
Epoch 0, train loss: 0.0276, val loss: 0.2903
Epoch 10, train loss: 0.0448, val loss: 0.1569
Epoch 20, train loss: 0.0281, val loss: 0.1484
Epoch 30, train loss: 0.0136, val loss: 0.0823
Epoch 40, train loss: 0.0104, val loss: 0.0222
Epoch 0, train loss: 0.0276, val loss: 0.2903
Epoch 10, train loss: 0.0448, val loss: 0.1569
Epoch 20, train loss: 0.0281, val loss: 0.1484
Epoch 30, train loss: 0.0136, val loss: 0.0823
Epoch 40, train loss: 0.0104, val loss: 0.0222
Epoch 50, train loss: 0.0034, val loss: 0.0359
Epoch 60, train loss: 0.0123, val loss: 0.0432
Epoch 70, train loss: 0.0025, val loss: 0.0353
Epoch 80, train loss: 0.0029, val loss: 0.0525
Epoch 90, train loss: 0.0062, val loss: 0.0332
Epoch 0, train loss: 0.0276, val loss: 0.0591
Epoch 10, train loss: 0.0063, val loss: 0.0211
Epoch 20, train loss: 0.0035, val loss: 0.0095
Epoch 30, train loss: 0.0037, val loss: 0.0087
Epoch 40, train loss: 0.0021, val loss: 0.0064
Epoch 0, train loss: 0.0276, val loss: 0.0591
Epoch 10, train loss: 0.0063, val loss: 0.0211
Epoch 20, train loss: 0.0035, val loss: 0.0095
Epoch 30, train loss: 0.0037, val loss: 0.0087
Epoch 40, train loss: 0.0021, val loss: 0.0064
Epoch 50, train loss: 0.0023, val loss: 0.0011
Epoch 60, train loss: 0.0021, val loss: 0.0014
Epoch 70, train loss: 0.0021, val loss: 0.0026
Inferred coeffs for Iceland: [ 1.0874174   1.2012991   0.78881925  0.57075703  0.9403868   1.2959636
 -2.9035969  -0.58980584  0.17985156  0.08447907 -1.3626273  -0.00868878
  0.00518758 -4.609413    2.4914653  -0.0207415  -1.4212822   0.86968696]
Epoch 0, train loss: 0.0297, val loss: 0.3061
Epoch 10, train loss: 0.0434, val loss: 0.1531
Epoch 20, train loss: 0.0254, val loss: 0.0306
Epoch 30, train loss: 0.0083, val loss: 0.0160
Epoch 40, train loss: 0.0063, val loss: 0.0076
Epoch 0, train loss: 0.0297, val loss: 0.3061
Epoch 10, train loss: 0.0434, val loss: 0.1531
Epoch 20, train loss: 0.0254, val loss: 0.0306
Epoch 30, train loss: 0.0083, val loss: 0.0160
Epoch 40, train loss: 0.0063, val loss: 0.0076
Epoch 50, train loss: 0.0103, val loss: 0.0368
Epoch 60, train loss: 0.0167, val loss: 0.0624
Epoch 70, train loss: 0.0067, val loss: 0.0060
Epoch 80, train loss: 0.0056, val loss: 0.0014
Epoch 0, train loss: 0.0297, val loss: 0.0633
Epoch 10, train loss: 0.0055, val loss: 0.0119
Epoch 20, train loss: 0.0034, val loss: 0.0016
Epoch 30, train loss: 0.0025, val loss: 0.0070
Epoch 40, train loss: 0.0022, val loss: 0.0012
Epoch 0, train loss: 0.0297, val loss: 0.0633
Epoch 10, train loss: 0.0055, val loss: 0.0119
Epoch 20, train loss: 0.0034, val loss: 0.0016
Epoch 30, train loss: 0.0025, val loss: 0.0070
Epoch 40, train loss: 0.0022, val loss: 0.0012
Epoch 50, train loss: 0.0022, val loss: 0.0023
Epoch 60, train loss: 0.0022, val loss: 0.0021
Epoch 70, train loss: 0.0022, val loss: 0.0022
Inferred coeffs for Canada: [ 1.0879971   1.1934887   0.795313    0.53868735  0.9428565   1.287983
 -2.8912663  -0.5786172   0.18522346  0.0845518  -1.3682208  -0.00810417
  0.00460294 -4.5583878   2.4398267  -0.02143388 -1.3592615   0.81293106]
Epoch 0, train loss: 0.0191, val loss: 0.3074
Epoch 10, train loss: 0.0534, val loss: 0.1701
Epoch 20, train loss: 0.0169, val loss: 0.0353
Epoch 30, train loss: 0.0044, val loss: 0.0732
Epoch 40, train loss: 0.0022, val loss: 0.0030
Epoch 0, train loss: 0.0191, val loss: 0.3074
Epoch 10, train loss: 0.0534, val loss: 0.1701
Epoch 20, train loss: 0.0169, val loss: 0.0353
Epoch 30, train loss: 0.0044, val loss: 0.0732
Epoch 40, train loss: 0.0022, val loss: 0.0030
Epoch 50, train loss: 0.0020, val loss: 0.0087
Epoch 60, train loss: 0.0030, val loss: 0.0312
Epoch 70, train loss: 0.0051, val loss: 0.0221
Epoch 80, train loss: 0.0024, val loss: 0.0179
Epoch 90, train loss: 0.0044, val loss: 0.0042
Epoch 0, train loss: 0.0191, val loss: 0.0460
Epoch 10, train loss: 0.0021, val loss: 0.0109
Epoch 20, train loss: 0.0019, val loss: 0.0111
Epoch 30, train loss: 0.0019, val loss: 0.0142
Epoch 0, train loss: 0.0191, val loss: 0.0460
Epoch 10, train loss: 0.0021, val loss: 0.0109
Epoch 20, train loss: 0.0019, val loss: 0.0111
Epoch 30, train loss: 0.0019, val loss: 0.0142
Inferred coeffs for Algeria: [ 1.08774     1.1925653   0.7954367   0.5370432   0.9425967   1.2879224
 -2.8907819  -0.5773866   0.18493176  0.08519835 -1.3691803  -0.00835352
  0.00485227 -4.591908    2.4736567  -0.02120905 -1.3511558   0.80556214]
Epoch 0, train loss: 0.0212, val loss: 0.3193
Epoch 10, train loss: 0.0512, val loss: 0.1846
Epoch 20, train loss: 0.0151, val loss: 0.0515
Epoch 30, train loss: 0.0029, val loss: 0.0560
Epoch 40, train loss: 0.0007, val loss: 0.0219
Epoch 0, train loss: 0.0212, val loss: 0.3193
Epoch 10, train loss: 0.0512, val loss: 0.1846
Epoch 20, train loss: 0.0151, val loss: 0.0515
Epoch 30, train loss: 0.0029, val loss: 0.0560
Epoch 40, train loss: 0.0007, val loss: 0.0219
Epoch 50, train loss: 0.0029, val loss: 0.0108
Epoch 60, train loss: 0.0124, val loss: 0.0244
Epoch 70, train loss: 0.0091, val loss: 0.0232
Epoch 80, train loss: 0.0020, val loss: 0.0138
Epoch 0, train loss: 0.0212, val loss: 0.0313
Epoch 10, train loss: 0.0067, val loss: 0.0183
Epoch 20, train loss: 0.0032, val loss: 0.0053
Epoch 30, train loss: 0.0007, val loss: 0.0099
Epoch 40, train loss: 0.0010, val loss: 0.0008
Epoch 0, train loss: 0.0212, val loss: 0.0313
Epoch 10, train loss: 0.0067, val loss: 0.0183
Epoch 20, train loss: 0.0032, val loss: 0.0053
Epoch 30, train loss: 0.0007, val loss: 0.0099
Epoch 40, train loss: 0.0010, val loss: 0.0008
Epoch 50, train loss: 0.0011, val loss: 0.0051
Inferred coeffs for Burkina Faso: [ 1.086593    1.2004565   0.7880117   0.5714795   0.93955255  1.2967691
 -2.9044006  -0.58895755  0.1790904   0.08526935 -1.3634465  -0.00951149
  0.00601028 -4.6093698   2.4914184  -0.01992001 -1.4205086   0.8689412 ]
Epoch 0, train loss: 0.0220, val loss: 0.3035
Epoch 10, train loss: 0.0503, val loss: 0.1701
Epoch 20, train loss: 0.0146, val loss: 0.0378
Epoch 30, train loss: 0.0024, val loss: 0.0693
Epoch 40, train loss: 0.0011, val loss: 0.0196
Epoch 0, train loss: 0.0220, val loss: 0.3035
Epoch 10, train loss: 0.0503, val loss: 0.1701
Epoch 20, train loss: 0.0146, val loss: 0.0378
Epoch 30, train loss: 0.0024, val loss: 0.0693
Epoch 40, train loss: 0.0011, val loss: 0.0196
Epoch 0, train loss: 0.0220, val loss: 0.0459
Epoch 10, train loss: 0.0075, val loss: 0.0356
Epoch 20, train loss: 0.0011, val loss: 0.0154
Epoch 30, train loss: 0.0017, val loss: 0.0147
Epoch 40, train loss: 0.0014, val loss: 0.0057
Epoch 0, train loss: 0.0220, val loss: 0.0459
Epoch 10, train loss: 0.0075, val loss: 0.0356
Epoch 20, train loss: 0.0011, val loss: 0.0154
Epoch 30, train loss: 0.0017, val loss: 0.0147
Epoch 40, train loss: 0.0014, val loss: 0.0057
Epoch 50, train loss: 0.0012, val loss: 0.0075
Inferred coeffs for Ghana: [ 1.0873438   1.1964039   0.7921053   0.55297333  0.9413425   1.2918923
 -2.8969424  -0.58305305  0.18242209  0.08497865 -1.3662347  -0.00875679
  0.00525557 -4.6063266   2.4883423  -0.02073426 -1.3860972   0.83738554]
Epoch 0, train loss: 0.0209, val loss: 0.3138
Epoch 10, train loss: 0.0515, val loss: 0.1790
Epoch 20, train loss: 0.0154, val loss: 0.0458
Epoch 30, train loss: 0.0031, val loss: 0.0617
Epoch 40, train loss: 0.0012, val loss: 0.0273
Epoch 0, train loss: 0.0209, val loss: 0.3138
Epoch 10, train loss: 0.0515, val loss: 0.1790
Epoch 20, train loss: 0.0154, val loss: 0.0458
Epoch 30, train loss: 0.0031, val loss: 0.0617
Epoch 40, train loss: 0.0012, val loss: 0.0273
Epoch 50, train loss: 0.0052, val loss: 0.0207
Epoch 60, train loss: 0.0013, val loss: 0.0071
Epoch 70, train loss: 0.0015, val loss: 0.0118
Epoch 80, train loss: 0.0020, val loss: 0.0422
Epoch 0, train loss: 0.0209, val loss: 0.0370
Epoch 10, train loss: 0.0081, val loss: 0.0268
Epoch 20, train loss: 0.0034, val loss: 0.0144
Epoch 30, train loss: 0.0026, val loss: 0.0078
Epoch 40, train loss: 0.0012, val loss: 0.0026
Epoch 0, train loss: 0.0209, val loss: 0.0370
Epoch 10, train loss: 0.0081, val loss: 0.0268
Epoch 20, train loss: 0.0034, val loss: 0.0144
Epoch 30, train loss: 0.0026, val loss: 0.0078
Epoch 40, train loss: 0.0012, val loss: 0.0026
Epoch 50, train loss: 0.0012, val loss: 0.0031
Epoch 60, train loss: 0.0012, val loss: 0.0008
Epoch 70, train loss: 0.0011, val loss: 0.0008
Epoch 80, train loss: 0.0011, val loss: 0.0008
Inferred coeffs for Cote d'Ivoire: [ 1.0867902   1.2006419   0.78821474  0.5712592   0.9397571   1.2965652
 -2.9041867  -0.5891381   0.17926915  0.08509003 -1.3632667  -0.00931454
  0.00581334 -4.6093335   2.4913814  -0.02011659 -1.4205247   0.8689562 ]
Epoch 0, train loss: 0.0241, val loss: 0.3129
Epoch 10, train loss: 0.0482, val loss: 0.1803
Epoch 20, train loss: 0.0252, val loss: 0.1282
Epoch 30, train loss: 0.0136, val loss: 0.0054
Epoch 40, train loss: 0.0052, val loss: 0.0038
Epoch 0, train loss: 0.0241, val loss: 0.3129
Epoch 10, train loss: 0.0482, val loss: 0.1803
Epoch 20, train loss: 0.0252, val loss: 0.1282
Epoch 30, train loss: 0.0136, val loss: 0.0054
Epoch 40, train loss: 0.0052, val loss: 0.0038
Epoch 50, train loss: 0.0105, val loss: 0.0017
Epoch 60, train loss: 0.0023, val loss: 0.0180
Epoch 70, train loss: 0.0092, val loss: 0.0091
Epoch 80, train loss: 0.0059, val loss: 0.0141
Epoch 0, train loss: 0.0241, val loss: 0.0356
Epoch 10, train loss: 0.0065, val loss: 0.0134
Epoch 20, train loss: 0.0023, val loss: 0.0011
Epoch 30, train loss: 0.0022, val loss: 0.0046
Epoch 40, train loss: 0.0022, val loss: 0.0064
Epoch 0, train loss: 0.0241, val loss: 0.0356
Epoch 10, train loss: 0.0065, val loss: 0.0134
Epoch 20, train loss: 0.0023, val loss: 0.0011
Epoch 30, train loss: 0.0022, val loss: 0.0046
Epoch 40, train loss: 0.0022, val loss: 0.0064
Epoch 50, train loss: 0.0021, val loss: 0.0089
Inferred coeffs for Niger: [ 1.0867404   1.2006218   0.788147    0.57139504  0.93969744  1.2966359
 -2.9042764  -0.58912915  0.17922714  0.08512097 -1.3632867  -0.00936423
  0.00586303 -4.6094975   2.4915478  -0.02006706 -1.4207863   0.8692078 ]
Epoch 0, train loss: 0.0208, val loss: 0.3220
Epoch 10, train loss: 0.0519, val loss: 0.1815
Epoch 20, train loss: 0.0147, val loss: 0.0446
Epoch 30, train loss: 0.0096, val loss: 0.0407
Epoch 40, train loss: 0.0282, val loss: 0.0880
Epoch 0, train loss: 0.0208, val loss: 0.3220
Epoch 10, train loss: 0.0519, val loss: 0.1815
Epoch 20, train loss: 0.0147, val loss: 0.0446
Epoch 30, train loss: 0.0096, val loss: 0.0407
Epoch 40, train loss: 0.0282, val loss: 0.0880
Epoch 50, train loss: 0.0083, val loss: 0.0106
Epoch 60, train loss: 0.0065, val loss: 0.0216
Epoch 70, train loss: 0.0129, val loss: 0.0107
Epoch 80, train loss: 0.0183, val loss: 0.0917
Epoch 0, train loss: 0.0208, val loss: 0.0347
Epoch 10, train loss: 0.0073, val loss: 0.0241
Epoch 20, train loss: 0.0027, val loss: 0.0116
Epoch 30, train loss: 0.0026, val loss: 0.0090
Epoch 40, train loss: 0.0018, val loss: 0.0007
Epoch 0, train loss: 0.0208, val loss: 0.0347
Epoch 10, train loss: 0.0073, val loss: 0.0241
Epoch 20, train loss: 0.0027, val loss: 0.0116
Epoch 30, train loss: 0.0026, val loss: 0.0090
Epoch 40, train loss: 0.0018, val loss: 0.0007
Inferred coeffs for Tunisia: [ 1.0866723   1.200562    0.78807265  0.57149535  0.9396271   1.2967119
 -2.9043562  -0.5890724   0.17915319  0.08518937 -1.3633493  -0.00943242
  0.00593122 -4.6090984   2.4911416  -0.0199991  -1.4207606   0.869186  ]
Epoch 0, train loss: 0.0164, val loss: 0.3542
Epoch 10, train loss: 0.0570, val loss: 0.1882
Epoch 20, train loss: 0.0151, val loss: 0.0353
Epoch 30, train loss: 0.0150, val loss: 0.0371
Epoch 40, train loss: 0.0013, val loss: 0.0441
Epoch 0, train loss: 0.0164, val loss: 0.3542
Epoch 10, train loss: 0.0570, val loss: 0.1882
Epoch 20, train loss: 0.0151, val loss: 0.0353
Epoch 30, train loss: 0.0150, val loss: 0.0371
Epoch 40, train loss: 0.0013, val loss: 0.0441
Epoch 0, train loss: 0.0164, val loss: 0.0279
Epoch 10, train loss: 0.0017, val loss: 0.0036
Epoch 20, train loss: 0.0022, val loss: 0.0063
Epoch 30, train loss: 0.0009, val loss: 0.0165
Epoch 0, train loss: 0.0164, val loss: 0.0279
Epoch 10, train loss: 0.0017, val loss: 0.0036
Epoch 20, train loss: 0.0022, val loss: 0.0063
Epoch 30, train loss: 0.0009, val loss: 0.0165
Inferred coeffs for Belgium: [ 1.0864737   1.2004282   0.78783077  0.5719203   0.93941575  1.2969627
 -2.9046407  -0.58896184  0.17892429  0.08537901 -1.3634996  -0.0096309
  0.0061297  -4.6087995   2.4908452  -0.01979964 -1.421079    0.8694552 ]
Epoch 0, train loss: 0.0185, val loss: 0.5330
Epoch 10, train loss: 0.0486, val loss: 0.1517
Epoch 20, train loss: 0.0162, val loss: 0.0703
Epoch 30, train loss: 0.0015, val loss: 0.0666
Epoch 40, train loss: 0.0045, val loss: 0.0173
Epoch 0, train loss: 0.0185, val loss: 0.5330
Epoch 10, train loss: 0.0486, val loss: 0.1517
Epoch 20, train loss: 0.0162, val loss: 0.0703
Epoch 30, train loss: 0.0015, val loss: 0.0666
Epoch 40, train loss: 0.0045, val loss: 0.0173
Epoch 50, train loss: 0.0055, val loss: 0.0162
Epoch 60, train loss: 0.0018, val loss: 0.0284
Epoch 70, train loss: 0.0125, val loss: 0.0377
Epoch 80, train loss: 0.0149, val loss: 0.0561
Epoch 0, train loss: 0.0185, val loss: 0.0207
Epoch 10, train loss: 0.0124, val loss: 0.0396
Epoch 20, train loss: 0.0038, val loss: 0.0162
Epoch 30, train loss: 0.0008, val loss: 0.0084
Epoch 40, train loss: 0.0004, val loss: 0.0093
Epoch 0, train loss: 0.0185, val loss: 0.0207
Epoch 10, train loss: 0.0124, val loss: 0.0396
Epoch 20, train loss: 0.0038, val loss: 0.0162
Epoch 30, train loss: 0.0008, val loss: 0.0084
Epoch 40, train loss: 0.0004, val loss: 0.0093
Epoch 50, train loss: 0.0007, val loss: 0.0115
Inferred coeffs for Germany: [ 1.0858968   1.1904823   0.79402703  0.53563005  0.94013804  1.2892148
 -2.892273   -0.57530236  0.18637547  0.08490166 -1.3700591  -0.01023387
  0.00673261 -4.488397    2.367865   -0.0193053  -1.3611847   0.81426096]
Epoch 0, train loss: 0.0225, val loss: 0.3046
Epoch 10, train loss: 0.0499, val loss: 0.1703
Epoch 20, train loss: 0.0184, val loss: 0.0650
Epoch 30, train loss: 0.0067, val loss: 0.0026
Epoch 40, train loss: 0.0103, val loss: 0.0086
Epoch 0, train loss: 0.0225, val loss: 0.3046
Epoch 10, train loss: 0.0499, val loss: 0.1703
Epoch 20, train loss: 0.0184, val loss: 0.0650
Epoch 30, train loss: 0.0067, val loss: 0.0026
Epoch 40, train loss: 0.0103, val loss: 0.0086
Epoch 0, train loss: 0.0225, val loss: 0.0457
Epoch 10, train loss: 0.0063, val loss: 0.0292
Epoch 20, train loss: 0.0029, val loss: 0.0153
Epoch 30, train loss: 0.0025, val loss: 0.0075
Epoch 40, train loss: 0.0018, val loss: 0.0013
Epoch 0, train loss: 0.0225, val loss: 0.0457
Epoch 10, train loss: 0.0063, val loss: 0.0292
Epoch 20, train loss: 0.0029, val loss: 0.0153
Epoch 30, train loss: 0.0025, val loss: 0.0075
Epoch 40, train loss: 0.0018, val loss: 0.0013
Epoch 50, train loss: 0.0016, val loss: 0.0054
Inferred coeffs for Estonia: [ 1.087011    1.2008808   0.7884251   0.5710872   0.93997145  1.2963561
 -2.9039898  -0.58938396  0.17949854  0.08485509 -1.363026   -0.00909343
  0.00559223 -4.6093707   2.49142    -0.02033803 -1.4209428   0.86937386]
Epoch 0, train loss: 0.0478, val loss: 0.1914
Epoch 10, train loss: 0.0178, val loss: 0.1041
Epoch 20, train loss: 0.0163, val loss: 0.0228
Epoch 30, train loss: 0.0125, val loss: 0.0225
Epoch 40, train loss: 0.0131, val loss: 0.0528
Epoch 0, train loss: 0.0478, val loss: 0.1914
Epoch 10, train loss: 0.0178, val loss: 0.1041
Epoch 20, train loss: 0.0163, val loss: 0.0228
Epoch 30, train loss: 0.0125, val loss: 0.0225
Epoch 40, train loss: 0.0131, val loss: 0.0528
Epoch 50, train loss: 0.0125, val loss: 0.0519
Epoch 0, train loss: 0.0478, val loss: 0.1744
Epoch 10, train loss: 0.0137, val loss: 0.0199
Epoch 20, train loss: 0.0131, val loss: 0.0490
Epoch 30, train loss: 0.0116, val loss: 0.0323
Epoch 0, train loss: 0.0478, val loss: 0.1744
Epoch 10, train loss: 0.0137, val loss: 0.0199
Epoch 20, train loss: 0.0131, val loss: 0.0490
Epoch 30, train loss: 0.0116, val loss: 0.0323
Inferred coeffs for Ireland: [ 1.0903428e+00  1.2043245e+00  7.9168099e-01  5.6815076e-01
  9.4328094e-01  1.2931163e+00 -2.9008074e+00 -5.9286785e-01
  1.8277448e-01  8.1510268e-02 -1.3596121e+00 -5.7620239e-03
  2.2608237e-03 -4.6084127e+00  2.4904635e+00 -2.3668051e-02
 -1.4251426e+00  8.7349844e-01]
Epoch 0, train loss: 0.0376, val loss: 0.2546
Epoch 10, train loss: 0.0349, val loss: 0.1169
Epoch 20, train loss: 0.0182, val loss: 0.0203
Epoch 30, train loss: 0.0161, val loss: 0.0491
Epoch 40, train loss: 0.0090, val loss: 0.0328
Epoch 0, train loss: 0.0376, val loss: 0.2546
Epoch 10, train loss: 0.0349, val loss: 0.1169
Epoch 20, train loss: 0.0182, val loss: 0.0203
Epoch 30, train loss: 0.0161, val loss: 0.0491
Epoch 40, train loss: 0.0090, val loss: 0.0328
Epoch 50, train loss: 0.0076, val loss: 0.0399
Epoch 60, train loss: 0.0147, val loss: 0.0419
Epoch 70, train loss: 0.0111, val loss: 0.0228
Epoch 0, train loss: 0.0376, val loss: 0.0993
Epoch 10, train loss: 0.0078, val loss: 0.0036
Epoch 20, train loss: 0.0079, val loss: 0.0084
Epoch 30, train loss: 0.0087, val loss: 0.0109
Epoch 40, train loss: 0.0073, val loss: 0.0030
Epoch 0, train loss: 0.0376, val loss: 0.0993
Epoch 10, train loss: 0.0078, val loss: 0.0036
Epoch 20, train loss: 0.0079, val loss: 0.0084
Epoch 30, train loss: 0.0087, val loss: 0.0109
Epoch 40, train loss: 0.0073, val loss: 0.0030
Epoch 50, train loss: 0.0070, val loss: 0.0051
Epoch 60, train loss: 0.0070, val loss: 0.0080
Epoch 70, train loss: 0.0069, val loss: 0.0128
Inferred coeffs for Luxembourg: [ 1.0891726e+00  1.1958430e+00  7.9563093e-01  5.4221654e-01
  9.4392896e-01  1.2878468e+00 -2.8916433e+00 -5.8148873e-01
  1.8527235e-01  8.3557606e-02 -1.3662847e+00 -6.9247400e-03
  3.4235090e-03 -4.5935178e+00  2.4754350e+00 -2.2612540e-02
 -1.3677481e+00  8.2113397e-01]
Epoch 0, train loss: 0.0618, val loss: 0.2025
Epoch 10, train loss: 0.0328, val loss: 0.0880
Epoch 20, train loss: 0.0185, val loss: 0.0312
Epoch 30, train loss: 0.0195, val loss: 0.0062
Epoch 40, train loss: 0.0230, val loss: 0.0325
Epoch 0, train loss: 0.0618, val loss: 0.2025
Epoch 10, train loss: 0.0328, val loss: 0.0880
Epoch 20, train loss: 0.0185, val loss: 0.0312
Epoch 30, train loss: 0.0195, val loss: 0.0062
Epoch 40, train loss: 0.0230, val loss: 0.0325
Epoch 50, train loss: 0.0219, val loss: 0.0485
Epoch 60, train loss: 0.0148, val loss: 0.0130
Epoch 70, train loss: 0.0086, val loss: 0.0078
Epoch 80, train loss: 0.0063, val loss: 0.0355
Epoch 0, train loss: 0.0618, val loss: 0.1714
Epoch 10, train loss: 0.0184, val loss: 0.0564
Epoch 20, train loss: 0.0092, val loss: 0.0058
Epoch 30, train loss: 0.0078, val loss: 0.0073
Epoch 40, train loss: 0.0061, val loss: 0.0075
Epoch 0, train loss: 0.0618, val loss: 0.1714
Epoch 10, train loss: 0.0184, val loss: 0.0564
Epoch 20, train loss: 0.0092, val loss: 0.0058
Epoch 30, train loss: 0.0078, val loss: 0.0073
Epoch 40, train loss: 0.0061, val loss: 0.0075
Epoch 50, train loss: 0.0060, val loss: 0.0122
Inferred coeffs for Norway: [ 1.0905122e+00  1.1982950e+00  7.9646742e-01  5.4284602e-01
  9.4570029e-01  1.2866217e+00 -2.8910410e+00 -5.8435011e-01
  1.8656111e-01  8.1617683e-02 -1.3638167e+00 -5.5874265e-03
  2.0862005e-03 -4.5516691e+00  2.4343107e+00 -2.3928609e-02
 -1.3798532e+00  8.3295238e-01]
Epoch 0, train loss: 0.0544, val loss: 0.1826
Epoch 10, train loss: 0.0218, val loss: 0.1120
Epoch 20, train loss: 0.0152, val loss: 0.0461
Epoch 30, train loss: 0.0118, val loss: 0.0065
Epoch 40, train loss: 0.0144, val loss: 0.0780
Epoch 0, train loss: 0.0544, val loss: 0.1826
Epoch 10, train loss: 0.0218, val loss: 0.1120
Epoch 20, train loss: 0.0152, val loss: 0.0461
Epoch 30, train loss: 0.0118, val loss: 0.0065
Epoch 40, train loss: 0.0144, val loss: 0.0780
Epoch 0, train loss: 0.0544, val loss: 0.1916
Epoch 10, train loss: 0.0188, val loss: 0.0064
Epoch 20, train loss: 0.0141, val loss: 0.0628
Epoch 30, train loss: 0.0122, val loss: 0.0131
Epoch 40, train loss: 0.0114, val loss: 0.0380
Epoch 0, train loss: 0.0544, val loss: 0.1916
Epoch 10, train loss: 0.0188, val loss: 0.0064
Epoch 20, train loss: 0.0141, val loss: 0.0628
Epoch 30, train loss: 0.0122, val loss: 0.0131
Epoch 40, train loss: 0.0114, val loss: 0.0380
Epoch 50, train loss: 0.0112, val loss: 0.0281
Inferred coeffs for Poland: [ 1.0908098e+00  1.2019179e+00  7.9425222e-01  5.5625069e-01
  9.4468611e-01  1.2898387e+00 -2.8959482e+00 -5.8936048e-01
  1.8487419e-01  8.1197724e-02 -1.3611670e+00 -5.2928180e-03
  1.7916017e-03 -4.5844383e+00  2.4667163e+00 -2.4174934e-02
 -1.4053195e+00  8.5570592e-01]
Epoch 0, train loss: 0.0156, val loss: 0.3500
Epoch 10, train loss: 0.0575, val loss: 0.1947
Epoch 20, train loss: 0.0176, val loss: 0.0484
Epoch 30, train loss: 0.0036, val loss: 0.0661
Epoch 40, train loss: 0.0003, val loss: 0.0013
Epoch 0, train loss: 0.0156, val loss: 0.3500
Epoch 10, train loss: 0.0575, val loss: 0.1947
Epoch 20, train loss: 0.0176, val loss: 0.0484
Epoch 30, train loss: 0.0036, val loss: 0.0661
Epoch 40, train loss: 0.0003, val loss: 0.0013
Epoch 50, train loss: 0.0143, val loss: 0.0494
Epoch 60, train loss: 0.0161, val loss: 0.0332
Epoch 70, train loss: 0.0077, val loss: 0.0334
Epoch 0, train loss: 0.0156, val loss: 0.0217
Epoch 10, train loss: 0.0021, val loss: 0.0046
Epoch 20, train loss: 0.0022, val loss: 0.0030
Epoch 30, train loss: 0.0019, val loss: 0.0154
Epoch 40, train loss: 0.0020, val loss: 0.0083
Epoch 0, train loss: 0.0156, val loss: 0.0217
Epoch 10, train loss: 0.0021, val loss: 0.0046
Epoch 20, train loss: 0.0022, val loss: 0.0030
Epoch 30, train loss: 0.0019, val loss: 0.0154
Epoch 40, train loss: 0.0020, val loss: 0.0083
Epoch 50, train loss: 0.0017, val loss: 0.0026
Inferred coeffs for Sweden: [ 1.0867741   1.1924715   0.79387784  0.5410721   0.94133174  1.2896421
 -2.8930013  -0.57772124  0.18387783  0.08579591 -1.369315   -0.00931886
  0.00581762 -4.559064    2.4402723  -0.02023313 -1.3590361   0.8126626 ]
Epoch 0, train loss: 0.0356, val loss: 0.2731
Epoch 10, train loss: 0.0448, val loss: 0.1701
Epoch 20, train loss: 0.0349, val loss: 0.1216
Epoch 30, train loss: 0.0087, val loss: 0.0300
Epoch 40, train loss: 0.0050, val loss: 0.0081
Epoch 0, train loss: 0.0356, val loss: 0.2731
Epoch 10, train loss: 0.0448, val loss: 0.1701
Epoch 20, train loss: 0.0349, val loss: 0.1216
Epoch 30, train loss: 0.0087, val loss: 0.0300
Epoch 40, train loss: 0.0050, val loss: 0.0081
Epoch 50, train loss: 0.0064, val loss: 0.0253
Epoch 60, train loss: 0.0058, val loss: 0.0106
Epoch 70, train loss: 0.0059, val loss: 0.0045
Epoch 0, train loss: 0.0356, val loss: 0.0765
Epoch 10, train loss: 0.0048, val loss: 0.0047
Epoch 20, train loss: 0.0073, val loss: 0.0297
Epoch 30, train loss: 0.0049, val loss: 0.0199
Epoch 40, train loss: 0.0049, val loss: 0.0166
Epoch 0, train loss: 0.0356, val loss: 0.0765
Epoch 10, train loss: 0.0048, val loss: 0.0047
Epoch 20, train loss: 0.0073, val loss: 0.0297
Epoch 30, train loss: 0.0049, val loss: 0.0199
Epoch 40, train loss: 0.0049, val loss: 0.0166
Epoch 50, train loss: 0.0048, val loss: 0.0142
Inferred coeffs for South Africa: [ 1.0884646e+00  1.1945392e+00  7.9537815e-01  5.4044759e-01
  9.4334525e-01  1.2879510e+00 -2.8915200e+00 -5.7994384e-01
  1.8518551e-01  8.4118702e-02 -1.3673325e+00 -7.6243458e-03
  4.1231047e-03 -4.6032376e+00  2.4852300e+00 -2.1930967e-02
 -1.3633320e+00  8.1729436e-01]
Epoch 0, train loss: 0.0207, val loss: 0.3097
Epoch 10, train loss: 0.0516, val loss: 0.1766
Epoch 20, train loss: 0.0172, val loss: 0.0529
Epoch 30, train loss: 0.0061, val loss: 0.0583
Epoch 40, train loss: 0.0144, val loss: 0.0380
Epoch 0, train loss: 0.0207, val loss: 0.3097
Epoch 10, train loss: 0.0516, val loss: 0.1766
Epoch 20, train loss: 0.0172, val loss: 0.0529
Epoch 30, train loss: 0.0061, val loss: 0.0583
Epoch 40, train loss: 0.0144, val loss: 0.0380
Epoch 50, train loss: 0.0032, val loss: 0.0016
Epoch 60, train loss: 0.0030, val loss: 0.0132
Epoch 70, train loss: 0.0054, val loss: 0.0157
Epoch 80, train loss: 0.0159, val loss: 0.0194
Epoch 0, train loss: 0.0207, val loss: 0.0393
Epoch 10, train loss: 0.0064, val loss: 0.0203
Epoch 20, train loss: 0.0038, val loss: 0.0165
Epoch 30, train loss: 0.0030, val loss: 0.0050
Epoch 40, train loss: 0.0030, val loss: 0.0013
Epoch 0, train loss: 0.0207, val loss: 0.0393
Epoch 10, train loss: 0.0064, val loss: 0.0203
Epoch 20, train loss: 0.0038, val loss: 0.0165
Epoch 30, train loss: 0.0030, val loss: 0.0050
Epoch 40, train loss: 0.0030, val loss: 0.0013
Epoch 50, train loss: 0.0030, val loss: 0.0015
Epoch 60, train loss: 0.0029, val loss: 0.0020
Epoch 70, train loss: 0.0030, val loss: 0.0013
Inferred coeffs for Cameroon: [ 1.0875778   1.1924683   0.79523665  0.5374299   0.9424727   1.2881025
 -2.8910053  -0.5773223   0.18470898  0.0853616  -1.3692913  -0.00852036
  0.00501913 -4.604352    2.486318   -0.02102363 -1.3521397   0.80612236]
Epoch 0, train loss: 0.0195, val loss: 0.3183
Epoch 10, train loss: 0.0528, val loss: 0.1855
Epoch 20, train loss: 0.0171, val loss: 0.0535
Epoch 30, train loss: 0.0050, val loss: 0.0534
Epoch 40, train loss: 0.0026, val loss: 0.0008
Epoch 0, train loss: 0.0195, val loss: 0.3183
Epoch 10, train loss: 0.0528, val loss: 0.1855
Epoch 20, train loss: 0.0171, val loss: 0.0535
Epoch 30, train loss: 0.0050, val loss: 0.0534
Epoch 40, train loss: 0.0026, val loss: 0.0008
Epoch 50, train loss: 0.0076, val loss: 0.0089
Epoch 60, train loss: 0.0030, val loss: 0.0217
Epoch 70, train loss: 0.0024, val loss: 0.0271
Epoch 0, train loss: 0.0195, val loss: 0.0304
Epoch 10, train loss: 0.0004, val loss: 0.0065
Epoch 20, train loss: 0.0005, val loss: 0.0031
Epoch 30, train loss: 0.0013, val loss: 0.0017
Epoch 40, train loss: 0.0006, val loss: 0.0013
Epoch 0, train loss: 0.0195, val loss: 0.0304
Epoch 10, train loss: 0.0004, val loss: 0.0065
Epoch 20, train loss: 0.0005, val loss: 0.0031
Epoch 30, train loss: 0.0013, val loss: 0.0017
Epoch 40, train loss: 0.0006, val loss: 0.0013
Epoch 50, train loss: 0.0005, val loss: 0.0003
Epoch 60, train loss: 0.0007, val loss: 0.0002
Epoch 70, train loss: 0.0004, val loss: 0.0015
Epoch 80, train loss: 0.0007, val loss: 0.0023
Epoch 90, train loss: 0.0004, val loss: 0.0016
Inferred coeffs for Mali: [ 1.0865794   1.2004901   0.78796405  0.57167476  0.93953305  1.2968243
 -2.9044776  -0.5890084   0.17903587  0.08528908 -1.3634311  -0.00952525
  0.00602406 -4.6095047   2.4915557  -0.01990541 -1.4207902   0.86918724]
Epoch 0, train loss: 0.0184, val loss: 0.4266
Epoch 10, train loss: 0.0537, val loss: 0.1469
Epoch 20, train loss: 0.0363, val loss: 0.0231
Epoch 30, train loss: 0.0219, val loss: 0.1451
Epoch 40, train loss: 0.0090, val loss: 0.0136
Epoch 0, train loss: 0.0184, val loss: 0.4266
Epoch 10, train loss: 0.0537, val loss: 0.1469
Epoch 20, train loss: 0.0363, val loss: 0.0231
Epoch 30, train loss: 0.0219, val loss: 0.1451
Epoch 40, train loss: 0.0090, val loss: 0.0136
Epoch 50, train loss: 0.0139, val loss: 0.0176
Epoch 60, train loss: 0.0116, val loss: 0.0895
Epoch 70, train loss: 0.0085, val loss: 0.0387
Epoch 0, train loss: 0.0184, val loss: 0.0525
Epoch 10, train loss: 0.0060, val loss: 0.0420
Epoch 20, train loss: 0.0055, val loss: 0.0480
Epoch 30, train loss: 0.0027, val loss: 0.0368
Epoch 0, train loss: 0.0184, val loss: 0.0525
Epoch 10, train loss: 0.0060, val loss: 0.0420
Epoch 20, train loss: 0.0055, val loss: 0.0480
Epoch 30, train loss: 0.0027, val loss: 0.0368
Inferred coeffs for Spain: [ 1.0870292   1.191724    0.79499745  0.5356003   0.9414338   1.2882946
 -2.8912866  -0.57654595  0.18648039  0.08442868 -1.3692074  -0.00908161
  0.00558036 -4.490379    2.3701887  -0.02047731 -1.3584185   0.81218183]
Epoch 0, train loss: 0.0226, val loss: 0.3113
Epoch 10, train loss: 0.0503, val loss: 0.1634
Epoch 20, train loss: 0.0277, val loss: 0.1233
Epoch 30, train loss: 0.0204, val loss: 0.0436
Epoch 40, train loss: 0.0033, val loss: 0.0635
Epoch 0, train loss: 0.0226, val loss: 0.3113
Epoch 10, train loss: 0.0503, val loss: 0.1634
Epoch 20, train loss: 0.0277, val loss: 0.1233
Epoch 30, train loss: 0.0204, val loss: 0.0436
Epoch 40, train loss: 0.0033, val loss: 0.0635
Epoch 50, train loss: 0.0113, val loss: 0.0125
Epoch 60, train loss: 0.0050, val loss: 0.0107
Epoch 70, train loss: 0.0031, val loss: 0.0022
Epoch 80, train loss: 0.0031, val loss: 0.0145
Epoch 0, train loss: 0.0226, val loss: 0.0530
Epoch 10, train loss: 0.0063, val loss: 0.0317
Epoch 20, train loss: 0.0040, val loss: 0.0235
Epoch 30, train loss: 0.0032, val loss: 0.0175
Epoch 40, train loss: 0.0031, val loss: 0.0127
Epoch 0, train loss: 0.0226, val loss: 0.0530
Epoch 10, train loss: 0.0063, val loss: 0.0317
Epoch 20, train loss: 0.0040, val loss: 0.0235
Epoch 30, train loss: 0.0032, val loss: 0.0175
Epoch 40, train loss: 0.0031, val loss: 0.0127
Inferred coeffs for Morocco: [ 1.0871671   1.2010738   0.7885562   0.5710605   0.9401192   1.2962308
 -2.9038827  -0.5895901   0.17963783  0.08469375 -1.3628427  -0.00893767
  0.00543647 -4.608798    2.4908407  -0.02049344 -1.4213866   0.86979556]
Epoch 0, train loss: 0.0182, val loss: 0.3153
Epoch 10, train loss: 0.0541, val loss: 0.1830
Epoch 20, train loss: 0.0185, val loss: 0.0514
Epoch 30, train loss: 0.0064, val loss: 0.0553
Epoch 40, train loss: 0.0029, val loss: 0.0251
Epoch 0, train loss: 0.0182, val loss: 0.3153
Epoch 10, train loss: 0.0541, val loss: 0.1830
Epoch 20, train loss: 0.0185, val loss: 0.0514
Epoch 30, train loss: 0.0064, val loss: 0.0553
Epoch 40, train loss: 0.0029, val loss: 0.0251
Epoch 50, train loss: 0.0263, val loss: 0.0398
Epoch 60, train loss: 0.0088, val loss: 0.0179
Epoch 70, train loss: 0.0030, val loss: 0.0476
Epoch 0, train loss: 0.0182, val loss: 0.0328
Epoch 10, train loss: 0.0024, val loss: 0.0016
Epoch 20, train loss: 0.0013, val loss: 0.0100
Epoch 30, train loss: 0.0013, val loss: 0.0044
Epoch 40, train loss: 0.0014, val loss: 0.0069
Epoch 0, train loss: 0.0182, val loss: 0.0328
Epoch 10, train loss: 0.0024, val loss: 0.0016
Epoch 20, train loss: 0.0013, val loss: 0.0100
Epoch 30, train loss: 0.0013, val loss: 0.0044
Epoch 40, train loss: 0.0014, val loss: 0.0069
Inferred coeffs for Guinea: [ 1.0866276   1.2005509   0.7880045   0.5716633   0.9395753   1.2967856
 -2.904447   -0.58907384  0.1790894   0.08523159 -1.3633697  -0.00947721
  0.00597601 -4.6095343   2.4915862  -0.01995355 -1.4209795   0.8693724 ]
Epoch 0, train loss: 0.0159, val loss: 0.3236
Epoch 10, train loss: 0.0563, val loss: 0.1915
Epoch 20, train loss: 0.0208, val loss: 0.0600
Epoch 30, train loss: 0.0087, val loss: 0.0466
Epoch 40, train loss: 0.0161, val loss: 0.0344
Epoch 0, train loss: 0.0159, val loss: 0.3236
Epoch 10, train loss: 0.0563, val loss: 0.1915
Epoch 20, train loss: 0.0208, val loss: 0.0600
Epoch 30, train loss: 0.0087, val loss: 0.0466
Epoch 40, train loss: 0.0161, val loss: 0.0344
Epoch 50, train loss: 0.0064, val loss: 0.0347
Epoch 60, train loss: 0.0024, val loss: 0.0118
Epoch 70, train loss: 0.0205, val loss: 0.0594
Epoch 80, train loss: 0.0038, val loss: 0.0442
Epoch 90, train loss: 0.0141, val loss: 0.0284
Epoch 0, train loss: 0.0159, val loss: 0.0244
Epoch 10, train loss: 0.0010, val loss: 0.0022
Epoch 20, train loss: 0.0008, val loss: 0.0096
Epoch 30, train loss: 0.0008, val loss: 0.0046
Epoch 40, train loss: 0.0007, val loss: 0.0051
Epoch 0, train loss: 0.0159, val loss: 0.0244
Epoch 10, train loss: 0.0010, val loss: 0.0022
Epoch 20, train loss: 0.0008, val loss: 0.0096
Epoch 30, train loss: 0.0008, val loss: 0.0046
Epoch 40, train loss: 0.0007, val loss: 0.0051
Inferred coeffs for Somalia: [ 1.0863835   1.2002999   0.7877651   0.5718821   0.9393318   1.2970241
 -2.9046826  -0.5888202   0.1788507   0.08547532 -1.3636186  -0.00972139
  0.00622019 -4.6095443   2.4915967  -0.01970947 -1.4206877   0.8690856 ]
Epoch 0, train loss: 0.0167, val loss: 0.3415
Epoch 10, train loss: 0.0563, val loss: 0.1915
Epoch 20, train loss: 0.0173, val loss: 0.0485
Epoch 30, train loss: 0.0038, val loss: 0.0643
Epoch 40, train loss: 0.0010, val loss: 0.0102
Epoch 0, train loss: 0.0167, val loss: 0.3415
Epoch 10, train loss: 0.0563, val loss: 0.1915
Epoch 20, train loss: 0.0173, val loss: 0.0485
Epoch 30, train loss: 0.0038, val loss: 0.0643
Epoch 40, train loss: 0.0010, val loss: 0.0102
Epoch 50, train loss: 0.0135, val loss: 0.0225
Epoch 60, train loss: 0.0101, val loss: 0.0378
Epoch 70, train loss: 0.0203, val loss: 0.0938
Epoch 0, train loss: 0.0167, val loss: 0.0249
Epoch 10, train loss: 0.0011, val loss: 0.0043
Epoch 20, train loss: 0.0014, val loss: 0.0054
Epoch 30, train loss: 0.0013, val loss: 0.0078
Epoch 40, train loss: 0.0012, val loss: 0.0042
Epoch 0, train loss: 0.0167, val loss: 0.0249
Epoch 10, train loss: 0.0011, val loss: 0.0043
Epoch 20, train loss: 0.0014, val loss: 0.0054
Epoch 30, train loss: 0.0013, val loss: 0.0078
Epoch 40, train loss: 0.0012, val loss: 0.0042
Inferred coeffs for Egypt: [ 1.0863987   1.2003136   0.78778213  0.5718582   0.9393472   1.2970067
 -2.904664   -0.58883303  0.17886907  0.08545882 -1.3636038  -0.00970593
  0.00620473 -4.608907    2.4909496  -0.01972507 -1.4206945   0.86909646]
Epoch 0, train loss: 0.0208, val loss: 0.3219
Epoch 10, train loss: 0.0516, val loss: 0.1863
Epoch 20, train loss: 0.0154, val loss: 0.0525
Epoch 30, train loss: 0.0031, val loss: 0.0551
Epoch 40, train loss: 0.0007, val loss: 0.0101
Epoch 0, train loss: 0.0208, val loss: 0.3219
Epoch 10, train loss: 0.0516, val loss: 0.1863
Epoch 20, train loss: 0.0154, val loss: 0.0525
Epoch 30, train loss: 0.0031, val loss: 0.0551
Epoch 40, train loss: 0.0007, val loss: 0.0101
Epoch 50, train loss: 0.0007, val loss: 0.0083
Epoch 60, train loss: 0.0161, val loss: 0.0638
Epoch 70, train loss: 0.0095, val loss: 0.0108
Epoch 0, train loss: 0.0208, val loss: 0.0298
Epoch 10, train loss: 0.0051, val loss: 0.0053
Epoch 20, train loss: 0.0020, val loss: 0.0061
Epoch 30, train loss: 0.0016, val loss: 0.0054
Epoch 40, train loss: 0.0006, val loss: 0.0075
Epoch 0, train loss: 0.0208, val loss: 0.0298
Epoch 10, train loss: 0.0051, val loss: 0.0053
Epoch 20, train loss: 0.0020, val loss: 0.0061
Epoch 30, train loss: 0.0016, val loss: 0.0054
Epoch 40, train loss: 0.0006, val loss: 0.0075
Epoch 50, train loss: 0.0006, val loss: 0.0048
Inferred coeffs for Albania: [ 1.086554    1.2004336   0.78796154  0.5715761   0.93950945  1.296822
 -2.9044616  -0.58894044  0.17904438  0.08530585 -1.3634735  -0.00955023
  0.00604903 -4.609344    2.4913914  -0.01988159 -1.4205736   0.86901   ]
Epoch 0, train loss: 0.0233, val loss: 0.3184
Epoch 10, train loss: 0.0492, val loss: 0.1804
Epoch 20, train loss: 0.0243, val loss: 0.1186
Epoch 30, train loss: 0.0132, val loss: 0.0017
Epoch 40, train loss: 0.0084, val loss: 0.0247
Epoch 0, train loss: 0.0233, val loss: 0.3184
Epoch 10, train loss: 0.0492, val loss: 0.1804
Epoch 20, train loss: 0.0243, val loss: 0.1186
Epoch 30, train loss: 0.0132, val loss: 0.0017
Epoch 40, train loss: 0.0084, val loss: 0.0247
Epoch 50, train loss: 0.0031, val loss: 0.0427
Epoch 60, train loss: 0.0160, val loss: 0.0402
Epoch 0, train loss: 0.0233, val loss: 0.0358
Epoch 10, train loss: 0.0065, val loss: 0.0194
Epoch 20, train loss: 0.0013, val loss: 0.0003
Epoch 30, train loss: 0.0012, val loss: 0.0010
Epoch 40, train loss: 0.0019, val loss: 0.0043
Epoch 0, train loss: 0.0233, val loss: 0.0358
Epoch 10, train loss: 0.0065, val loss: 0.0194
Epoch 20, train loss: 0.0013, val loss: 0.0003
Epoch 30, train loss: 0.0012, val loss: 0.0010
Epoch 40, train loss: 0.0019, val loss: 0.0043
Epoch 50, train loss: 0.0012, val loss: 0.0099
Inferred coeffs for Bulgaria: [ 1.0867182   1.2005943   0.78812784  0.5713991   0.93967575  1.2966542
 -2.9042926  -0.5891003   0.17920902  0.08514266 -1.363312   -0.00938643
  0.00588523 -4.6091747   2.4912205  -0.02004531 -1.420718    0.8691531 ]
Epoch 0, train loss: 0.0221, val loss: 0.3208
Epoch 10, train loss: 0.0505, val loss: 0.1804
Epoch 20, train loss: 0.0154, val loss: 0.0560
Epoch 30, train loss: 0.0129, val loss: 0.0282
Epoch 40, train loss: 0.0260, val loss: 0.0782
Epoch 0, train loss: 0.0221, val loss: 0.3208
Epoch 10, train loss: 0.0505, val loss: 0.1804
Epoch 20, train loss: 0.0154, val loss: 0.0560
Epoch 30, train loss: 0.0129, val loss: 0.0282
Epoch 40, train loss: 0.0260, val loss: 0.0782
Epoch 50, train loss: 0.0112, val loss: 0.0048
Epoch 60, train loss: 0.0063, val loss: 0.0456
Epoch 70, train loss: 0.0275, val loss: 0.0562
Epoch 80, train loss: 0.0030, val loss: 0.0546
Epoch 90, train loss: 0.0109, val loss: 0.0248
Epoch 0, train loss: 0.0221, val loss: 0.0358
Epoch 10, train loss: 0.0068, val loss: 0.0210
Epoch 20, train loss: 0.0028, val loss: 0.0083
Epoch 30, train loss: 0.0024, val loss: 0.0011
Epoch 40, train loss: 0.0012, val loss: 0.0025
Epoch 0, train loss: 0.0221, val loss: 0.0358
Epoch 10, train loss: 0.0068, val loss: 0.0210
Epoch 20, train loss: 0.0028, val loss: 0.0083
Epoch 30, train loss: 0.0024, val loss: 0.0011
Epoch 40, train loss: 0.0012, val loss: 0.0025
Epoch 50, train loss: 0.0008, val loss: 0.0055
Epoch 60, train loss: 0.0009, val loss: 0.0025
Epoch 70, train loss: 0.0008, val loss: 0.0026
Inferred coeffs for Cyprus: [ 1.0878379   1.1887088   0.79840827  0.52136683  0.9436723   1.2841572
 -2.8849435  -0.5714556   0.18730891  0.0855572  -1.3723099  -0.00825177
  0.00475051 -4.5711684   2.452567   -0.02135143 -1.3163254   0.77380025]
Epoch 0, train loss: 0.0205, val loss: 0.3168
Epoch 10, train loss: 0.0524, val loss: 0.1712
Epoch 20, train loss: 0.0245, val loss: 0.0949
Epoch 30, train loss: 0.0211, val loss: 0.0280
Epoch 40, train loss: 0.0140, val loss: 0.0111
Epoch 0, train loss: 0.0205, val loss: 0.3168
Epoch 10, train loss: 0.0524, val loss: 0.1712
Epoch 20, train loss: 0.0245, val loss: 0.0949
Epoch 30, train loss: 0.0211, val loss: 0.0280
Epoch 40, train loss: 0.0140, val loss: 0.0111
Epoch 50, train loss: 0.0162, val loss: 0.0116
Epoch 60, train loss: 0.0032, val loss: 0.0090
Epoch 70, train loss: 0.0059, val loss: 0.0120
Epoch 80, train loss: 0.0057, val loss: 0.0021
Epoch 90, train loss: 0.0037, val loss: 0.0329
Epoch 0, train loss: 0.0205, val loss: 0.0451
Epoch 10, train loss: 0.0066, val loss: 0.0291
Epoch 20, train loss: 0.0039, val loss: 0.0254
Epoch 30, train loss: 0.0028, val loss: 0.0171
Epoch 40, train loss: 0.0029, val loss: 0.0088
Epoch 0, train loss: 0.0205, val loss: 0.0451
Epoch 10, train loss: 0.0066, val loss: 0.0291
Epoch 20, train loss: 0.0039, val loss: 0.0254
Epoch 30, train loss: 0.0028, val loss: 0.0171
Epoch 40, train loss: 0.0029, val loss: 0.0088
Inferred coeffs for Croatia: [ 1.087731    1.1916862   0.79606986  0.5335357   0.9427608   1.2871122
 -2.889539   -0.5760926   0.18561868  0.08516271 -1.3698057  -0.00834657
  0.00484532 -4.567502    2.4488485  -0.02125738 -1.3435115   0.79922247]
Epoch 0, train loss: 0.0279, val loss: 0.3317
Epoch 10, train loss: 0.0458, val loss: 0.1542
Epoch 20, train loss: 0.0207, val loss: 0.0091
Epoch 30, train loss: 0.0022, val loss: 0.0012
Epoch 40, train loss: 0.0187, val loss: 0.0221
Epoch 0, train loss: 0.0279, val loss: 0.3317
Epoch 10, train loss: 0.0458, val loss: 0.1542
Epoch 20, train loss: 0.0207, val loss: 0.0091
Epoch 30, train loss: 0.0022, val loss: 0.0012
Epoch 40, train loss: 0.0187, val loss: 0.0221
Epoch 50, train loss: 0.0035, val loss: 0.0048
Epoch 60, train loss: 0.0060, val loss: 0.0359
Epoch 0, train loss: 0.0279, val loss: 0.0613
Epoch 10, train loss: 0.0071, val loss: 0.0295
Epoch 20, train loss: 0.0038, val loss: 0.0189
Epoch 30, train loss: 0.0031, val loss: 0.0120
Epoch 40, train loss: 0.0023, val loss: 0.0015
Epoch 0, train loss: 0.0279, val loss: 0.0613
Epoch 10, train loss: 0.0071, val loss: 0.0295
Epoch 20, train loss: 0.0038, val loss: 0.0189
Epoch 30, train loss: 0.0031, val loss: 0.0120
Epoch 40, train loss: 0.0023, val loss: 0.0015
Epoch 50, train loss: 0.0022, val loss: 0.0026
Epoch 60, train loss: 0.0022, val loss: 0.0031
Epoch 70, train loss: 0.0022, val loss: 0.0032
Epoch 80, train loss: 0.0021, val loss: 0.0017
Epoch 90, train loss: 0.0021, val loss: 0.0025
Inferred coeffs for Greece: [ 1.0875534   1.1950132   0.7934927   0.54639983  0.941862    1.2901702
 -2.8945096  -0.58104706  0.18403217  0.08455072 -1.367012   -0.00854017
  0.00503894 -4.5482697   2.4297009  -0.0209994  -1.3752211   0.8279974 ]
Epoch 0, train loss: 0.0225, val loss: 0.3044
Epoch 10, train loss: 0.0500, val loss: 0.1659
Epoch 20, train loss: 0.0290, val loss: 0.1303
Epoch 30, train loss: 0.0062, val loss: 0.0723
Epoch 40, train loss: 0.0037, val loss: 0.0462
Epoch 0, train loss: 0.0225, val loss: 0.3044
Epoch 10, train loss: 0.0500, val loss: 0.1659
Epoch 20, train loss: 0.0290, val loss: 0.1303
Epoch 30, train loss: 0.0062, val loss: 0.0723
Epoch 40, train loss: 0.0037, val loss: 0.0462
Epoch 50, train loss: 0.0155, val loss: 0.0273
Epoch 0, train loss: 0.0225, val loss: 0.0503
Epoch 10, train loss: 0.0068, val loss: 0.0325
Epoch 20, train loss: 0.0031, val loss: 0.0221
Epoch 30, train loss: 0.0030, val loss: 0.0196
Epoch 40, train loss: 0.0027, val loss: 0.0150
Epoch 0, train loss: 0.0225, val loss: 0.0503
Epoch 10, train loss: 0.0068, val loss: 0.0325
Epoch 20, train loss: 0.0031, val loss: 0.0221
Epoch 30, train loss: 0.0030, val loss: 0.0196
Epoch 40, train loss: 0.0027, val loss: 0.0150
Epoch 50, train loss: 0.0019, val loss: 0.0065
Inferred coeffs for Hungary: [ 1.0871251   1.2009963   0.78853786  0.5709793   0.94008476  1.296244
 -2.903878   -0.58949995  0.17961146  0.08474123 -1.3629112  -0.00897984
  0.00547864 -4.609116    2.4911618  -0.02045172 -1.4210614   0.86949575]
Epoch 0, train loss: 0.0343, val loss: 0.2066
Epoch 10, train loss: 0.0458, val loss: 0.0711
Epoch 20, train loss: 0.0161, val loss: 0.2218
Epoch 30, train loss: 0.0220, val loss: 0.2302
Epoch 0, train loss: 0.0343, val loss: 0.2066
Epoch 10, train loss: 0.0458, val loss: 0.0711
Epoch 20, train loss: 0.0161, val loss: 0.2218
Epoch 30, train loss: 0.0220, val loss: 0.2302
Epoch 0, train loss: 0.0343, val loss: 0.2466
Epoch 10, train loss: 0.0151, val loss: 0.1857
Epoch 20, train loss: 0.0145, val loss: 0.1800
Epoch 30, train loss: 0.0145, val loss: 0.1968
Epoch 0, train loss: 0.0343, val loss: 0.2466
Epoch 10, train loss: 0.0151, val loss: 0.1857
Epoch 20, train loss: 0.0145, val loss: 0.1800
Epoch 30, train loss: 0.0145, val loss: 0.1968
Inferred coeffs for Italy: [ 1.0907195e+00  1.2018955e+00  7.9408890e-01  5.5669069e-01
  9.4422567e-01  1.2901628e+00 -2.8963301e+00 -5.8934504e-01
  1.8528788e-01  8.0946386e-02 -1.3610594e+00 -5.3861081e-03
  1.8848911e-03 -4.5649199e+00  2.4470477e+00 -2.4079410e-02
 -1.4073606e+00  8.5744607e-01]
Epoch 0, train loss: 0.0294, val loss: 0.3002
Epoch 10, train loss: 0.0429, val loss: 0.1664
Epoch 20, train loss: 0.0288, val loss: 0.1608
Epoch 30, train loss: 0.0027, val loss: 0.0615
Epoch 40, train loss: 0.0208, val loss: 0.0386
Epoch 0, train loss: 0.0294, val loss: 0.3002
Epoch 10, train loss: 0.0429, val loss: 0.1664
Epoch 20, train loss: 0.0288, val loss: 0.1608
Epoch 30, train loss: 0.0027, val loss: 0.0615
Epoch 40, train loss: 0.0208, val loss: 0.0386
Epoch 0, train loss: 0.0294, val loss: 0.0496
Epoch 10, train loss: 0.0056, val loss: 0.0050
Epoch 20, train loss: 0.0031, val loss: 0.0052
Epoch 30, train loss: 0.0020, val loss: 0.0121
Epoch 40, train loss: 0.0017, val loss: 0.0151
Epoch 0, train loss: 0.0294, val loss: 0.0496
Epoch 10, train loss: 0.0056, val loss: 0.0050
Epoch 20, train loss: 0.0031, val loss: 0.0052
Epoch 30, train loss: 0.0020, val loss: 0.0121
Epoch 40, train loss: 0.0017, val loss: 0.0151
Inferred coeffs for Slovenia: [ 1.0871246   1.2010363   0.78851074  0.57111615  0.9400752   1.296276
 -2.903933   -0.58955497  0.17959899  0.08473119 -1.362879   -0.00898004
  0.00547884 -4.6094384   2.4914887  -0.02045117 -1.4214088   0.8698171 ]
Epoch 0, train loss: 0.0273, val loss: 0.2127
Epoch 10, train loss: 0.0399, val loss: 0.0170
Epoch 20, train loss: 0.0187, val loss: 0.1022
Epoch 30, train loss: 0.0134, val loss: 0.1466
Epoch 0, train loss: 0.0273, val loss: 0.2127
Epoch 10, train loss: 0.0399, val loss: 0.0170
Epoch 20, train loss: 0.0187, val loss: 0.1022
Epoch 30, train loss: 0.0134, val loss: 0.1466
Epoch 0, train loss: 0.0273, val loss: 0.1443
Epoch 10, train loss: 0.0084, val loss: 0.1166
Epoch 20, train loss: 0.0093, val loss: 0.0853
Epoch 30, train loss: 0.0084, val loss: 0.0993
Epoch 0, train loss: 0.0273, val loss: 0.1443
Epoch 10, train loss: 0.0084, val loss: 0.1166
Epoch 20, train loss: 0.0093, val loss: 0.0853
Epoch 30, train loss: 0.0084, val loss: 0.0993
Inferred coeffs for Israel: [ 1.0900595e+00  1.2017591e+00  7.9300129e-01  5.5979347e-01
  9.4348562e-01  1.2914072e+00 -2.8977880e+00 -5.8939946e-01
  1.8381321e-01  8.1939213e-02 -1.3615432e+00 -6.0414425e-03
  2.5402235e-03 -4.6011105e+00  2.4831357e+00 -2.3417844e-02
 -1.4086158e+00  8.5850281e-01]
Epoch 0, train loss: 0.0853, val loss: 0.0443
Epoch 10, train loss: 0.0298, val loss: 0.0594
Epoch 20, train loss: 0.0297, val loss: 0.0144
Epoch 30, train loss: 0.0292, val loss: 0.0208
Epoch 40, train loss: 0.0287, val loss: 0.0384
Epoch 0, train loss: 0.0853, val loss: 0.0443
Epoch 10, train loss: 0.0298, val loss: 0.0594
Epoch 20, train loss: 0.0297, val loss: 0.0144
Epoch 30, train loss: 0.0292, val loss: 0.0208
Epoch 40, train loss: 0.0287, val loss: 0.0384
Epoch 50, train loss: 0.0288, val loss: 0.0191
Epoch 0, train loss: 0.0853, val loss: 0.3394
Epoch 10, train loss: 0.0300, val loss: 0.0320
Epoch 20, train loss: 0.0298, val loss: 0.0544
Epoch 30, train loss: 0.0307, val loss: 0.0613
Epoch 40, train loss: 0.0299, val loss: 0.0144
Epoch 0, train loss: 0.0853, val loss: 0.3394
Epoch 10, train loss: 0.0300, val loss: 0.0320
Epoch 20, train loss: 0.0298, val loss: 0.0544
Epoch 30, train loss: 0.0307, val loss: 0.0613
Epoch 40, train loss: 0.0299, val loss: 0.0144
Epoch 50, train loss: 0.0295, val loss: 0.0323
Epoch 60, train loss: 0.0293, val loss: 0.0171
Epoch 70, train loss: 0.0292, val loss: 0.0196
Inferred coeffs for Austria: [ 1.0938685e+00  1.2079878e+00  7.9505080e-01  5.6559467e-01
  9.4683731e-01  1.2898440e+00 -2.8974917e+00 -5.9657866e-01
  1.8560258e-01  7.8418992e-02 -1.3562274e+00 -2.2388385e-03
 -1.2623563e-03 -4.6049724e+00  2.4870732e+00 -2.7174938e-02
 -1.4281077e+00  8.7601966e-01]
Epoch 0, train loss: 0.1040, val loss: 0.0344
Epoch 10, train loss: 0.0423, val loss: 0.0184
Epoch 20, train loss: 0.0585, val loss: 0.2208
Epoch 30, train loss: 0.0442, val loss: 0.1754
Epoch 40, train loss: 0.0371, val loss: 0.1142
Epoch 0, train loss: 0.1040, val loss: 0.0344
Epoch 10, train loss: 0.0423, val loss: 0.0184
Epoch 20, train loss: 0.0585, val loss: 0.2208
Epoch 30, train loss: 0.0442, val loss: 0.1754
Epoch 40, train loss: 0.0371, val loss: 0.1142
Epoch 50, train loss: 0.0393, val loss: 0.1286
Epoch 60, train loss: 0.0328, val loss: 0.0442
Epoch 70, train loss: 0.0302, val loss: 0.0191
Epoch 80, train loss: 0.0300, val loss: 0.0216
Epoch 90, train loss: 0.0295, val loss: 0.0101
Epoch 0, train loss: 0.1040, val loss: 0.4107
Epoch 10, train loss: 0.0316, val loss: 0.0149
Epoch 20, train loss: 0.0294, val loss: 0.0282
Epoch 30, train loss: 0.0314, val loss: 0.0446
Epoch 40, train loss: 0.0301, val loss: 0.0256
Epoch 0, train loss: 0.1040, val loss: 0.4107
Epoch 10, train loss: 0.0316, val loss: 0.0149
Epoch 20, train loss: 0.0294, val loss: 0.0282
Epoch 30, train loss: 0.0314, val loss: 0.0446
Epoch 40, train loss: 0.0301, val loss: 0.0256
Epoch 50, train loss: 0.0295, val loss: 0.0130
Epoch 60, train loss: 0.0293, val loss: 0.0108
Epoch 70, train loss: 0.0292, val loss: 0.0077
Epoch 80, train loss: 0.0291, val loss: 0.0097
Epoch 90, train loss: 0.0291, val loss: 0.0045
Inferred coeffs for Portugal: [ 1.0999418e+00  1.2107439e+00  8.0248970e-01  5.5649239e-01
  9.5608801e-01  1.2827436e+00 -2.8855040e+00 -5.9837914e-01
  1.8032080e-01  8.1512146e-02 -1.3569340e+00  3.7538128e-03
 -7.2549586e-03 -4.5120869e+00  2.3946157e+00 -3.2805681e-02
 -1.3877621e+00  8.2879865e-01]
Epoch 0, train loss: 0.0222, val loss: 0.3064
Epoch 10, train loss: 0.0502, val loss: 0.1727
Epoch 20, train loss: 0.0143, val loss: 0.0401
Epoch 30, train loss: 0.0075, val loss: 0.0103
Epoch 40, train loss: 0.0116, val loss: 0.0345
Epoch 0, train loss: 0.0222, val loss: 0.3064
Epoch 10, train loss: 0.0502, val loss: 0.1727
Epoch 20, train loss: 0.0143, val loss: 0.0401
Epoch 30, train loss: 0.0075, val loss: 0.0103
Epoch 40, train loss: 0.0116, val loss: 0.0345
Epoch 50, train loss: 0.0129, val loss: 0.0286
Epoch 0, train loss: 0.0222, val loss: 0.0433
Epoch 10, train loss: 0.0072, val loss: 0.0275
Epoch 20, train loss: 0.0024, val loss: 0.0139
Epoch 30, train loss: 0.0024, val loss: 0.0115
Epoch 40, train loss: 0.0020, val loss: 0.0031
Epoch 0, train loss: 0.0222, val loss: 0.0433
Epoch 10, train loss: 0.0072, val loss: 0.0275
Epoch 20, train loss: 0.0024, val loss: 0.0139
Epoch 30, train loss: 0.0024, val loss: 0.0115
Epoch 40, train loss: 0.0020, val loss: 0.0031
Epoch 50, train loss: 0.0019, val loss: 0.0016
Epoch 60, train loss: 0.0021, val loss: 0.0051
Epoch 70, train loss: 0.0017, val loss: 0.0030
Epoch 80, train loss: 0.0019, val loss: 0.0053
Epoch 90, train loss: 0.0017, val loss: 0.0014
Inferred coeffs for Bosnia and Herzegovina: [ 1.0869645   1.2008226   0.78838307  0.5711212   0.93993586  1.2963973
 -2.9040208  -0.58932143  0.17941988  0.08492848 -1.3630943  -0.0091417
  0.00564051 -4.6093984   2.4914505  -0.02028902 -1.4206749   0.8690977 ]
Epoch 0, train loss: 0.0294, val loss: 0.2497
Epoch 10, train loss: 0.0435, val loss: 0.1048
Epoch 20, train loss: 0.0191, val loss: 0.0375
Epoch 30, train loss: 0.0129, val loss: 0.0647
Epoch 40, train loss: 0.0087, val loss: 0.0414
Epoch 0, train loss: 0.0294, val loss: 0.2497
Epoch 10, train loss: 0.0435, val loss: 0.1048
Epoch 20, train loss: 0.0191, val loss: 0.0375
Epoch 30, train loss: 0.0129, val loss: 0.0647
Epoch 40, train loss: 0.0087, val loss: 0.0414
Epoch 50, train loss: 0.0084, val loss: 0.0648
Epoch 0, train loss: 0.0294, val loss: 0.1116
Epoch 10, train loss: 0.0078, val loss: 0.0712
Epoch 20, train loss: 0.0083, val loss: 0.0287
Epoch 30, train loss: 0.0082, val loss: 0.0649
Epoch 0, train loss: 0.0294, val loss: 0.1116
Epoch 10, train loss: 0.0078, val loss: 0.0712
Epoch 20, train loss: 0.0083, val loss: 0.0287
Epoch 30, train loss: 0.0082, val loss: 0.0649
Inferred coeffs for Romania: [ 1.0892720e+00  1.1973133e+00  7.9476035e-01  5.4716712e-01
  9.4348752e-01  1.2890474e+00 -2.8935807e+00 -5.8354604e-01
  1.8502696e-01  8.3063059e-02 -1.3650228e+00 -6.8211961e-03
  3.3199664e-03 -4.5844870e+00  2.4662724e+00 -2.2700271e-02
 -1.3800645e+00  8.3242077e-01]
Epoch 0, train loss: 0.1433, val loss: 0.1851
Epoch 10, train loss: 0.0668, val loss: 0.1342
Epoch 20, train loss: 0.0691, val loss: 0.2778
Epoch 30, train loss: 0.0517, val loss: 0.1801
Epoch 40, train loss: 0.0429, val loss: 0.0554
Epoch 0, train loss: 0.1433, val loss: 0.1851
Epoch 10, train loss: 0.0668, val loss: 0.1342
Epoch 20, train loss: 0.0691, val loss: 0.2778
Epoch 30, train loss: 0.0517, val loss: 0.1801
Epoch 40, train loss: 0.0429, val loss: 0.0554
Epoch 50, train loss: 0.0424, val loss: 0.0212
Epoch 60, train loss: 0.0428, val loss: 0.0450
Epoch 70, train loss: 0.0431, val loss: 0.0260
Epoch 80, train loss: 0.0398, val loss: 0.0272
Epoch 90, train loss: 0.0392, val loss: 0.0700
Epoch 0, train loss: 0.1433, val loss: 0.5671
Epoch 10, train loss: 0.0580, val loss: 0.1516
Epoch 20, train loss: 0.0491, val loss: 0.1027
Epoch 30, train loss: 0.0429, val loss: 0.0346
Epoch 40, train loss: 0.0390, val loss: 0.0642
Epoch 0, train loss: 0.1433, val loss: 0.5671
Epoch 10, train loss: 0.0580, val loss: 0.1516
Epoch 20, train loss: 0.0491, val loss: 0.1027
Epoch 30, train loss: 0.0429, val loss: 0.0346
Epoch 40, train loss: 0.0390, val loss: 0.0642
Epoch 50, train loss: 0.0395, val loss: 0.0267
Inferred coeffs for Switzerland: [ 1.0981517e+00  1.2121283e+00  7.9948753e-01  5.6036204e-01
  9.5113420e-01  1.2853097e+00 -2.8929548e+00 -6.0067064e-01
  1.9042993e-01  7.3807888e-02 -1.3518603e+00  2.0463720e-03
 -5.5475691e-03 -4.6043396e+00  2.4864848e+00 -3.1473011e-02
 -1.4326038e+00  8.8088715e-01]
Epoch 0, train loss: 0.5601, val loss: 1.9313
Epoch 10, train loss: 0.1854, val loss: 0.0655
Epoch 20, train loss: 0.1276, val loss: 0.2605
Epoch 30, train loss: 0.1218, val loss: 0.3455
Epoch 0, train loss: 0.5601, val loss: 1.9313
Epoch 10, train loss: 0.1854, val loss: 0.0655
Epoch 20, train loss: 0.1276, val loss: 0.2605
Epoch 30, train loss: 0.1218, val loss: 0.3455
Epoch 0, train loss: 0.5601, val loss: 2.3295
Epoch 10, train loss: 0.4453, val loss: 1.8781
Epoch 20, train loss: 0.3290, val loss: 1.2812
Epoch 30, train loss: 0.2126, val loss: 0.7389
Epoch 40, train loss: 0.1320, val loss: 0.3617
Epoch 0, train loss: 0.5601, val loss: 2.3295
Epoch 10, train loss: 0.4453, val loss: 1.8781
Epoch 20, train loss: 0.3290, val loss: 1.2812
Epoch 30, train loss: 0.2126, val loss: 0.7389
Epoch 40, train loss: 0.1320, val loss: 0.3617
Epoch 50, train loss: 0.1179, val loss: 0.1621
Epoch 60, train loss: 0.1211, val loss: 0.1438
Epoch 70, train loss: 0.1159, val loss: 0.2076
Epoch 80, train loss: 0.1158, val loss: 0.2447
Inferred coeffs for Turkey: [ 1.1387975   1.2504444   0.8426912   0.50511223  0.9951704   1.2400603
 -2.843194   -0.63907605  0.23317932  0.03206936 -1.3113018   0.04270343
 -0.04620667 -4.6022234   2.5107892  -0.07227143 -1.4578017   0.91359663]
Epoch 0, train loss: 0.0271, val loss: 0.2785
Epoch 10, train loss: 0.0453, val loss: 0.1440
Epoch 20, train loss: 0.0257, val loss: 0.1161
Epoch 30, train loss: 0.0177, val loss: 0.0434
Epoch 40, train loss: 0.0104, val loss: 0.0700
Epoch 0, train loss: 0.0271, val loss: 0.2785
Epoch 10, train loss: 0.0453, val loss: 0.1440
Epoch 20, train loss: 0.0257, val loss: 0.1161
Epoch 30, train loss: 0.0177, val loss: 0.0434
Epoch 40, train loss: 0.0104, val loss: 0.0700
Epoch 0, train loss: 0.0271, val loss: 0.0720
Epoch 10, train loss: 0.0059, val loss: 0.0396
Epoch 20, train loss: 0.0044, val loss: 0.0134
Epoch 30, train loss: 0.0042, val loss: 0.0047
Epoch 40, train loss: 0.0045, val loss: 0.0174
Epoch 0, train loss: 0.0271, val loss: 0.0720
Epoch 10, train loss: 0.0059, val loss: 0.0396
Epoch 20, train loss: 0.0044, val loss: 0.0134
Epoch 30, train loss: 0.0042, val loss: 0.0047
Epoch 40, train loss: 0.0045, val loss: 0.0174
Inferred coeffs for Moldova: [ 1.0880052e+00  1.1985196e+00  7.9176617e-01  5.5764323e-01
  9.4173306e-01  1.2924352e+00 -2.8982952e+00 -5.8576840e-01
  1.8234453e-01  8.4129125e-02 -1.3644539e+00 -8.0922749e-03
  4.5910594e-03 -4.6054659e+00  2.4874828e+00 -2.1391764e-02
 -1.3974665e+00  8.4809887e-01]
Epoch 0, train loss: 0.0369, val loss: 0.2302
Epoch 10, train loss: 0.0297, val loss: 0.0086
Epoch 20, train loss: 0.0173, val loss: 0.0857
Epoch 30, train loss: 0.0131, val loss: 0.0287
Epoch 40, train loss: 0.0081, val loss: 0.0216
Epoch 0, train loss: 0.0369, val loss: 0.2302
Epoch 10, train loss: 0.0297, val loss: 0.0086
Epoch 20, train loss: 0.0173, val loss: 0.0857
Epoch 30, train loss: 0.0131, val loss: 0.0287
Epoch 40, train loss: 0.0081, val loss: 0.0216
Epoch 50, train loss: 0.0081, val loss: 0.0499
Epoch 0, train loss: 0.0369, val loss: 0.1271
Epoch 10, train loss: 0.0082, val loss: 0.0387
Epoch 20, train loss: 0.0080, val loss: 0.0297
Epoch 30, train loss: 0.0080, val loss: 0.0414
Epoch 0, train loss: 0.0369, val loss: 0.1271
Epoch 10, train loss: 0.0082, val loss: 0.0387
Epoch 20, train loss: 0.0080, val loss: 0.0297
Epoch 30, train loss: 0.0080, val loss: 0.0414
Inferred coeffs for Serbia: [ 1.0895376e+00  1.1989292e+00  7.9412293e-01  5.5164969e-01
  9.4362116e-01  1.2898008e+00 -2.8950551e+00 -5.8570927e-01
  1.8453358e-01  8.2656898e-02 -1.3637310e+00 -6.5584481e-03
  3.0572261e-03 -4.5944042e+00  2.4763825e+00 -2.2941722e-02
 -1.3906761e+00  8.4226948e-01]
Epoch 0, train loss: 0.0224, val loss: 0.3110
Epoch 10, train loss: 0.0499, val loss: 0.1783
Epoch 20, train loss: 0.0143, val loss: 0.0463
Epoch 30, train loss: 0.0022, val loss: 0.0605
Epoch 40, train loss: 0.0008, val loss: 0.0503
Epoch 0, train loss: 0.0224, val loss: 0.3110
Epoch 10, train loss: 0.0499, val loss: 0.1783
Epoch 20, train loss: 0.0143, val loss: 0.0463
Epoch 30, train loss: 0.0022, val loss: 0.0605
Epoch 40, train loss: 0.0008, val loss: 0.0503
Epoch 50, train loss: 0.0123, val loss: 0.0545
Epoch 60, train loss: 0.0088, val loss: 0.0004
Epoch 70, train loss: 0.0062, val loss: 0.0318
Epoch 80, train loss: 0.0038, val loss: 0.0048
Epoch 90, train loss: 0.0069, val loss: 0.0068
Epoch 0, train loss: 0.0224, val loss: 0.0376
Epoch 10, train loss: 0.0066, val loss: 0.0244
Epoch 20, train loss: 0.0013, val loss: 0.0063
Epoch 30, train loss: 0.0013, val loss: 0.0064
Epoch 40, train loss: 0.0015, val loss: 0.0005
Epoch 0, train loss: 0.0224, val loss: 0.0376
Epoch 10, train loss: 0.0066, val loss: 0.0244
Epoch 20, train loss: 0.0013, val loss: 0.0063
Epoch 30, train loss: 0.0013, val loss: 0.0064
Epoch 40, train loss: 0.0015, val loss: 0.0005
Epoch 50, train loss: 0.0006, val loss: 0.0016
Inferred coeffs for Slovakia: [ 1.087584    1.1921326   0.79548323  0.53612596  0.94254005  1.2878034
 -2.89053    -0.5768145   0.18490736  0.08539932 -1.3695645  -0.00849912
  0.00499788 -4.6052885   2.4872687  -0.0210801  -1.3481022   0.8030718 ]
Epoch 0, train loss: 0.0262, val loss: 0.2784
Epoch 10, train loss: 0.0463, val loss: 0.1414
Epoch 20, train loss: 0.0306, val loss: 0.0587
Epoch 30, train loss: 0.0177, val loss: 0.0254
Epoch 40, train loss: 0.0101, val loss: 0.0237
Epoch 0, train loss: 0.0262, val loss: 0.2784
Epoch 10, train loss: 0.0463, val loss: 0.1414
Epoch 20, train loss: 0.0306, val loss: 0.0587
Epoch 30, train loss: 0.0177, val loss: 0.0254
Epoch 40, train loss: 0.0101, val loss: 0.0237
Epoch 50, train loss: 0.0059, val loss: 0.0317
Epoch 0, train loss: 0.0262, val loss: 0.0747
Epoch 10, train loss: 0.0072, val loss: 0.0464
Epoch 20, train loss: 0.0073, val loss: 0.0011
Epoch 30, train loss: 0.0058, val loss: 0.0176
Epoch 40, train loss: 0.0057, val loss: 0.0215
Epoch 0, train loss: 0.0262, val loss: 0.0747
Epoch 10, train loss: 0.0072, val loss: 0.0464
Epoch 20, train loss: 0.0073, val loss: 0.0011
Epoch 30, train loss: 0.0058, val loss: 0.0176
Epoch 40, train loss: 0.0057, val loss: 0.0215
Epoch 50, train loss: 0.0056, val loss: 0.0128
Inferred coeffs for Dominican Republic: [ 1.0877944   1.2016772   0.7891989   0.570355    0.9407551   1.2955842
 -2.9032228  -0.59018457  0.1802647   0.0840775  -1.3622372  -0.00831064
  0.00480944 -4.6091857   2.4912338  -0.02112042 -1.4217958   0.87021446]
Epoch 0, train loss: 0.0171, val loss: 0.3260
Epoch 10, train loss: 0.0553, val loss: 0.1922
Epoch 20, train loss: 0.0194, val loss: 0.0596
Epoch 30, train loss: 0.0072, val loss: 0.0477
Epoch 40, train loss: 0.0047, val loss: 0.0047
Epoch 0, train loss: 0.0171, val loss: 0.3260
Epoch 10, train loss: 0.0553, val loss: 0.1922
Epoch 20, train loss: 0.0194, val loss: 0.0596
Epoch 30, train loss: 0.0072, val loss: 0.0477
Epoch 40, train loss: 0.0047, val loss: 0.0047
Epoch 50, train loss: 0.0317, val loss: 0.1018
Epoch 60, train loss: 0.0316, val loss: 0.1089
Epoch 70, train loss: 0.0120, val loss: 0.0023
Epoch 0, train loss: 0.0171, val loss: 0.0238
Epoch 10, train loss: 0.0004, val loss: 0.0083
Epoch 20, train loss: 0.0022, val loss: 0.0033
Epoch 30, train loss: 0.0005, val loss: 0.0010
Epoch 40, train loss: 0.0006, val loss: 0.0002
Epoch 0, train loss: 0.0171, val loss: 0.0238
Epoch 10, train loss: 0.0004, val loss: 0.0083
Epoch 20, train loss: 0.0022, val loss: 0.0033
Epoch 30, train loss: 0.0005, val loss: 0.0010
Epoch 40, train loss: 0.0006, val loss: 0.0002
Epoch 50, train loss: 0.0007, val loss: 0.0038
Epoch 60, train loss: 0.0004, val loss: 0.0015
Epoch 70, train loss: 0.0003, val loss: 0.0017
Epoch 80, train loss: 0.0003, val loss: 0.0004
Inferred coeffs for Guatemala: [ 1.086379    1.2002625   0.7877821   0.57177466  0.93933344  1.2970029
 -2.9046443  -0.5887717   0.17886081  0.08548481 -1.3636476  -0.00972585
  0.00622466 -4.6094418   2.491494   -0.01970534 -1.4204255   0.8688437 ]
Epoch 0, train loss: 0.0196, val loss: 0.3212
Epoch 10, train loss: 0.0528, val loss: 0.1878
Epoch 20, train loss: 0.0170, val loss: 0.0554
Epoch 30, train loss: 0.0048, val loss: 0.0517
Epoch 40, train loss: 0.0020, val loss: 0.0005
Epoch 0, train loss: 0.0196, val loss: 0.3212
Epoch 10, train loss: 0.0528, val loss: 0.1878
Epoch 20, train loss: 0.0170, val loss: 0.0554
Epoch 30, train loss: 0.0048, val loss: 0.0517
Epoch 40, train loss: 0.0020, val loss: 0.0005
Epoch 50, train loss: 0.0095, val loss: 0.0485
Epoch 60, train loss: 0.0121, val loss: 0.0194
Epoch 70, train loss: 0.0012, val loss: 0.0006
Epoch 80, train loss: 0.0062, val loss: 0.0297
Epoch 90, train loss: 0.0105, val loss: 0.0129
Epoch 0, train loss: 0.0196, val loss: 0.0282
Epoch 10, train loss: 0.0018, val loss: 0.0047
Epoch 20, train loss: 0.0009, val loss: 0.0069
Epoch 30, train loss: 0.0009, val loss: 0.0052
Epoch 40, train loss: 0.0008, val loss: 0.0044
Epoch 0, train loss: 0.0196, val loss: 0.0282
Epoch 10, train loss: 0.0018, val loss: 0.0047
Epoch 20, train loss: 0.0009, val loss: 0.0069
Epoch 30, train loss: 0.0009, val loss: 0.0052
Epoch 40, train loss: 0.0008, val loss: 0.0044
Epoch 50, train loss: 0.0009, val loss: 0.0029
Inferred coeffs for Honduras: [ 1.0873276   1.191504    0.79549086  0.53496844  0.94236463  1.2877349
 -2.890276   -0.57600635  0.1848414   0.08571495 -1.3701276  -0.0087768
  0.00527558 -4.6031995   2.4851367  -0.02075946 -1.346218    0.8003249 ]
Epoch 0, train loss: 0.0256, val loss: 0.2754
Epoch 10, train loss: 0.0471, val loss: 0.1344
Epoch 20, train loss: 0.0214, val loss: 0.0388
Epoch 30, train loss: 0.0082, val loss: 0.0839
Epoch 40, train loss: 0.0076, val loss: 0.0169
Epoch 0, train loss: 0.0256, val loss: 0.2754
Epoch 10, train loss: 0.0471, val loss: 0.1344
Epoch 20, train loss: 0.0214, val loss: 0.0388
Epoch 30, train loss: 0.0082, val loss: 0.0839
Epoch 40, train loss: 0.0076, val loss: 0.0169
Epoch 50, train loss: 0.0051, val loss: 0.0104
Epoch 0, train loss: 0.0256, val loss: 0.0819
Epoch 10, train loss: 0.0070, val loss: 0.0558
Epoch 20, train loss: 0.0052, val loss: 0.0254
Epoch 30, train loss: 0.0050, val loss: 0.0204
Epoch 0, train loss: 0.0256, val loss: 0.0819
Epoch 10, train loss: 0.0070, val loss: 0.0558
Epoch 20, train loss: 0.0052, val loss: 0.0254
Epoch 30, train loss: 0.0050, val loss: 0.0204
Inferred coeffs for Mexico: [ 1.0879905   1.2019436   0.7893481   0.570401    0.9409337   1.2954448
 -2.903122   -0.5904769   0.18043908  0.08386403 -1.3619845  -0.00811423
  0.00461303 -4.6090817   2.491131   -0.02131627 -1.4225775   0.8709538 ]
Epoch 0, train loss: 0.0476, val loss: 0.2264
Epoch 10, train loss: 0.0048, val loss: 0.0555
Epoch 20, train loss: 0.0049, val loss: 0.0389
Epoch 30, train loss: 0.0049, val loss: 0.0358
Epoch 0, train loss: 0.0476, val loss: 0.2264
Epoch 10, train loss: 0.0048, val loss: 0.0555
Epoch 20, train loss: 0.0049, val loss: 0.0389
Epoch 30, train loss: 0.0049, val loss: 0.0358
Epoch 0, train loss: 0.0476, val loss: 0.1274
Epoch 10, train loss: 0.0073, val loss: 0.0054
Epoch 20, train loss: 0.0054, val loss: 0.0186
Epoch 30, train loss: 0.0042, val loss: 0.0117
Epoch 40, train loss: 0.0042, val loss: 0.0097
Epoch 0, train loss: 0.0476, val loss: 0.1274
Epoch 10, train loss: 0.0073, val loss: 0.0054
Epoch 20, train loss: 0.0054, val loss: 0.0186
Epoch 30, train loss: 0.0042, val loss: 0.0117
Epoch 40, train loss: 0.0042, val loss: 0.0097
Epoch 50, train loss: 0.0043, val loss: 0.0065
Inferred coeffs for Panama: [ 1.0892551e+00  1.2031134e+00  7.9067785e-01  5.6879967e-01
  9.4222969e-01  1.2940965e+00 -2.9017215e+00 -5.9161210e-01
  1.8173103e-01  8.2622819e-02 -1.3607953e+00 -6.8494403e-03
  3.3482378e-03 -4.6088920e+00  2.4909406e+00 -2.2581574e-02
 -1.4230764e+00  8.7150544e-01]
Epoch 0, train loss: 0.0213, val loss: 0.3175
Epoch 10, train loss: 0.0510, val loss: 0.1832
Epoch 20, train loss: 0.0151, val loss: 0.0503
Epoch 30, train loss: 0.0028, val loss: 0.0571
Epoch 40, train loss: 0.0008, val loss: 0.0259
Epoch 0, train loss: 0.0213, val loss: 0.3175
Epoch 10, train loss: 0.0510, val loss: 0.1832
Epoch 20, train loss: 0.0151, val loss: 0.0503
Epoch 30, train loss: 0.0028, val loss: 0.0571
Epoch 40, train loss: 0.0008, val loss: 0.0259
Epoch 50, train loss: 0.0080, val loss: 0.0027
Epoch 60, train loss: 0.0022, val loss: 0.0007
Epoch 70, train loss: 0.0016, val loss: 0.0364
Epoch 80, train loss: 0.0077, val loss: 0.0139
Epoch 90, train loss: 0.0032, val loss: 0.0456
Epoch 0, train loss: 0.0213, val loss: 0.0327
Epoch 10, train loss: 0.0071, val loss: 0.0246
Epoch 20, train loss: 0.0031, val loss: 0.0034
Epoch 30, train loss: 0.0019, val loss: 0.0021
Epoch 40, train loss: 0.0016, val loss: 0.0016
Epoch 0, train loss: 0.0213, val loss: 0.0327
Epoch 10, train loss: 0.0071, val loss: 0.0246
Epoch 20, train loss: 0.0031, val loss: 0.0034
Epoch 30, train loss: 0.0019, val loss: 0.0021
Epoch 40, train loss: 0.0016, val loss: 0.0016
Epoch 50, train loss: 0.0008, val loss: 0.0022
Inferred coeffs for Costa Rica: [ 1.0874289   1.1919714   0.7953333   0.5362501   0.94237304  1.2879574
 -2.8906875  -0.5766543   0.18478729  0.0855343  -1.3697125  -0.0086734
  0.00517215 -4.6004596   2.4823532  -0.02086435 -1.3494557   0.8034352 ]
Epoch 0, train loss: 0.0224, val loss: 0.3102
Epoch 10, train loss: 0.0501, val loss: 0.1723
Epoch 20, train loss: 0.0261, val loss: 0.1165
Epoch 30, train loss: 0.0170, val loss: 0.0017
Epoch 40, train loss: 0.0223, val loss: 0.0014
Epoch 0, train loss: 0.0224, val loss: 0.3102
Epoch 10, train loss: 0.0501, val loss: 0.1723
Epoch 20, train loss: 0.0261, val loss: 0.1165
Epoch 30, train loss: 0.0170, val loss: 0.0017
Epoch 40, train loss: 0.0223, val loss: 0.0014
Epoch 0, train loss: 0.0224, val loss: 0.0439
Epoch 10, train loss: 0.0062, val loss: 0.0264
Epoch 20, train loss: 0.0031, val loss: 0.0163
Epoch 30, train loss: 0.0026, val loss: 0.0094
Epoch 40, train loss: 0.0016, val loss: 0.0003
Epoch 0, train loss: 0.0224, val loss: 0.0439
Epoch 10, train loss: 0.0062, val loss: 0.0264
Epoch 20, train loss: 0.0031, val loss: 0.0163
Epoch 30, train loss: 0.0026, val loss: 0.0094
Epoch 40, train loss: 0.0016, val loss: 0.0003
Epoch 50, train loss: 0.0018, val loss: 0.0028
Epoch 60, train loss: 0.0017, val loss: 0.0057
Epoch 70, train loss: 0.0016, val loss: 0.0008
Inferred coeffs for Cuba: [ 1.0869539   1.2008066   0.78837794  0.5710928   0.9399188   1.2964013
 -2.9040265  -0.5893042   0.17944103  0.08492001 -1.3630986  -0.00915132
  0.00565012 -4.60913     2.4911752  -0.02028012 -1.4207317   0.86916995]
Epoch 0, train loss: 0.0200, val loss: 0.3021
Epoch 10, train loss: 0.0523, val loss: 0.1697
Epoch 20, train loss: 0.0167, val loss: 0.0380
Epoch 30, train loss: 0.0032, val loss: 0.0552
Epoch 40, train loss: 0.0110, val loss: 0.0337
Epoch 0, train loss: 0.0200, val loss: 0.3021
Epoch 10, train loss: 0.0523, val loss: 0.1697
Epoch 20, train loss: 0.0167, val loss: 0.0380
Epoch 30, train loss: 0.0032, val loss: 0.0552
Epoch 40, train loss: 0.0110, val loss: 0.0337
Epoch 0, train loss: 0.0200, val loss: 0.0462
Epoch 10, train loss: 0.0071, val loss: 0.0332
Epoch 20, train loss: 0.0036, val loss: 0.0263
Epoch 30, train loss: 0.0032, val loss: 0.0104
Epoch 40, train loss: 0.0031, val loss: 0.0083
Epoch 0, train loss: 0.0200, val loss: 0.0462
Epoch 10, train loss: 0.0071, val loss: 0.0332
Epoch 20, train loss: 0.0036, val loss: 0.0263
Epoch 30, train loss: 0.0032, val loss: 0.0104
Epoch 40, train loss: 0.0031, val loss: 0.0083
Inferred coeffs for New Zealand: [ 1.0873677   1.1964325   0.7921243   0.55298275  0.94136477  1.2918769
 -2.8969274  -0.5830834   0.18243222  0.08496223 -1.3662113  -0.00873421
  0.00523298 -4.607823    2.489855   -0.02075435 -1.3862331   0.8374598 ]
Epoch 0, train loss: 0.0212, val loss: 0.3194
Epoch 10, train loss: 0.0513, val loss: 0.1831
Epoch 20, train loss: 0.0152, val loss: 0.0499
Epoch 30, train loss: 0.0043, val loss: 0.0536
Epoch 40, train loss: 0.0034, val loss: 0.0048
Epoch 0, train loss: 0.0212, val loss: 0.3194
Epoch 10, train loss: 0.0513, val loss: 0.1831
Epoch 20, train loss: 0.0152, val loss: 0.0499
Epoch 30, train loss: 0.0043, val loss: 0.0536
Epoch 40, train loss: 0.0034, val loss: 0.0048
Epoch 50, train loss: 0.0022, val loss: 0.0009
Epoch 60, train loss: 0.0035, val loss: 0.0094
Epoch 70, train loss: 0.0049, val loss: 0.0109
Epoch 80, train loss: 0.0077, val loss: 0.0244
Epoch 0, train loss: 0.0212, val loss: 0.0330
Epoch 10, train loss: 0.0057, val loss: 0.0135
Epoch 20, train loss: 0.0009, val loss: 0.0064
Epoch 30, train loss: 0.0025, val loss: 0.0084
Epoch 40, train loss: 0.0013, val loss: 0.0011
Epoch 0, train loss: 0.0212, val loss: 0.0330
Epoch 10, train loss: 0.0057, val loss: 0.0135
Epoch 20, train loss: 0.0009, val loss: 0.0064
Epoch 30, train loss: 0.0025, val loss: 0.0084
Epoch 40, train loss: 0.0013, val loss: 0.0011
Epoch 50, train loss: 0.0009, val loss: 0.0041
Epoch 60, train loss: 0.0012, val loss: 0.0027
Epoch 70, train loss: 0.0012, val loss: 0.0025
Epoch 80, train loss: 0.0009, val loss: 0.0031
Epoch 90, train loss: 0.0005, val loss: 0.0007
Inferred coeffs for Bahrain: [ 1.0866443   1.2004797   0.7880821   0.57132715  0.9396079   1.2966949
 -2.9043124  -0.5889708   0.17916037  0.08521818 -1.3634143  -0.00946013
  0.00595892 -4.6092296   2.4912775  -0.01997184 -1.4203554   0.86880994]
Epoch 0, train loss: 0.0361, val loss: 0.2683
Epoch 10, train loss: 0.0372, val loss: 0.1104
Epoch 20, train loss: 0.0149, val loss: 0.0971
Epoch 30, train loss: 0.0088, val loss: 0.0132
Epoch 40, train loss: 0.0059, val loss: 0.0030
Epoch 0, train loss: 0.0361, val loss: 0.2683
Epoch 10, train loss: 0.0372, val loss: 0.1104
Epoch 20, train loss: 0.0149, val loss: 0.0971
Epoch 30, train loss: 0.0088, val loss: 0.0132
Epoch 40, train loss: 0.0059, val loss: 0.0030
Epoch 50, train loss: 0.0054, val loss: 0.0366
Epoch 60, train loss: 0.0141, val loss: 0.0078
Epoch 0, train loss: 0.0361, val loss: 0.1059
Epoch 10, train loss: 0.0067, val loss: 0.0369
Epoch 20, train loss: 0.0068, val loss: 0.0067
Epoch 30, train loss: 0.0057, val loss: 0.0070
Epoch 40, train loss: 0.0051, val loss: 0.0122
Epoch 0, train loss: 0.0361, val loss: 0.1059
Epoch 10, train loss: 0.0067, val loss: 0.0369
Epoch 20, train loss: 0.0068, val loss: 0.0067
Epoch 30, train loss: 0.0057, val loss: 0.0070
Epoch 40, train loss: 0.0051, val loss: 0.0122
Inferred coeffs for Saudi Arabia: [ 1.0885340e+00  1.2024209e+00  7.8993630e-01  5.6962633e-01
  9.4149572e-01  1.2948462e+00 -2.9024866e+00 -5.9092993e-01
  1.8100341e-01  8.3336130e-02 -1.3614936e+00 -7.5707501e-03
  4.0695518e-03 -4.6079130e+00  2.4899540e+00 -2.1860121e-02
 -1.4225856e+00  8.7099820e-01]
Epoch 0, train loss: 0.2671, val loss: 0.6337
Epoch 10, train loss: 0.0934, val loss: 0.2941
Epoch 20, train loss: 0.0515, val loss: 0.1245
Epoch 30, train loss: 0.0437, val loss: 0.0287
Epoch 40, train loss: 0.0333, val loss: 0.0926
Epoch 0, train loss: 0.2671, val loss: 0.6337
Epoch 10, train loss: 0.0934, val loss: 0.2941
Epoch 20, train loss: 0.0515, val loss: 0.1245
Epoch 30, train loss: 0.0437, val loss: 0.0287
Epoch 40, train loss: 0.0333, val loss: 0.0926
Epoch 0, train loss: 0.2671, val loss: 0.9910
Epoch 10, train loss: 0.1626, val loss: 0.5872
Epoch 20, train loss: 0.0558, val loss: 0.0539
Epoch 30, train loss: 0.0529, val loss: 0.2057
Epoch 40, train loss: 0.0347, val loss: 0.0060
Epoch 0, train loss: 0.2671, val loss: 0.9910
Epoch 10, train loss: 0.1626, val loss: 0.5872
Epoch 20, train loss: 0.0558, val loss: 0.0539
Epoch 30, train loss: 0.0529, val loss: 0.2057
Epoch 40, train loss: 0.0347, val loss: 0.0060
Epoch 50, train loss: 0.0333, val loss: 0.0686
Inferred coeffs for Iran: [ 1.1067144   1.2208911   0.8078857   0.5528168   0.9595586   1.2769924
 -2.8848007  -0.6094993   0.19896334  0.0651809  -1.3431357   0.01060929
 -0.01411049 -4.609455    2.491379   -0.04003552 -1.442489    0.8907361 ]
Epoch 0, train loss: 0.0185, val loss: 0.3313
Epoch 10, train loss: 0.0542, val loss: 0.1912
Epoch 20, train loss: 0.0174, val loss: 0.0563
Epoch 30, train loss: 0.0078, val loss: 0.0441
Epoch 40, train loss: 0.0277, val loss: 0.0794
Epoch 0, train loss: 0.0185, val loss: 0.3313
Epoch 10, train loss: 0.0542, val loss: 0.1912
Epoch 20, train loss: 0.0174, val loss: 0.0563
Epoch 30, train loss: 0.0078, val loss: 0.0441
Epoch 40, train loss: 0.0277, val loss: 0.0794
Epoch 50, train loss: 0.0026, val loss: 0.0202
Epoch 60, train loss: 0.0169, val loss: 0.0711
Epoch 70, train loss: 0.0145, val loss: 0.0097
Epoch 0, train loss: 0.0185, val loss: 0.0251
Epoch 10, train loss: 0.0010, val loss: 0.0084
Epoch 20, train loss: 0.0005, val loss: 0.0040
Epoch 30, train loss: 0.0014, val loss: 0.0018
Epoch 40, train loss: 0.0016, val loss: 0.0005
Epoch 0, train loss: 0.0185, val loss: 0.0251
Epoch 10, train loss: 0.0010, val loss: 0.0084
Epoch 20, train loss: 0.0005, val loss: 0.0040
Epoch 30, train loss: 0.0014, val loss: 0.0018
Epoch 40, train loss: 0.0016, val loss: 0.0005
Epoch 50, train loss: 0.0011, val loss: 0.0014
Inferred coeffs for Kuwait: [ 1.0863932   1.200302    0.7877804   0.57184285  0.93934226  1.2970076
 -2.9046626  -0.58881974  0.17886761  0.08546424 -1.3636134  -0.00971151
  0.00621031 -4.6091986   2.4912448  -0.01971956 -1.4206499   0.8690555 ]
Epoch 0, train loss: 0.0179, val loss: 0.3247
Epoch 10, train loss: 0.0546, val loss: 0.1880
Epoch 20, train loss: 0.0181, val loss: 0.0535
Epoch 30, train loss: 0.0057, val loss: 0.0547
Epoch 40, train loss: 0.0031, val loss: 0.0024
Epoch 0, train loss: 0.0179, val loss: 0.3247
Epoch 10, train loss: 0.0546, val loss: 0.1880
Epoch 20, train loss: 0.0181, val loss: 0.0535
Epoch 30, train loss: 0.0057, val loss: 0.0547
Epoch 40, train loss: 0.0031, val loss: 0.0024
Epoch 50, train loss: 0.0011, val loss: 0.0148
Epoch 60, train loss: 0.0053, val loss: 0.0124
Epoch 70, train loss: 0.0130, val loss: 0.0105
Epoch 0, train loss: 0.0179, val loss: 0.0281
Epoch 10, train loss: 0.0027, val loss: 0.0080
Epoch 20, train loss: 0.0010, val loss: 0.0064
Epoch 30, train loss: 0.0009, val loss: 0.0014
Epoch 0, train loss: 0.0179, val loss: 0.0281
Epoch 10, train loss: 0.0027, val loss: 0.0080
Epoch 20, train loss: 0.0010, val loss: 0.0064
Epoch 30, train loss: 0.0009, val loss: 0.0014
Inferred coeffs for Lebanon: [ 1.0871434   1.1925372   0.79444826  0.5397315   0.9418816   1.2889925
 -2.8921778  -0.5776387   0.18410623  0.08566476 -1.3692875  -0.00895347
  0.00545222 -4.594493    2.4762902  -0.02058773 -1.3562721   0.80990523]
Epoch 0, train loss: 0.0296, val loss: 0.2617
Epoch 10, train loss: 0.0430, val loss: 0.1214
Epoch 20, train loss: 0.0197, val loss: 0.0305
Epoch 30, train loss: 0.0059, val loss: 0.0032
Epoch 40, train loss: 0.0066, val loss: 0.0237
Epoch 0, train loss: 0.0296, val loss: 0.2617
Epoch 10, train loss: 0.0430, val loss: 0.1214
Epoch 20, train loss: 0.0197, val loss: 0.0305
Epoch 30, train loss: 0.0059, val loss: 0.0032
Epoch 40, train loss: 0.0066, val loss: 0.0237
Epoch 50, train loss: 0.0060, val loss: 0.0229
Epoch 0, train loss: 0.0296, val loss: 0.0948
Epoch 10, train loss: 0.0073, val loss: 0.0500
Epoch 20, train loss: 0.0077, val loss: 0.0040
Epoch 30, train loss: 0.0061, val loss: 0.0225
Epoch 40, train loss: 0.0061, val loss: 0.0245
Epoch 0, train loss: 0.0296, val loss: 0.0948
Epoch 10, train loss: 0.0073, val loss: 0.0500
Epoch 20, train loss: 0.0077, val loss: 0.0040
Epoch 30, train loss: 0.0061, val loss: 0.0225
Epoch 40, train loss: 0.0061, val loss: 0.0245
Epoch 50, train loss: 0.0059, val loss: 0.0266
Inferred coeffs for Pakistan: [ 1.0888368e+00  1.1970066e+00  7.9423869e-01  5.4809731e-01
  9.4307810e-01  1.2895658e+00 -2.8941853e+00 -5.8330727e-01
  1.8446222e-01  8.3517179e-02 -1.3653687e+00 -7.2654067e-03
  3.7641732e-03 -4.5925198e+00  2.4744003e+00 -2.2235084e-02
 -1.3811852e+00  8.3299428e-01]
Epoch 0, train loss: 0.0198, val loss: 0.3162
Epoch 10, train loss: 0.0527, val loss: 0.1791
Epoch 20, train loss: 0.0162, val loss: 0.0443
Epoch 30, train loss: 0.0037, val loss: 0.0642
Epoch 40, train loss: 0.0013, val loss: 0.0067
Epoch 0, train loss: 0.0198, val loss: 0.3162
Epoch 10, train loss: 0.0527, val loss: 0.1791
Epoch 20, train loss: 0.0162, val loss: 0.0443
Epoch 30, train loss: 0.0037, val loss: 0.0642
Epoch 40, train loss: 0.0013, val loss: 0.0067
Epoch 50, train loss: 0.0121, val loss: 0.0502
Epoch 60, train loss: 0.0057, val loss: 0.0176
Epoch 70, train loss: 0.0064, val loss: 0.0072
Epoch 0, train loss: 0.0198, val loss: 0.0370
Epoch 10, train loss: 0.0027, val loss: 0.0036
Epoch 20, train loss: 0.0016, val loss: 0.0009
Epoch 30, train loss: 0.0010, val loss: 0.0097
Epoch 40, train loss: 0.0010, val loss: 0.0058
Epoch 0, train loss: 0.0198, val loss: 0.0370
Epoch 10, train loss: 0.0027, val loss: 0.0036
Epoch 20, train loss: 0.0016, val loss: 0.0009
Epoch 30, train loss: 0.0010, val loss: 0.0097
Epoch 40, train loss: 0.0010, val loss: 0.0058
Epoch 50, train loss: 0.0010, val loss: 0.0071
Inferred coeffs for Iraq: [ 1.0874187   1.1930755   0.79453784  0.5404277   0.9420902   1.2889504
 -2.8922584  -0.57829005  0.18425569  0.08534762 -1.3688031  -0.00867684
  0.00517562 -4.593702    2.4754899  -0.02086419 -1.3586403   0.8121843 ]
Epoch 0, train loss: 0.0271, val loss: 0.2888
Epoch 10, train loss: 0.0457, val loss: 0.1457
Epoch 20, train loss: 0.0239, val loss: 0.0647
Epoch 30, train loss: 0.0082, val loss: 0.0668
Epoch 40, train loss: 0.0124, val loss: 0.0252
Epoch 0, train loss: 0.0271, val loss: 0.2888
Epoch 10, train loss: 0.0457, val loss: 0.1457
Epoch 20, train loss: 0.0239, val loss: 0.0647
Epoch 30, train loss: 0.0082, val loss: 0.0668
Epoch 40, train loss: 0.0124, val loss: 0.0252
Epoch 0, train loss: 0.0271, val loss: 0.0706
Epoch 10, train loss: 0.0067, val loss: 0.0390
Epoch 20, train loss: 0.0024, val loss: 0.0257
Epoch 30, train loss: 0.0027, val loss: 0.0234
Epoch 0, train loss: 0.0271, val loss: 0.0706
Epoch 10, train loss: 0.0067, val loss: 0.0390
Epoch 20, train loss: 0.0024, val loss: 0.0257
Epoch 30, train loss: 0.0027, val loss: 0.0234
Inferred coeffs for Qatar: [ 1.0876663   1.2016375   0.78901196  0.5707868   0.94060576  1.2957835
 -2.90347    -0.59017724  0.18010762  0.08418496 -1.3622948  -0.00843841
  0.00493721 -4.6090794   2.4911299  -0.02099191 -1.4224006   0.8707656 ]
Epoch 0, train loss: 0.0194, val loss: 0.2757
Epoch 10, train loss: 0.0537, val loss: 0.1224
Epoch 20, train loss: 0.0231, val loss: 0.0327
Epoch 30, train loss: 0.0221, val loss: 0.0396
Epoch 40, train loss: 0.0133, val loss: 0.1390
Epoch 0, train loss: 0.0194, val loss: 0.2757
Epoch 10, train loss: 0.0537, val loss: 0.1224
Epoch 20, train loss: 0.0231, val loss: 0.0327
Epoch 30, train loss: 0.0221, val loss: 0.0396
Epoch 40, train loss: 0.0133, val loss: 0.1390
Epoch 50, train loss: 0.0129, val loss: 0.0559
Epoch 60, train loss: 0.0091, val loss: 0.0825
Epoch 0, train loss: 0.0194, val loss: 0.0940
Epoch 10, train loss: 0.0065, val loss: 0.0789
Epoch 20, train loss: 0.0036, val loss: 0.0804
Epoch 30, train loss: 0.0035, val loss: 0.0784
Epoch 0, train loss: 0.0194, val loss: 0.0940
Epoch 10, train loss: 0.0065, val loss: 0.0789
Epoch 20, train loss: 0.0036, val loss: 0.0804
Epoch 30, train loss: 0.0035, val loss: 0.0784
Inferred coeffs for South Korea: [ 1.0891225e+00  1.1949441e+00  7.9614270e-01  5.3910655e-01
  9.4365865e-01  1.2873893e+00 -2.8907325e+00 -5.8020198e-01
  1.8615638e-01  8.3436713e-02 -1.3668886e+00 -6.9797053e-03
  3.4784505e-03 -4.5617285e+00  2.4430599e+00 -2.2548452e-02
 -1.3630930e+00  8.1630337e-01]
Epoch 0, train loss: 0.0284, val loss: 0.2868
Epoch 10, train loss: 0.0443, val loss: 0.1472
Epoch 20, train loss: 0.0327, val loss: 0.0771
Epoch 30, train loss: 0.0275, val loss: 0.0338
Epoch 40, train loss: 0.0120, val loss: 0.0365
Epoch 0, train loss: 0.0284, val loss: 0.2868
Epoch 10, train loss: 0.0443, val loss: 0.1472
Epoch 20, train loss: 0.0327, val loss: 0.0771
Epoch 30, train loss: 0.0275, val loss: 0.0338
Epoch 40, train loss: 0.0120, val loss: 0.0365
Epoch 50, train loss: 0.0083, val loss: 0.0261
Epoch 60, train loss: 0.0050, val loss: 0.0363
Epoch 70, train loss: 0.0090, val loss: 0.0044
Epoch 80, train loss: 0.0075, val loss: 0.0116
Epoch 90, train loss: 0.0061, val loss: 0.0098
Epoch 0, train loss: 0.0284, val loss: 0.0690
Epoch 10, train loss: 0.0059, val loss: 0.0319
Epoch 20, train loss: 0.0055, val loss: 0.0017
Epoch 30, train loss: 0.0047, val loss: 0.0053
Epoch 0, train loss: 0.0284, val loss: 0.0690
Epoch 10, train loss: 0.0059, val loss: 0.0319
Epoch 20, train loss: 0.0055, val loss: 0.0017
Epoch 30, train loss: 0.0047, val loss: 0.0053
Inferred coeffs for Argentina: [ 1.0876393   1.201611    0.7889846   0.5708156   0.9405787   1.2958109
 -2.9034977  -0.590151    0.1800803   0.08421193 -1.3623214  -0.00846539
  0.00496419 -4.6092153   2.4912665  -0.02096492 -1.4223777   0.8707423 ]
Epoch 0, train loss: 0.0514, val loss: 0.0680
Epoch 10, train loss: 0.0204, val loss: 0.2212
Epoch 20, train loss: 0.0240, val loss: 0.2082
Epoch 30, train loss: 0.0200, val loss: 0.1225
Epoch 0, train loss: 0.0514, val loss: 0.0680
Epoch 10, train loss: 0.0204, val loss: 0.2212
Epoch 20, train loss: 0.0240, val loss: 0.2082
Epoch 30, train loss: 0.0200, val loss: 0.1225
Epoch 0, train loss: 0.0514, val loss: 0.2931
Epoch 10, train loss: 0.0242, val loss: 0.0883
Epoch 20, train loss: 0.0209, val loss: 0.1715
Epoch 30, train loss: 0.0197, val loss: 0.1091
Epoch 0, train loss: 0.0514, val loss: 0.2931
Epoch 10, train loss: 0.0242, val loss: 0.0883
Epoch 20, train loss: 0.0209, val loss: 0.1715
Epoch 30, train loss: 0.0197, val loss: 0.1091
Inferred coeffs for Brazil: [ 1.0934860e+00  1.2071214e+00  7.9507828e-01  5.6363624e-01
  9.4652903e-01  1.2896355e+00 -2.8971510e+00 -5.9554291e-01
  1.8614408e-01  7.8364469e-02 -1.3566978e+00 -2.6184623e-03
 -8.8273961e-04 -4.6062698e+00  2.4883268e+00 -2.6816597e-02
 -1.4260213e+00  8.7459517e-01]
Epoch 0, train loss: 0.0533, val loss: 0.1571
Epoch 10, train loss: 0.0183, val loss: 0.1075
Epoch 20, train loss: 0.0126, val loss: 0.0273
Epoch 30, train loss: 0.0132, val loss: 0.0678
Epoch 40, train loss: 0.0126, val loss: 0.0048
Epoch 0, train loss: 0.0533, val loss: 0.1571
Epoch 10, train loss: 0.0183, val loss: 0.1075
Epoch 20, train loss: 0.0126, val loss: 0.0273
Epoch 30, train loss: 0.0132, val loss: 0.0678
Epoch 40, train loss: 0.0126, val loss: 0.0048
Epoch 50, train loss: 0.0161, val loss: 0.0540
Epoch 60, train loss: 0.0129, val loss: 0.0716
Epoch 0, train loss: 0.0533, val loss: 0.1951
Epoch 10, train loss: 0.0200, val loss: 0.0073
Epoch 20, train loss: 0.0154, val loss: 0.0649
Epoch 30, train loss: 0.0137, val loss: 0.0066
Epoch 40, train loss: 0.0129, val loss: 0.0381
Epoch 0, train loss: 0.0533, val loss: 0.1951
Epoch 10, train loss: 0.0200, val loss: 0.0073
Epoch 20, train loss: 0.0154, val loss: 0.0649
Epoch 30, train loss: 0.0137, val loss: 0.0066
Epoch 40, train loss: 0.0129, val loss: 0.0381
Epoch 50, train loss: 0.0126, val loss: 0.0211
Inferred coeffs for Chile: [ 1.0915123e+00  1.2018093e+00  7.9548514e-01  5.5293024e-01
  9.4584078e-01  1.2884281e+00 -2.8939707e+00 -5.8891362e-01
  1.8518575e-01  8.1122704e-02 -1.3613442e+00 -4.5928690e-03
  1.0916442e-03 -4.6023483e+00  2.4844785e+00 -2.4857329e-02
 -1.3981127e+00  8.4853560e-01]
Epoch 0, train loss: 0.0417, val loss: 0.2153
Epoch 10, train loss: 0.0186, val loss: 0.1350
Epoch 20, train loss: 0.0220, val loss: 0.0669
Epoch 30, train loss: 0.0165, val loss: 0.0055
Epoch 40, train loss: 0.0100, val loss: 0.0066
Epoch 0, train loss: 0.0417, val loss: 0.2153
Epoch 10, train loss: 0.0186, val loss: 0.1350
Epoch 20, train loss: 0.0220, val loss: 0.0669
Epoch 30, train loss: 0.0165, val loss: 0.0055
Epoch 40, train loss: 0.0100, val loss: 0.0066
Epoch 0, train loss: 0.0417, val loss: 0.1361
Epoch 10, train loss: 0.0116, val loss: 0.0114
Epoch 20, train loss: 0.0105, val loss: 0.0198
Epoch 30, train loss: 0.0099, val loss: 0.0281
Epoch 40, train loss: 0.0102, val loss: 0.0083
Epoch 0, train loss: 0.0417, val loss: 0.1361
Epoch 10, train loss: 0.0116, val loss: 0.0114
Epoch 20, train loss: 0.0105, val loss: 0.0198
Epoch 30, train loss: 0.0099, val loss: 0.0281
Epoch 40, train loss: 0.0102, val loss: 0.0083
Epoch 50, train loss: 0.0097, val loss: 0.0111
Inferred coeffs for Ecuador: [ 1.0895760e+00  1.2034421e+00  7.9099017e-01  5.6853122e-01
  9.4255507e-01  1.2937876e+00 -2.9014096e+00 -5.9194261e-01
  1.8201263e-01  8.2325406e-02 -1.3604817e+00 -6.5289810e-03
  3.0277800e-03 -4.6091881e+00  2.4912405e+00 -2.2901254e-02
 -1.4233438e+00  8.7175596e-01]
Epoch 0, train loss: 0.0337, val loss: 0.2574
Epoch 10, train loss: 0.0388, val loss: 0.1193
Epoch 20, train loss: 0.0088, val loss: 0.0663
Epoch 30, train loss: 0.0080, val loss: 0.0378
Epoch 40, train loss: 0.0053, val loss: 0.0395
Epoch 0, train loss: 0.0337, val loss: 0.2574
Epoch 10, train loss: 0.0388, val loss: 0.1193
Epoch 20, train loss: 0.0088, val loss: 0.0663
Epoch 30, train loss: 0.0080, val loss: 0.0378
Epoch 40, train loss: 0.0053, val loss: 0.0395
Epoch 0, train loss: 0.0337, val loss: 0.0968
Epoch 10, train loss: 0.0055, val loss: 0.0362
Epoch 20, train loss: 0.0068, val loss: 0.0028
Epoch 30, train loss: 0.0045, val loss: 0.0069
Epoch 40, train loss: 0.0047, val loss: 0.0119
Epoch 0, train loss: 0.0337, val loss: 0.0968
Epoch 10, train loss: 0.0055, val loss: 0.0362
Epoch 20, train loss: 0.0068, val loss: 0.0028
Epoch 30, train loss: 0.0045, val loss: 0.0069
Epoch 40, train loss: 0.0047, val loss: 0.0119
Epoch 50, train loss: 0.0045, val loss: 0.0091
Inferred coeffs for Colombia: [ 1.0886949e+00  1.1983241e+00  7.9307270e-01  5.5366176e-01
  9.4259739e-01  1.2909892e+00 -2.8963633e+00 -5.8521354e-01
  1.8353437e-01  8.3512999e-02 -1.3644193e+00 -7.4075693e-03
  3.9063543e-03 -4.5991921e+00  2.4811511e+00 -2.2075275e-02
 -1.3920990e+00  8.4300822e-01]
Epoch 0, train loss: 0.0184, val loss: 0.3208
Epoch 10, train loss: 0.0540, val loss: 0.1869
Epoch 20, train loss: 0.0181, val loss: 0.0543
Epoch 30, train loss: 0.0059, val loss: 0.0530
Epoch 40, train loss: 0.0033, val loss: 0.0009
Epoch 0, train loss: 0.0184, val loss: 0.3208
Epoch 10, train loss: 0.0540, val loss: 0.1869
Epoch 20, train loss: 0.0181, val loss: 0.0543
Epoch 30, train loss: 0.0059, val loss: 0.0530
Epoch 40, train loss: 0.0033, val loss: 0.0009
Epoch 50, train loss: 0.0074, val loss: 0.0254
Epoch 60, train loss: 0.0006, val loss: 0.0237
Epoch 70, train loss: 0.0051, val loss: 0.0342
Epoch 80, train loss: 0.0116, val loss: 0.0578
Epoch 0, train loss: 0.0184, val loss: 0.0290
Epoch 10, train loss: 0.0020, val loss: 0.0002
Epoch 20, train loss: 0.0020, val loss: 0.0083
Epoch 30, train loss: 0.0012, val loss: 0.0005
Epoch 40, train loss: 0.0009, val loss: 0.0015
Epoch 0, train loss: 0.0184, val loss: 0.0290
Epoch 10, train loss: 0.0020, val loss: 0.0002
Epoch 20, train loss: 0.0020, val loss: 0.0083
Epoch 30, train loss: 0.0012, val loss: 0.0005
Epoch 40, train loss: 0.0009, val loss: 0.0015
Epoch 50, train loss: 0.0005, val loss: 0.0036
Epoch 60, train loss: 0.0006, val loss: 0.0021
Inferred coeffs for Bolivia: [ 1.0865333   1.2004393   0.7879226   0.571695    0.93948483  1.2968647
 -2.9045174  -0.5889554   0.17900366  0.08532815 -1.3634773  -0.00957112
  0.00606992 -4.6094556   2.4915044  -0.01985985 -1.4207431   0.8691481 ]
Epoch 0, train loss: 0.0456, val loss: 0.0903
Epoch 10, train loss: 0.0198, val loss: 0.1804
Epoch 20, train loss: 0.0192, val loss: 0.1890
Epoch 30, train loss: 0.0166, val loss: 0.1366
Epoch 0, train loss: 0.0456, val loss: 0.0903
Epoch 10, train loss: 0.0198, val loss: 0.1804
Epoch 20, train loss: 0.0192, val loss: 0.1890
Epoch 30, train loss: 0.0166, val loss: 0.1366
Epoch 0, train loss: 0.0456, val loss: 0.2636
Epoch 10, train loss: 0.0191, val loss: 0.1086
Epoch 20, train loss: 0.0146, val loss: 0.1768
Epoch 30, train loss: 0.0136, val loss: 0.1461
Epoch 0, train loss: 0.0456, val loss: 0.2636
Epoch 10, train loss: 0.0191, val loss: 0.1086
Epoch 20, train loss: 0.0146, val loss: 0.1768
Epoch 30, train loss: 0.0136, val loss: 0.1461
Inferred coeffs for Peru: [ 1.0920057e+00  1.2039760e+00  7.9478651e-01  5.5870342e-01
  9.4548386e-01  1.2895930e+00 -2.8961608e+00 -5.9174365e-01
  1.8560876e-01  7.9951651e-02 -1.3593725e+00 -4.0985364e-03
  5.9732224e-04 -4.6041059e+00  2.4861743e+00 -2.5352508e-02
 -1.4128859e+00  8.6249542e-01]
Epoch 0, train loss: 0.0236, val loss: 0.3203
Epoch 10, train loss: 0.0488, val loss: 0.1860
Epoch 20, train loss: 0.0209, val loss: 0.1030
Epoch 30, train loss: 0.0123, val loss: 0.0086
Epoch 40, train loss: 0.0066, val loss: 0.0031
Epoch 0, train loss: 0.0236, val loss: 0.3203
Epoch 10, train loss: 0.0488, val loss: 0.1860
Epoch 20, train loss: 0.0209, val loss: 0.1030
Epoch 30, train loss: 0.0123, val loss: 0.0086
Epoch 40, train loss: 0.0066, val loss: 0.0031
Epoch 50, train loss: 0.0024, val loss: 0.0280
Epoch 60, train loss: 0.0066, val loss: 0.0019
Epoch 70, train loss: 0.0054, val loss: 0.0298
Epoch 0, train loss: 0.0236, val loss: 0.0300
Epoch 10, train loss: 0.0073, val loss: 0.0096
Epoch 20, train loss: 0.0025, val loss: 0.0013
Epoch 30, train loss: 0.0024, val loss: 0.0061
Epoch 40, train loss: 0.0024, val loss: 0.0068
Epoch 0, train loss: 0.0236, val loss: 0.0300
Epoch 10, train loss: 0.0073, val loss: 0.0096
Epoch 20, train loss: 0.0025, val loss: 0.0013
Epoch 30, train loss: 0.0024, val loss: 0.0061
Epoch 40, train loss: 0.0024, val loss: 0.0068
Epoch 50, train loss: 0.0025, val loss: 0.0080
Inferred coeffs for Uruguay: [ 1.0871775   1.1927756   0.7943565   0.540367    0.9419237   1.2890722
 -2.8923898  -0.5779859   0.18409804  0.08554468 -1.369049   -0.00892373
  0.00542248 -4.6018515   2.4837823  -0.02060731 -1.3586963   0.8120072 ]
Epoch 0, train loss: 0.0283, val loss: 0.2871
Epoch 10, train loss: 0.0442, val loss: 0.1501
Epoch 20, train loss: 0.0293, val loss: 0.1561
Epoch 30, train loss: 0.0180, val loss: 0.0856
Epoch 40, train loss: 0.0137, val loss: 0.0118
Epoch 0, train loss: 0.0283, val loss: 0.2871
Epoch 10, train loss: 0.0442, val loss: 0.1501
Epoch 20, train loss: 0.0293, val loss: 0.1561
Epoch 30, train loss: 0.0180, val loss: 0.0856
Epoch 40, train loss: 0.0137, val loss: 0.0118
Epoch 0, train loss: 0.0283, val loss: 0.0661
Epoch 10, train loss: 0.0057, val loss: 0.0217
Epoch 20, train loss: 0.0033, val loss: 0.0101
Epoch 30, train loss: 0.0020, val loss: 0.0013
Epoch 40, train loss: 0.0017, val loss: 0.0083
Epoch 0, train loss: 0.0283, val loss: 0.0661
Epoch 10, train loss: 0.0057, val loss: 0.0217
Epoch 20, train loss: 0.0033, val loss: 0.0101
Epoch 30, train loss: 0.0020, val loss: 0.0013
Epoch 40, train loss: 0.0017, val loss: 0.0083
Epoch 50, train loss: 0.0017, val loss: 0.0032
Epoch 60, train loss: 0.0017, val loss: 0.0068
Inferred coeffs for Kazakhstan: [ 1.0875897   1.2014743   0.7889923   0.57057595  0.94055337  1.2957914
 -2.903429   -0.5899825   0.18004677  0.08429018 -1.362445   -0.00851503
  0.00501383 -4.6091733   2.4912224  -0.02091571 -1.4215592   0.86997044]
Epoch 0, train loss: 0.0217, val loss: 0.3155
Epoch 10, train loss: 0.0506, val loss: 0.1819
Epoch 20, train loss: 0.0148, val loss: 0.0495
Epoch 30, train loss: 0.0026, val loss: 0.0577
Epoch 40, train loss: 0.0006, val loss: 0.0278
Epoch 0, train loss: 0.0217, val loss: 0.3155
Epoch 10, train loss: 0.0506, val loss: 0.1819
Epoch 20, train loss: 0.0148, val loss: 0.0495
Epoch 30, train loss: 0.0026, val loss: 0.0577
Epoch 40, train loss: 0.0006, val loss: 0.0278
Epoch 50, train loss: 0.0080, val loss: 0.0126
Epoch 60, train loss: 0.0064, val loss: 0.0253
Epoch 70, train loss: 0.0062, val loss: 0.0340
Epoch 0, train loss: 0.0217, val loss: 0.0340
Epoch 10, train loss: 0.0079, val loss: 0.0273
Epoch 20, train loss: 0.0047, val loss: 0.0097
Epoch 30, train loss: 0.0028, val loss: 0.0074
Epoch 0, train loss: 0.0217, val loss: 0.0340
Epoch 10, train loss: 0.0079, val loss: 0.0273
Epoch 20, train loss: 0.0047, val loss: 0.0097
Epoch 30, train loss: 0.0028, val loss: 0.0074
Inferred coeffs for Kyrgyzstan: [ 1.0873902   1.1927059   0.79475105  0.53919643  0.9421739   1.2886649
 -2.8918037  -0.57776356  0.18434562  0.08546025 -1.3691212  -0.00870837
  0.00520713 -4.6035457   2.4854975  -0.02082881 -1.3557832   0.80939484]
Epoch 0, train loss: 0.0184, val loss: 0.3146
Epoch 10, train loss: 0.0541, val loss: 0.1788
Epoch 20, train loss: 0.0178, val loss: 0.0449
Epoch 30, train loss: 0.0054, val loss: 0.0631
Epoch 40, train loss: 0.0027, val loss: 0.0065
Epoch 0, train loss: 0.0184, val loss: 0.3146
Epoch 10, train loss: 0.0541, val loss: 0.1788
Epoch 20, train loss: 0.0178, val loss: 0.0449
Epoch 30, train loss: 0.0054, val loss: 0.0631
Epoch 40, train loss: 0.0027, val loss: 0.0065
Epoch 50, train loss: 0.0076, val loss: 0.0235
Epoch 60, train loss: 0.0268, val loss: 0.0669
Epoch 70, train loss: 0.0019, val loss: 0.0574
Epoch 80, train loss: 0.0172, val loss: 0.0256
Epoch 0, train loss: 0.0184, val loss: 0.0373
Epoch 10, train loss: 0.0018, val loss: 0.0014
Epoch 20, train loss: 0.0022, val loss: 0.0058
Epoch 30, train loss: 0.0017, val loss: 0.0104
Epoch 40, train loss: 0.0016, val loss: 0.0117
Epoch 0, train loss: 0.0184, val loss: 0.0373
Epoch 10, train loss: 0.0018, val loss: 0.0014
Epoch 20, train loss: 0.0022, val loss: 0.0058
Epoch 30, train loss: 0.0017, val loss: 0.0104
Epoch 40, train loss: 0.0016, val loss: 0.0117
Inferred coeffs for Azerbaijan: [ 1.0867559   1.2006904   0.7881258   0.5715712   0.93970156  1.2966657
 -2.9043329  -0.58921677  0.17921422  0.08510074 -1.363233   -0.00934891
  0.0058477  -4.6093884   2.491438   -0.02008184 -1.4211975   0.86958635]
Epoch 0, train loss: 0.0244, val loss: 0.2864
Epoch 10, train loss: 0.0484, val loss: 0.1417
Epoch 20, train loss: 0.0264, val loss: 0.1031
Epoch 30, train loss: 0.0233, val loss: 0.0374
Epoch 40, train loss: 0.0059, val loss: 0.0686
Epoch 0, train loss: 0.0244, val loss: 0.2864
Epoch 10, train loss: 0.0484, val loss: 0.1417
Epoch 20, train loss: 0.0264, val loss: 0.1031
Epoch 30, train loss: 0.0233, val loss: 0.0374
Epoch 40, train loss: 0.0059, val loss: 0.0686
Epoch 50, train loss: 0.0089, val loss: 0.0159
Epoch 60, train loss: 0.0054, val loss: 0.0165
Epoch 70, train loss: 0.0055, val loss: 0.0349
Epoch 0, train loss: 0.0244, val loss: 0.0747
Epoch 10, train loss: 0.0070, val loss: 0.0496
Epoch 20, train loss: 0.0054, val loss: 0.0199
Epoch 30, train loss: 0.0051, val loss: 0.0204
Epoch 0, train loss: 0.0244, val loss: 0.0747
Epoch 10, train loss: 0.0070, val loss: 0.0496
Epoch 20, train loss: 0.0054, val loss: 0.0199
Epoch 30, train loss: 0.0051, val loss: 0.0204
Inferred coeffs for Ukraine: [ 1.0877675   1.2017258   0.78912175  0.5706409   0.9407094   1.295672
 -2.9033518  -0.5902608   0.18021488  0.08408555 -1.3622032  -0.00833723
  0.00483603 -4.6089807   2.4910293  -0.02109325 -1.4223987   0.8707723 ]
Epoch 0, train loss: 0.0169, val loss: 0.3168
Epoch 10, train loss: 0.0555, val loss: 0.1821
Epoch 20, train loss: 0.0194, val loss: 0.0489
Epoch 30, train loss: 0.0071, val loss: 0.0587
Epoch 40, train loss: 0.0043, val loss: 0.0076
Epoch 0, train loss: 0.0169, val loss: 0.3168
Epoch 10, train loss: 0.0555, val loss: 0.1821
Epoch 20, train loss: 0.0194, val loss: 0.0489
Epoch 30, train loss: 0.0071, val loss: 0.0587
Epoch 40, train loss: 0.0043, val loss: 0.0076
Epoch 50, train loss: 0.0046, val loss: 0.0256
Epoch 60, train loss: 0.0040, val loss: 0.0036
Epoch 0, train loss: 0.0169, val loss: 0.0339
Epoch 10, train loss: 0.0006, val loss: 0.0040
Epoch 20, train loss: 0.0027, val loss: 0.0040
Epoch 30, train loss: 0.0010, val loss: 0.0123
Epoch 0, train loss: 0.0169, val loss: 0.0339
Epoch 10, train loss: 0.0006, val loss: 0.0040
Epoch 20, train loss: 0.0027, val loss: 0.0040
Epoch 30, train loss: 0.0010, val loss: 0.0123
Inferred coeffs for Belarus: [ 1.0866698   1.2006403   0.7880159   0.5717808   0.93960935  1.2967795
 -2.9044657  -0.5891799   0.17911148  0.08518153 -1.3632917  -0.0094349
  0.0059337  -4.609463    2.4915152  -0.01999543 -1.4213992   0.86976457]
Epoch 0, train loss: 0.0699, val loss: 0.2089
Epoch 10, train loss: 0.0214, val loss: 0.0382
Epoch 20, train loss: 0.0087, val loss: 0.0166
Epoch 30, train loss: 0.0080, val loss: 0.0432
Epoch 0, train loss: 0.0699, val loss: 0.2089
Epoch 10, train loss: 0.0214, val loss: 0.0382
Epoch 20, train loss: 0.0087, val loss: 0.0166
Epoch 30, train loss: 0.0080, val loss: 0.0432
Epoch 0, train loss: 0.0699, val loss: 0.1417
Epoch 10, train loss: 0.0204, val loss: 0.1360
Epoch 20, train loss: 0.0115, val loss: 0.0232
Epoch 30, train loss: 0.0086, val loss: 0.0836
Epoch 0, train loss: 0.0699, val loss: 0.1417
Epoch 10, train loss: 0.0204, val loss: 0.1360
Epoch 20, train loss: 0.0115, val loss: 0.0232
Epoch 30, train loss: 0.0086, val loss: 0.0836
Inferred coeffs for Tajikistan: [ 1.0896744e+00  1.2036473e+00  7.9101872e-01  5.6878620e-01
  9.4261342e-01  1.2937771e+00 -2.9014645e+00 -5.9218764e-01
  1.8211472e-01  8.2176715e-02 -1.3602854e+00 -6.4303903e-03
  2.9291909e-03 -4.6094255e+00  2.4914777e+00 -2.2999909e-02
 -1.4244148e+00  8.7277919e-01]
Epoch 0, train loss: 0.0282, val loss: 0.2860
Epoch 10, train loss: 0.0442, val loss: 0.1517
Epoch 20, train loss: 0.0233, val loss: 0.0904
Epoch 30, train loss: 0.0087, val loss: 0.0411
Epoch 40, train loss: 0.0043, val loss: 0.0299
Epoch 0, train loss: 0.0282, val loss: 0.2860
Epoch 10, train loss: 0.0442, val loss: 0.1517
Epoch 20, train loss: 0.0233, val loss: 0.0904
Epoch 30, train loss: 0.0087, val loss: 0.0411
Epoch 40, train loss: 0.0043, val loss: 0.0299
Epoch 50, train loss: 0.0119, val loss: 0.0168
Epoch 60, train loss: 0.0052, val loss: 0.0201
Epoch 0, train loss: 0.0282, val loss: 0.0643
Epoch 10, train loss: 0.0057, val loss: 0.0313
Epoch 20, train loss: 0.0039, val loss: 0.0021
Epoch 30, train loss: 0.0041, val loss: 0.0078
Epoch 40, train loss: 0.0034, val loss: 0.0022
Epoch 0, train loss: 0.0282, val loss: 0.0643
Epoch 10, train loss: 0.0057, val loss: 0.0313
Epoch 20, train loss: 0.0039, val loss: 0.0021
Epoch 30, train loss: 0.0041, val loss: 0.0078
Epoch 40, train loss: 0.0034, val loss: 0.0022
Epoch 50, train loss: 0.0034, val loss: 0.0041
Epoch 60, train loss: 0.0034, val loss: 0.0038
Inferred coeffs for Uzbekistan: [ 1.0881120e+00  1.1947381e+00  7.9456985e-01  5.4327959e-01
  9.4266713e-01  1.2890166e+00 -2.8928308e+00 -5.8038533e-01
  1.8442969e-01  8.4517628e-02 -1.3673323e+00 -7.9869432e-03
  4.4857147e-03 -4.6023016e+00  2.4842558e+00 -2.1536438e-02
 -1.3675399e+00  8.2038999e-01]
Epoch 0, train loss: 0.0175, val loss: 0.3012
Epoch 10, train loss: 0.0548, val loss: 0.1677
Epoch 20, train loss: 0.0190, val loss: 0.0353
Epoch 30, train loss: 0.0068, val loss: 0.0718
Epoch 40, train loss: 0.0030, val loss: 0.0213
Epoch 0, train loss: 0.0175, val loss: 0.3012
Epoch 10, train loss: 0.0548, val loss: 0.1677
Epoch 20, train loss: 0.0190, val loss: 0.0353
Epoch 30, train loss: 0.0068, val loss: 0.0718
Epoch 40, train loss: 0.0030, val loss: 0.0213
Epoch 50, train loss: 0.0103, val loss: 0.0144
Epoch 60, train loss: 0.0106, val loss: 0.0302
Epoch 70, train loss: 0.0197, val loss: 0.0743
Epoch 80, train loss: 0.0087, val loss: 0.0513
Epoch 0, train loss: 0.0175, val loss: 0.0483
Epoch 10, train loss: 0.0021, val loss: 0.0185
Epoch 20, train loss: 0.0019, val loss: 0.0261
Epoch 30, train loss: 0.0015, val loss: 0.0264
Epoch 0, train loss: 0.0175, val loss: 0.0483
Epoch 10, train loss: 0.0021, val loss: 0.0185
Epoch 20, train loss: 0.0019, val loss: 0.0261
Epoch 30, train loss: 0.0015, val loss: 0.0264
Inferred coeffs for Bangladesh: [ 1.0879157   1.192951    0.7954663   0.5376329   0.9427389   1.2879204
 -2.8908813  -0.577863    0.18498766  0.08500032 -1.3688422  -0.00818346
  0.00468221 -4.6037164   2.4856672  -0.02135609 -1.3538253   0.807647  ]
Epoch 0, train loss: 0.0350, val loss: 0.2454
Epoch 10, train loss: 0.0374, val loss: 0.1108
Epoch 20, train loss: 0.0086, val loss: 0.0497
Epoch 30, train loss: 0.0052, val loss: 0.0338
Epoch 40, train loss: 0.0055, val loss: 0.0068
Epoch 0, train loss: 0.0350, val loss: 0.2454
Epoch 10, train loss: 0.0374, val loss: 0.1108
Epoch 20, train loss: 0.0086, val loss: 0.0497
Epoch 30, train loss: 0.0052, val loss: 0.0338
Epoch 40, train loss: 0.0055, val loss: 0.0068
Epoch 50, train loss: 0.0092, val loss: 0.0035
Epoch 60, train loss: 0.0105, val loss: 0.0063
Epoch 70, train loss: 0.0049, val loss: 0.0051
Epoch 80, train loss: 0.0052, val loss: 0.0288
Epoch 90, train loss: 0.0051, val loss: 0.0026
Epoch 0, train loss: 0.0350, val loss: 0.1053
Epoch 10, train loss: 0.0059, val loss: 0.0377
Epoch 20, train loss: 0.0054, val loss: 0.0123
Epoch 30, train loss: 0.0051, val loss: 0.0079
Epoch 0, train loss: 0.0350, val loss: 0.1053
Epoch 10, train loss: 0.0059, val loss: 0.0377
Epoch 20, train loss: 0.0054, val loss: 0.0123
Epoch 30, train loss: 0.0051, val loss: 0.0079
Inferred coeffs for Indonesia: [ 1.0886693e+00  1.2026085e+00  7.9003680e-01  5.6967074e-01
  9.4161618e-01  1.2947536e+00 -2.9024239e+00 -5.9113693e-01
  1.8112588e-01  8.3185956e-02 -1.3613153e+00 -7.4352636e-03
  3.9340630e-03 -4.6093450e+00  2.4913960e+00 -2.1995418e-02
 -1.4231529e+00  8.7153882e-01]
Epoch 0, train loss: 0.0335, val loss: 0.3377
Epoch 10, train loss: 0.0399, val loss: 0.1732
Epoch 20, train loss: 0.0194, val loss: 0.0298
Epoch 30, train loss: 0.0156, val loss: 0.0115
Epoch 40, train loss: 0.0054, val loss: 0.0018
Epoch 0, train loss: 0.0335, val loss: 0.3377
Epoch 10, train loss: 0.0399, val loss: 0.1732
Epoch 20, train loss: 0.0194, val loss: 0.0298
Epoch 30, train loss: 0.0156, val loss: 0.0115
Epoch 40, train loss: 0.0054, val loss: 0.0018
Epoch 50, train loss: 0.0053, val loss: 0.0132
Epoch 60, train loss: 0.0053, val loss: 0.0139
Epoch 70, train loss: 0.0053, val loss: 0.0179
Epoch 0, train loss: 0.0335, val loss: 0.0429
Epoch 10, train loss: 0.0054, val loss: 0.0081
Epoch 20, train loss: 0.0076, val loss: 0.0493
Epoch 30, train loss: 0.0056, val loss: 0.0247
Epoch 40, train loss: 0.0055, val loss: 0.0198
Epoch 0, train loss: 0.0335, val loss: 0.0429
Epoch 10, train loss: 0.0054, val loss: 0.0081
Epoch 20, train loss: 0.0076, val loss: 0.0493
Epoch 30, train loss: 0.0056, val loss: 0.0247
Epoch 40, train loss: 0.0055, val loss: 0.0198
Inferred coeffs for China: [ 1.0870864   1.1934297   0.7938369   0.54254395  0.94167656  1.2895875
 -2.8934133  -0.5789929   0.18431832  0.08503161 -1.3682736  -0.00901738
  0.00551613 -4.551286    2.4326477  -0.02051493 -1.3672409   0.8202503 ]
Epoch 0, train loss: 0.0203, val loss: 0.3235
Epoch 10, train loss: 0.0523, val loss: 0.1842
Epoch 20, train loss: 0.0154, val loss: 0.0480
Epoch 30, train loss: 0.0027, val loss: 0.0611
Epoch 40, train loss: 0.0013, val loss: 0.0375
Epoch 0, train loss: 0.0203, val loss: 0.3235
Epoch 10, train loss: 0.0523, val loss: 0.1842
Epoch 20, train loss: 0.0154, val loss: 0.0480
Epoch 30, train loss: 0.0027, val loss: 0.0611
Epoch 40, train loss: 0.0013, val loss: 0.0375
Epoch 50, train loss: 0.0187, val loss: 0.0200
Epoch 60, train loss: 0.0067, val loss: 0.0090
Epoch 0, train loss: 0.0203, val loss: 0.0320
Epoch 10, train loss: 0.0043, val loss: 0.0065
Epoch 20, train loss: 0.0013, val loss: 0.0005
Epoch 30, train loss: 0.0013, val loss: 0.0008
Epoch 40, train loss: 0.0010, val loss: 0.0011
Epoch 0, train loss: 0.0203, val loss: 0.0320
Epoch 10, train loss: 0.0043, val loss: 0.0065
Epoch 20, train loss: 0.0013, val loss: 0.0005
Epoch 30, train loss: 0.0013, val loss: 0.0008
Epoch 40, train loss: 0.0010, val loss: 0.0011
Epoch 50, train loss: 0.0012, val loss: 0.0012
Epoch 60, train loss: 0.0010, val loss: 0.0034
Inferred coeffs for Latvia: [ 1.0866092   1.2005012   0.78800774  0.5715728   0.9395658   1.2967778
 -2.9044218  -0.589012    0.17907979  0.08525851 -1.363414   -0.0094958
  0.0059946  -4.6091638   2.49121    -0.01993529 -1.4206846   0.86909926]
Epoch 0, train loss: 0.0197, val loss: 0.3148
Epoch 10, train loss: 0.0529, val loss: 0.1770
Epoch 20, train loss: 0.0162, val loss: 0.0418
Epoch 30, train loss: 0.0037, val loss: 0.0668
Epoch 40, train loss: 0.0023, val loss: 0.0185
Epoch 0, train loss: 0.0197, val loss: 0.3148
Epoch 10, train loss: 0.0529, val loss: 0.1770
Epoch 20, train loss: 0.0162, val loss: 0.0418
Epoch 30, train loss: 0.0037, val loss: 0.0668
Epoch 40, train loss: 0.0023, val loss: 0.0185
Epoch 50, train loss: 0.0033, val loss: 0.0101
Epoch 60, train loss: 0.0087, val loss: 0.0038
Epoch 70, train loss: 0.0071, val loss: 0.0164
Epoch 80, train loss: 0.0078, val loss: 0.0270
Epoch 0, train loss: 0.0197, val loss: 0.0391
Epoch 10, train loss: 0.0067, val loss: 0.0260
Epoch 20, train loss: 0.0034, val loss: 0.0182
Epoch 30, train loss: 0.0025, val loss: 0.0102
Epoch 40, train loss: 0.0024, val loss: 0.0076
Epoch 0, train loss: 0.0197, val loss: 0.0391
Epoch 10, train loss: 0.0067, val loss: 0.0260
Epoch 20, train loss: 0.0034, val loss: 0.0182
Epoch 30, train loss: 0.0025, val loss: 0.0102
Epoch 40, train loss: 0.0024, val loss: 0.0076
Epoch 50, train loss: 0.0022, val loss: 0.0042
Inferred coeffs for Lithuania: [ 1.0868323   1.2007146   0.78823674  0.5713147   0.93978894  1.2965472
 -2.9041874  -0.58922213  0.1793115   0.08503396 -1.3631968  -0.00927287
  0.00577166 -4.609215    2.4912603  -0.02015844 -1.4208511   0.8692742 ]
Epoch 0, train loss: 0.0213, val loss: 0.3082
Epoch 10, train loss: 0.0510, val loss: 0.1753
Epoch 20, train loss: 0.0153, val loss: 0.0433
Epoch 30, train loss: 0.0031, val loss: 0.0636
Epoch 40, train loss: 0.0030, val loss: 0.0290
Epoch 0, train loss: 0.0213, val loss: 0.3082
Epoch 10, train loss: 0.0510, val loss: 0.1753
Epoch 20, train loss: 0.0153, val loss: 0.0433
Epoch 30, train loss: 0.0031, val loss: 0.0636
Epoch 40, train loss: 0.0030, val loss: 0.0290
Epoch 50, train loss: 0.0061, val loss: 0.0398
Epoch 60, train loss: 0.0058, val loss: 0.0252
Epoch 70, train loss: 0.0021, val loss: 0.0207
Epoch 80, train loss: 0.0058, val loss: 0.0442
Epoch 0, train loss: 0.0213, val loss: 0.0406
Epoch 10, train loss: 0.0066, val loss: 0.0258
Epoch 20, train loss: 0.0033, val loss: 0.0170
Epoch 30, train loss: 0.0027, val loss: 0.0126
Epoch 40, train loss: 0.0024, val loss: 0.0076
Epoch 0, train loss: 0.0213, val loss: 0.0406
Epoch 10, train loss: 0.0066, val loss: 0.0258
Epoch 20, train loss: 0.0033, val loss: 0.0170
Epoch 30, train loss: 0.0027, val loss: 0.0126
Epoch 40, train loss: 0.0024, val loss: 0.0076
Epoch 50, train loss: 0.0020, val loss: 0.0017
Inferred coeffs for Armenia: [ 1.0868613   1.2007365   0.78827196  0.571256    0.9398203   1.2965107
 -2.9041467  -0.5892417   0.17934668  0.08500383 -1.3631718  -0.00924299
  0.00574179 -4.60948     2.4915304  -0.02018834 -1.4208372   0.8692628 ]
Epoch 0, train loss: 0.0217, val loss: 0.3035
Epoch 10, train loss: 0.0506, val loss: 0.1714
Epoch 20, train loss: 0.0250, val loss: 0.1025
Epoch 30, train loss: 0.0142, val loss: 0.0018
Epoch 40, train loss: 0.0075, val loss: 0.0070
Epoch 0, train loss: 0.0217, val loss: 0.3035
Epoch 10, train loss: 0.0506, val loss: 0.1714
Epoch 20, train loss: 0.0250, val loss: 0.1025
Epoch 30, train loss: 0.0142, val loss: 0.0018
Epoch 40, train loss: 0.0075, val loss: 0.0070
Epoch 50, train loss: 0.0079, val loss: 0.0052
Epoch 60, train loss: 0.0040, val loss: 0.0164
Epoch 70, train loss: 0.0054, val loss: 0.0040
Epoch 80, train loss: 0.0056, val loss: 0.0141
Epoch 0, train loss: 0.0217, val loss: 0.0444
Epoch 10, train loss: 0.0068, val loss: 0.0251
Epoch 20, train loss: 0.0037, val loss: 0.0186
Epoch 30, train loss: 0.0035, val loss: 0.0016
Epoch 40, train loss: 0.0033, val loss: 0.0035
Epoch 0, train loss: 0.0217, val loss: 0.0444
Epoch 10, train loss: 0.0068, val loss: 0.0251
Epoch 20, train loss: 0.0037, val loss: 0.0186
Epoch 30, train loss: 0.0035, val loss: 0.0016
Epoch 40, train loss: 0.0033, val loss: 0.0035
Epoch 50, train loss: 0.0033, val loss: 0.0071
Epoch 60, train loss: 0.0033, val loss: 0.0071
Inferred coeffs for Djibouti: [ 1.0877551   1.1927134   0.79536957  0.53750634  0.94267553  1.2879595
 -2.8908944  -0.577606    0.18481454  0.08519113 -1.3690611  -0.00834772
  0.00484647 -4.607695    2.489717   -0.02118327 -1.3534347   0.8070869 ]
Epoch 0, train loss: 0.0160, val loss: 0.3255
Epoch 10, train loss: 0.0562, val loss: 0.1935
Epoch 20, train loss: 0.0207, val loss: 0.0622
Epoch 30, train loss: 0.0087, val loss: 0.0444
Epoch 40, train loss: 0.0207, val loss: 0.0528
Epoch 0, train loss: 0.0160, val loss: 0.3255
Epoch 10, train loss: 0.0562, val loss: 0.1935
Epoch 20, train loss: 0.0207, val loss: 0.0622
Epoch 30, train loss: 0.0087, val loss: 0.0444
Epoch 40, train loss: 0.0207, val loss: 0.0528
Epoch 50, train loss: 0.0320, val loss: 0.0757
Epoch 60, train loss: 0.0325, val loss: 0.0851
Epoch 0, train loss: 0.0160, val loss: 0.0223
Epoch 10, train loss: 0.0008, val loss: 0.0036
Epoch 20, train loss: 0.0009, val loss: 0.0072
Epoch 30, train loss: 0.0005, val loss: 0.0041
Epoch 40, train loss: 0.0004, val loss: 0.0052
Epoch 0, train loss: 0.0160, val loss: 0.0223
Epoch 10, train loss: 0.0008, val loss: 0.0036
Epoch 20, train loss: 0.0009, val loss: 0.0072
Epoch 30, train loss: 0.0005, val loss: 0.0041
Epoch 40, train loss: 0.0004, val loss: 0.0052
Epoch 50, train loss: 0.0003, val loss: 0.0051
Inferred coeffs for Guinea-Bissau: [ 1.0863241   1.2002307   0.78771234  0.57190734  0.9392741   1.2970755
 -2.9047291  -0.5887474   0.1787962   0.0855359  -1.363685   -0.00978076
  0.00627956 -4.6095557   2.4916077  -0.01965023 -1.4205486   0.8689528 ]