    55. 

  55.       - -1
    56. 

  56.     - - 0.1
    57. 

  57.       - 1
    58. 

  58.       - 1
    59. 

  59.     - - 0.1
    60. 

  60.       - 6
    61. 

  61.       - 1
    62. 

  62.     - - 0.1
    63. 

  63.       - 1
    64. 

  64.       - -1
    65. 

  65.     - - 0.1
    66. 

  66.       - 6
    67. 

  67.       - -1
    68. 

  68.     - - 0.2
    69. 

  69.       - 1
    70. 

  70.       - 1
    71. 

  71.     - - 0.2
    72. 

  72.       - 6
    73. 

  73.       - 1
    74. 

  74.     - - 0.2
    75. 

  75.       - 1
    76. 

  76.       - -1
    77. 

  77.     - - 0.2
    78. 

  78.       - 6
    79. 

  79.       - -1
    80. 

  80.     g5_params:
    81. 

  81.     - - 0.01
    82. 

  82.       - 1
    83. 

  83.       - 1
    84. 

  84.     - - 0.01
    85. 

  85.       - 6
    86. 

  86.       - 1
    87. 

  87.     - - 0.01
    88. 

  88.       - 1
    89. 

  89.       - -1
    90. 

  90.     - - 0.01
    91. 

  91.       - 6
    92. 

  92.       - -1
    93. 

  93.     - - 0.1
    94. 

  94.       - 1
    95. 

  95.       - 1
    96. 

  96.     - - 0.1
    97. 

  97.       - 6
    98. 

  98.       - 1
    99. 

  99.     - - 0.1
    100. 

  100.       - 1
    101. 

  101.       - -1
    102. 

  102.     - - 0.1
    103. 

  103.       - 6
    104. 

  104.       - -1
    105. 

  105.     - - 0.2
    106. 

  106.       - 1
    107. 

  107.       - 1
    108. 

  108.     - - 0.2
    109. 

  109.       - 6
    110. 

  110.       - 1
    111. 

  111.     - - 0.2
    112. 

  112.       - 1
    113. 

  113.       - -1
    114. 

  114.     - - 0.2
    115. 

  115.       - 6
    116. 

  116.       - -1
    117. 

  117.     r_cut: 6.1
    118. 

  118. general:
    119. 

  119.   train_on_forces: true
    120. 

  120.   layers:
    121. 

  121.   - 16
    122. 

  122.   - 16
    123. 

  123. training:
    124. 

  124.   Optimizer:
    125. 

  125.     Adam:
    126. 

  126.       beta_1: 0.9
    127. 

  127.       beta_2: 0.999
    128. 

  128.       decay: 0.0
    129. 

  129.       learning_rate: 0.0001
    130. 

  130.   beta: 50
    131. 

  131.   loss: mse
    132. 

  132.   order:
    133. 

  133.   - ef
    134. 

  134.   scale_force_loss_by_y_true: 0.0
    135. 

  135.   epochs: 2048
    136. 

  136.   batch_size: 64
    137. 

  137.   steps_per_epoch: 32
    138. 

  138. 

  139. system:
    140. 

  140.   data: /beegfs/work/fzills/work/data/LiCl_900K.extxyz
    141. 

  141.   datasets:
    142. 

  142.   - - uniform_energetic
    143. 

  143.     - 5000
    144. 

  144. 

  145. evaluation:
    146. 

  146.   batch: 256
    147. 

  147.
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