-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathtrain.log
More file actions
253 lines (252 loc) · 21.2 KB
/
Copy pathtrain.log
File metadata and controls
253 lines (252 loc) · 21.2 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
Starting Training Workflow
============================================================
1: Loading data from JSON file...
Loading molecular data from: data/compressed_graph_data.json
Processing 25214 molecules...
Successfully loaded 25214 molecules
Graph sizes (first 3): [(41, 41), (41, 41), (23, 23)]
Sample atoms (first 2): [['C', 'C', 'H', 'C', 'C', 'H', 'C', 'H', 'C', 'H', 'C', 'C', 'C', 'H', 'C', 'C', 'H', 'C', 'H', 'C', 'H', 'C', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'O', 'Cl', 'Cl', 'Ni', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H'], ['Ni', 'N', 'C', 'C', 'N', 'H', 'H', 'H', 'H', 'H', 'H', 'C', 'C', 'N', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'N', 'C', 'C', 'N', 'C', 'C', 'N', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H', 'H']]
Eq BL range: 1.611 - 2.955
Ax BL range: 1.451 - 3.460
2: Initializing atom featurizer...
3: Splitting data...
Training set: 16388 | Validation set: 3783 | Test set: 5043
Predicting: both bond lengths
4: Creating datasets...
Dataset initialized with 16388 molecules
Max graph size: 511
Feature dimension: 4
Target type: both
Output dimension: 2
Dataset initialized with 3783 molecules
Max graph size: 301
Feature dimension: 4
Target type: both
Output dimension: 2
Dataset initialized with 5043 molecules
Max graph size: 667
Feature dimension: 4
Target type: both
Output dimension: 2
5: Creating data loaders (bucketed by graph size)...
6: Initializing MPNN model...
MPNN Model Architecture:
Node dim: 4
Edge dim: 16
Message dim: 64
Readout dim: 128
Number of MP layers: 3
Parameters: 29,539
7: Training model...
Starting training for 200 epochs...
Learning rate: 0.0001 | Device: cuda
Epoch 1/200 | Train Loss: 0.673535 | Val Loss: 0.024220 | Val MAE: 0.109537 | Val R²: -0.092760
Epoch 2/200 | Train Loss: 0.078782 | Val Loss: 0.024217 | Val MAE: 0.109766 | Val R²: -0.107035
Epoch 3/200 | Train Loss: 0.068878 | Val Loss: 0.024124 | Val MAE: 0.109655 | Val R²: -0.101175
Epoch 4/200 | Train Loss: 0.065316 | Val Loss: 0.021827 | Val MAE: 0.110202 | Val R²: 0.029180
Epoch 5/200 | Train Loss: 0.061774 | Val Loss: 0.021806 | Val MAE: 0.104948 | Val R²: 0.025886
Epoch 6/200 | Train Loss: 0.058970 | Val Loss: 0.021310 | Val MAE: 0.108734 | Val R²: 0.056196
Epoch 7/200 | Train Loss: 0.056738 | Val Loss: 0.021101 | Val MAE: 0.103494 | Val R²: 0.065658
Epoch 8/200 | Train Loss: 0.055532 | Val Loss: 0.021013 | Val MAE: 0.102703 | Val R²: 0.063087
Epoch 9/200 | Train Loss: 0.054698 | Val Loss: 0.021736 | Val MAE: 0.102648 | Val R²: 0.022475
Epoch 10/200 | Train Loss: 0.052741 | Val Loss: 0.021256 | Val MAE: 0.103153 | Val R²: 0.047638
Epoch 11/200 | Train Loss: 0.050551 | Val Loss: 0.019586 | Val MAE: 0.102989 | Val R²: 0.125260
Epoch 12/200 | Train Loss: 0.049261 | Val Loss: 0.019510 | Val MAE: 0.103625 | Val R²: 0.125491
Epoch 13/200 | Train Loss: 0.048574 | Val Loss: 0.019055 | Val MAE: 0.100078 | Val R²: 0.149048
Epoch 14/200 | Train Loss: 0.047946 | Val Loss: 0.019186 | Val MAE: 0.100451 | Val R²: 0.131580
Epoch 15/200 | Train Loss: 0.045877 | Val Loss: 0.018708 | Val MAE: 0.099357 | Val R²: 0.158309
Epoch 16/200 | Train Loss: 0.045125 | Val Loss: 0.018575 | Val MAE: 0.098387 | Val R²: 0.166340
Epoch 17/200 | Train Loss: 0.044652 | Val Loss: 0.019063 | Val MAE: 0.103061 | Val R²: 0.142483
Epoch 18/200 | Train Loss: 0.043356 | Val Loss: 0.019861 | Val MAE: 0.108231 | Val R²: 0.107004
Epoch 19/200 | Train Loss: 0.043285 | Val Loss: 0.020615 | Val MAE: 0.099053 | Val R²: 0.051155
Epoch 20/200 | Train Loss: 0.041842 | Val Loss: 0.018575 | Val MAE: 0.095421 | Val R²: 0.167300
Epoch 21/200 | Train Loss: 0.041992 | Val Loss: 0.019340 | Val MAE: 0.096454 | Val R²: 0.126271
Epoch 22/200 | Train Loss: 0.041919 | Val Loss: 0.019501 | Val MAE: 0.096125 | Val R²: 0.107996
Epoch 23/200 | Train Loss: 0.040306 | Val Loss: 0.021043 | Val MAE: 0.101922 | Val R²: 0.027589
Epoch 24/200 | Train Loss: 0.040129 | Val Loss: 0.018371 | Val MAE: 0.098009 | Val R²: 0.176885
Epoch 25/200 | Train Loss: 0.039242 | Val Loss: 0.018147 | Val MAE: 0.099381 | Val R²: 0.184640
Epoch 26/200 | Train Loss: 0.038147 | Val Loss: 0.017972 | Val MAE: 0.096831 | Val R²: 0.195015
Epoch 27/200 | Train Loss: 0.037533 | Val Loss: 0.019138 | Val MAE: 0.095813 | Val R²: 0.128224
Epoch 28/200 | Train Loss: 0.037219 | Val Loss: 0.018206 | Val MAE: 0.096142 | Val R²: 0.178358
Epoch 29/200 | Train Loss: 0.036105 | Val Loss: 0.017708 | Val MAE: 0.095864 | Val R²: 0.202236
Epoch 30/200 | Train Loss: 0.036364 | Val Loss: 0.017669 | Val MAE: 0.097489 | Val R²: 0.209194
Epoch 31/200 | Train Loss: 0.035241 | Val Loss: 0.019624 | Val MAE: 0.096613 | Val R²: 0.094165
Epoch 32/200 | Train Loss: 0.034144 | Val Loss: 0.017817 | Val MAE: 0.098389 | Val R²: 0.196928
Epoch 33/200 | Train Loss: 0.034146 | Val Loss: 0.018206 | Val MAE: 0.092815 | Val R²: 0.167660
Epoch 34/200 | Train Loss: 0.033361 | Val Loss: 0.017161 | Val MAE: 0.091626 | Val R²: 0.228083
Epoch 35/200 | Train Loss: 0.033124 | Val Loss: 0.017012 | Val MAE: 0.096667 | Val R²: 0.238912
Epoch 36/200 | Train Loss: 0.032179 | Val Loss: 0.018168 | Val MAE: 0.093000 | Val R²: 0.185387
Epoch 37/200 | Train Loss: 0.031493 | Val Loss: 0.019411 | Val MAE: 0.096154 | Val R²: 0.089189
Epoch 38/200 | Train Loss: 0.030726 | Val Loss: 0.016168 | Val MAE: 0.091708 | Val R²: 0.271021
Epoch 39/200 | Train Loss: 0.030172 | Val Loss: 0.016247 | Val MAE: 0.093968 | Val R²: 0.270144
Epoch 40/200 | Train Loss: 0.030393 | Val Loss: 0.019022 | Val MAE: 0.092995 | Val R²: 0.136614
Epoch 41/200 | Train Loss: 0.029331 | Val Loss: 0.019021 | Val MAE: 0.094263 | Val R²: 0.135321
Epoch 42/200 | Train Loss: 0.028960 | Val Loss: 0.015394 | Val MAE: 0.089466 | Val R²: 0.301627
Epoch 43/200 | Train Loss: 0.028806 | Val Loss: 0.015920 | Val MAE: 0.088914 | Val R²: 0.280648
Epoch 44/200 | Train Loss: 0.028324 | Val Loss: 0.015215 | Val MAE: 0.090376 | Val R²: 0.306606
Epoch 45/200 | Train Loss: 0.027301 | Val Loss: 0.016235 | Val MAE: 0.088965 | Val R²: 0.265167
Epoch 46/200 | Train Loss: 0.026739 | Val Loss: 0.015139 | Val MAE: 0.087116 | Val R²: 0.307551
Epoch 47/200 | Train Loss: 0.025882 | Val Loss: 0.014899 | Val MAE: 0.084404 | Val R²: 0.331050
Epoch 48/200 | Train Loss: 0.025358 | Val Loss: 0.014828 | Val MAE: 0.084895 | Val R²: 0.329032
Epoch 49/200 | Train Loss: 0.025319 | Val Loss: 0.014524 | Val MAE: 0.086629 | Val R²: 0.335565
Epoch 50/200 | Train Loss: 0.024443 | Val Loss: 0.014349 | Val MAE: 0.088624 | Val R²: 0.354636
Epoch 51/200 | Train Loss: 0.024505 | Val Loss: 0.014054 | Val MAE: 0.087035 | Val R²: 0.363950
Epoch 52/200 | Train Loss: 0.024019 | Val Loss: 0.014122 | Val MAE: 0.084078 | Val R²: 0.366887
Epoch 53/200 | Train Loss: 0.023238 | Val Loss: 0.014629 | Val MAE: 0.091923 | Val R²: 0.336578
Epoch 54/200 | Train Loss: 0.022798 | Val Loss: 0.015763 | Val MAE: 0.099172 | Val R²: 0.274737
Epoch 55/200 | Train Loss: 0.022655 | Val Loss: 0.013816 | Val MAE: 0.088404 | Val R²: 0.365825
Epoch 56/200 | Train Loss: 0.022720 | Val Loss: 0.013216 | Val MAE: 0.083146 | Val R²: 0.383618
Epoch 57/200 | Train Loss: 0.022316 | Val Loss: 0.013998 | Val MAE: 0.089888 | Val R²: 0.360796
Epoch 58/200 | Train Loss: 0.021603 | Val Loss: 0.013484 | Val MAE: 0.082542 | Val R²: 0.374817
Epoch 59/200 | Train Loss: 0.021257 | Val Loss: 0.012633 | Val MAE: 0.080686 | Val R²: 0.401647
Epoch 60/200 | Train Loss: 0.020617 | Val Loss: 0.012166 | Val MAE: 0.081505 | Val R²: 0.411904
Epoch 61/200 | Train Loss: 0.020106 | Val Loss: 0.013116 | Val MAE: 0.086156 | Val R²: 0.382579
Epoch 62/200 | Train Loss: 0.019674 | Val Loss: 0.011549 | Val MAE: 0.080446 | Val R²: 0.435890
Epoch 63/200 | Train Loss: 0.019132 | Val Loss: 0.011379 | Val MAE: 0.078951 | Val R²: 0.452876
Epoch 64/200 | Train Loss: 0.018659 | Val Loss: 0.011577 | Val MAE: 0.078314 | Val R²: 0.441847
Epoch 65/200 | Train Loss: 0.017950 | Val Loss: 0.010503 | Val MAE: 0.074641 | Val R²: 0.488988
Epoch 66/200 | Train Loss: 0.017676 | Val Loss: 0.010767 | Val MAE: 0.076753 | Val R²: 0.487532
Epoch 67/200 | Train Loss: 0.017573 | Val Loss: 0.011063 | Val MAE: 0.074969 | Val R²: 0.481495
Epoch 68/200 | Train Loss: 0.016941 | Val Loss: 0.010312 | Val MAE: 0.075515 | Val R²: 0.502161
Epoch 69/200 | Train Loss: 0.016744 | Val Loss: 0.010319 | Val MAE: 0.072359 | Val R²: 0.504318
Epoch 70/200 | Train Loss: 0.016450 | Val Loss: 0.009959 | Val MAE: 0.071249 | Val R²: 0.521300
Epoch 71/200 | Train Loss: 0.016652 | Val Loss: 0.010926 | Val MAE: 0.078689 | Val R²: 0.487085
Epoch 72/200 | Train Loss: 0.016176 | Val Loss: 0.010009 | Val MAE: 0.073706 | Val R²: 0.521413
Epoch 73/200 | Train Loss: 0.016048 | Val Loss: 0.009809 | Val MAE: 0.071651 | Val R²: 0.530552
Epoch 74/200 | Train Loss: 0.016019 | Val Loss: 0.009589 | Val MAE: 0.069463 | Val R²: 0.542348
Epoch 75/200 | Train Loss: 0.015754 | Val Loss: 0.009436 | Val MAE: 0.070064 | Val R²: 0.548296
Epoch 76/200 | Train Loss: 0.015516 | Val Loss: 0.009576 | Val MAE: 0.071448 | Val R²: 0.540771
Epoch 77/200 | Train Loss: 0.015419 | Val Loss: 0.009853 | Val MAE: 0.069940 | Val R²: 0.524009
Epoch 78/200 | Train Loss: 0.015154 | Val Loss: 0.009465 | Val MAE: 0.067838 | Val R²: 0.550518
Epoch 79/200 | Train Loss: 0.015040 | Val Loss: 0.009980 | Val MAE: 0.068425 | Val R²: 0.530046
Epoch 80/200 | Train Loss: 0.014996 | Val Loss: 0.010671 | Val MAE: 0.073511 | Val R²: 0.500108
Epoch 81/200 | Train Loss: 0.014850 | Val Loss: 0.010584 | Val MAE: 0.073560 | Val R²: 0.505895
Epoch 82/200 | Train Loss: 0.014806 | Val Loss: 0.009735 | Val MAE: 0.072132 | Val R²: 0.536977
Epoch 83/200 | Train Loss: 0.014540 | Val Loss: 0.009403 | Val MAE: 0.069702 | Val R²: 0.551446
Epoch 84/200 | Train Loss: 0.014554 | Val Loss: 0.010090 | Val MAE: 0.072712 | Val R²: 0.520616
Epoch 85/200 | Train Loss: 0.014387 | Val Loss: 0.009423 | Val MAE: 0.068101 | Val R²: 0.549079
Epoch 86/200 | Train Loss: 0.014447 | Val Loss: 0.009187 | Val MAE: 0.070256 | Val R²: 0.556410
Epoch 87/200 | Train Loss: 0.014241 | Val Loss: 0.010772 | Val MAE: 0.072241 | Val R²: 0.493506
Epoch 88/200 | Train Loss: 0.014196 | Val Loss: 0.009205 | Val MAE: 0.068382 | Val R²: 0.560054
Epoch 89/200 | Train Loss: 0.013976 | Val Loss: 0.009514 | Val MAE: 0.072148 | Val R²: 0.544020
Epoch 90/200 | Train Loss: 0.014062 | Val Loss: 0.010512 | Val MAE: 0.076145 | Val R²: 0.508847
Epoch 91/200 | Train Loss: 0.014052 | Val Loss: 0.008941 | Val MAE: 0.066618 | Val R²: 0.572337
Epoch 92/200 | Train Loss: 0.013606 | Val Loss: 0.009286 | Val MAE: 0.067735 | Val R²: 0.553941
Epoch 93/200 | Train Loss: 0.013716 | Val Loss: 0.009234 | Val MAE: 0.068701 | Val R²: 0.557540
Epoch 94/200 | Train Loss: 0.013605 | Val Loss: 0.009137 | Val MAE: 0.069349 | Val R²: 0.561871
Epoch 95/200 | Train Loss: 0.013360 | Val Loss: 0.009053 | Val MAE: 0.067412 | Val R²: 0.568330
Epoch 96/200 | Train Loss: 0.013110 | Val Loss: 0.009168 | Val MAE: 0.070261 | Val R²: 0.559626
Epoch 97/200 | Train Loss: 0.013280 | Val Loss: 0.009380 | Val MAE: 0.068460 | Val R²: 0.548765
Epoch 98/200 | Train Loss: 0.013130 | Val Loss: 0.009126 | Val MAE: 0.066226 | Val R²: 0.562680
Epoch 99/200 | Train Loss: 0.013120 | Val Loss: 0.008828 | Val MAE: 0.067702 | Val R²: 0.576009
Epoch 100/200 | Train Loss: 0.013155 | Val Loss: 0.008943 | Val MAE: 0.066226 | Val R²: 0.571945
Epoch 101/200 | Train Loss: 0.012895 | Val Loss: 0.009120 | Val MAE: 0.070561 | Val R²: 0.560936
Epoch 102/200 | Train Loss: 0.012768 | Val Loss: 0.008692 | Val MAE: 0.066200 | Val R²: 0.583190
Epoch 103/200 | Train Loss: 0.012841 | Val Loss: 0.009073 | Val MAE: 0.069345 | Val R²: 0.563121
Epoch 104/200 | Train Loss: 0.012541 | Val Loss: 0.009137 | Val MAE: 0.068283 | Val R²: 0.563579
Epoch 105/200 | Train Loss: 0.012664 | Val Loss: 0.009275 | Val MAE: 0.069365 | Val R²: 0.557369
Epoch 106/200 | Train Loss: 0.012706 | Val Loss: 0.008892 | Val MAE: 0.066566 | Val R²: 0.577725
Epoch 107/200 | Train Loss: 0.012582 | Val Loss: 0.009197 | Val MAE: 0.067702 | Val R²: 0.563486
Epoch 108/200 | Train Loss: 0.012387 | Val Loss: 0.008585 | Val MAE: 0.064478 | Val R²: 0.587801
Epoch 109/200 | Train Loss: 0.012554 | Val Loss: 0.009061 | Val MAE: 0.066685 | Val R²: 0.569001
Epoch 110/200 | Train Loss: 0.012383 | Val Loss: 0.008581 | Val MAE: 0.067675 | Val R²: 0.587220
Epoch 111/200 | Train Loss: 0.012381 | Val Loss: 0.008688 | Val MAE: 0.065240 | Val R²: 0.584480
Epoch 112/200 | Train Loss: 0.012422 | Val Loss: 0.009189 | Val MAE: 0.067943 | Val R²: 0.568555
Epoch 113/200 | Train Loss: 0.012142 | Val Loss: 0.008597 | Val MAE: 0.066916 | Val R²: 0.587234
Epoch 114/200 | Train Loss: 0.012136 | Val Loss: 0.009074 | Val MAE: 0.068986 | Val R²: 0.570769
Epoch 115/200 | Train Loss: 0.011818 | Val Loss: 0.008601 | Val MAE: 0.065523 | Val R²: 0.589645
Epoch 116/200 | Train Loss: 0.012087 | Val Loss: 0.008561 | Val MAE: 0.065959 | Val R²: 0.589644
Epoch 117/200 | Train Loss: 0.011668 | Val Loss: 0.008768 | Val MAE: 0.066272 | Val R²: 0.585921
Epoch 118/200 | Train Loss: 0.011854 | Val Loss: 0.008520 | Val MAE: 0.066729 | Val R²: 0.591092
Epoch 119/200 | Train Loss: 0.011880 | Val Loss: 0.008542 | Val MAE: 0.064374 | Val R²: 0.593095
Epoch 120/200 | Train Loss: 0.011649 | Val Loss: 0.008440 | Val MAE: 0.066395 | Val R²: 0.594193
Epoch 121/200 | Train Loss: 0.011839 | Val Loss: 0.008410 | Val MAE: 0.065103 | Val R²: 0.595535
Epoch 122/200 | Train Loss: 0.011587 | Val Loss: 0.008749 | Val MAE: 0.068067 | Val R²: 0.584422
Epoch 123/200 | Train Loss: 0.011542 | Val Loss: 0.008499 | Val MAE: 0.063814 | Val R²: 0.593993
Epoch 124/200 | Train Loss: 0.011477 | Val Loss: 0.008479 | Val MAE: 0.065287 | Val R²: 0.591307
Epoch 125/200 | Train Loss: 0.011703 | Val Loss: 0.009555 | Val MAE: 0.071435 | Val R²: 0.558190
Epoch 126/200 | Train Loss: 0.011407 | Val Loss: 0.008834 | Val MAE: 0.065191 | Val R²: 0.581728
Epoch 127/200 | Train Loss: 0.011377 | Val Loss: 0.008284 | Val MAE: 0.065170 | Val R²: 0.601438
Epoch 128/200 | Train Loss: 0.011315 | Val Loss: 0.008535 | Val MAE: 0.063594 | Val R²: 0.591847
Epoch 129/200 | Train Loss: 0.011253 | Val Loss: 0.008350 | Val MAE: 0.065880 | Val R²: 0.600919
Epoch 130/200 | Train Loss: 0.011198 | Val Loss: 0.008141 | Val MAE: 0.063860 | Val R²: 0.610042
Epoch 131/200 | Train Loss: 0.010977 | Val Loss: 0.008184 | Val MAE: 0.064665 | Val R²: 0.606709
Epoch 132/200 | Train Loss: 0.011269 | Val Loss: 0.008448 | Val MAE: 0.065541 | Val R²: 0.596622
Epoch 133/200 | Train Loss: 0.010955 | Val Loss: 0.008914 | Val MAE: 0.067116 | Val R²: 0.571698
Epoch 134/200 | Train Loss: 0.010906 | Val Loss: 0.008514 | Val MAE: 0.064121 | Val R²: 0.592958
Epoch 135/200 | Train Loss: 0.010837 | Val Loss: 0.008024 | Val MAE: 0.063960 | Val R²: 0.613516
Epoch 136/200 | Train Loss: 0.010864 | Val Loss: 0.009379 | Val MAE: 0.071372 | Val R²: 0.562172
Epoch 137/200 | Train Loss: 0.010868 | Val Loss: 0.008569 | Val MAE: 0.067702 | Val R²: 0.589452
Epoch 138/200 | Train Loss: 0.010766 | Val Loss: 0.008061 | Val MAE: 0.064505 | Val R²: 0.611987
Epoch 139/200 | Train Loss: 0.010601 | Val Loss: 0.008259 | Val MAE: 0.066478 | Val R²: 0.601048
Epoch 140/200 | Train Loss: 0.010709 | Val Loss: 0.008091 | Val MAE: 0.063164 | Val R²: 0.610741
Epoch 141/200 | Train Loss: 0.010689 | Val Loss: 0.008482 | Val MAE: 0.066359 | Val R²: 0.593674
Epoch 142/200 | Train Loss: 0.010606 | Val Loss: 0.008331 | Val MAE: 0.064874 | Val R²: 0.605387
Epoch 143/200 | Train Loss: 0.010497 | Val Loss: 0.008382 | Val MAE: 0.067374 | Val R²: 0.598234
Epoch 144/200 | Train Loss: 0.010547 | Val Loss: 0.009332 | Val MAE: 0.068536 | Val R²: 0.563342
Epoch 145/200 | Train Loss: 0.010218 | Val Loss: 0.008373 | Val MAE: 0.064908 | Val R²: 0.600636
Epoch 146/200 | Train Loss: 0.010418 | Val Loss: 0.008251 | Val MAE: 0.063731 | Val R²: 0.606398
Epoch 147/200 | Train Loss: 0.010146 | Val Loss: 0.008055 | Val MAE: 0.063047 | Val R²: 0.616284
Epoch 148/200 | Train Loss: 0.010086 | Val Loss: 0.007873 | Val MAE: 0.064025 | Val R²: 0.621411
Epoch 149/200 | Train Loss: 0.010035 | Val Loss: 0.007985 | Val MAE: 0.064364 | Val R²: 0.618866
Epoch 150/200 | Train Loss: 0.010085 | Val Loss: 0.007928 | Val MAE: 0.062613 | Val R²: 0.622317
Epoch 151/200 | Train Loss: 0.009921 | Val Loss: 0.007832 | Val MAE: 0.063552 | Val R²: 0.623410
Epoch 152/200 | Train Loss: 0.009960 | Val Loss: 0.008186 | Val MAE: 0.062869 | Val R²: 0.613113
Epoch 153/200 | Train Loss: 0.009931 | Val Loss: 0.008105 | Val MAE: 0.064074 | Val R²: 0.612700
Epoch 154/200 | Train Loss: 0.009854 | Val Loss: 0.007832 | Val MAE: 0.062975 | Val R²: 0.625187
Epoch 155/200 | Train Loss: 0.009982 | Val Loss: 0.007918 | Val MAE: 0.062783 | Val R²: 0.621579
Epoch 156/200 | Train Loss: 0.009983 | Val Loss: 0.008034 | Val MAE: 0.061958 | Val R²: 0.616644
Epoch 157/200 | Train Loss: 0.009827 | Val Loss: 0.007896 | Val MAE: 0.062512 | Val R²: 0.622941
Epoch 158/200 | Train Loss: 0.009705 | Val Loss: 0.008144 | Val MAE: 0.065749 | Val R²: 0.614169
Epoch 159/200 | Train Loss: 0.009914 | Val Loss: 0.008010 | Val MAE: 0.063747 | Val R²: 0.619739
Epoch 160/200 | Train Loss: 0.009749 | Val Loss: 0.007844 | Val MAE: 0.062621 | Val R²: 0.626041
Epoch 161/200 | Train Loss: 0.009909 | Val Loss: 0.007826 | Val MAE: 0.062434 | Val R²: 0.623553
Epoch 162/200 | Train Loss: 0.009651 | Val Loss: 0.008063 | Val MAE: 0.063830 | Val R²: 0.618881
Epoch 163/200 | Train Loss: 0.009670 | Val Loss: 0.007718 | Val MAE: 0.062460 | Val R²: 0.629973
Epoch 164/200 | Train Loss: 0.009733 | Val Loss: 0.007727 | Val MAE: 0.062388 | Val R²: 0.629745
Epoch 165/200 | Train Loss: 0.009546 | Val Loss: 0.007899 | Val MAE: 0.064250 | Val R²: 0.620270
Epoch 166/200 | Train Loss: 0.009708 | Val Loss: 0.007814 | Val MAE: 0.062883 | Val R²: 0.627886
Epoch 167/200 | Train Loss: 0.009615 | Val Loss: 0.007924 | Val MAE: 0.062641 | Val R²: 0.619767
Epoch 168/200 | Train Loss: 0.009691 | Val Loss: 0.008108 | Val MAE: 0.062719 | Val R²: 0.613057
Epoch 169/200 | Train Loss: 0.009641 | Val Loss: 0.008487 | Val MAE: 0.067820 | Val R²: 0.599072
Epoch 170/200 | Train Loss: 0.009687 | Val Loss: 0.007705 | Val MAE: 0.062095 | Val R²: 0.631826
Epoch 171/200 | Train Loss: 0.009531 | Val Loss: 0.007947 | Val MAE: 0.064304 | Val R²: 0.621652
Epoch 172/200 | Train Loss: 0.009575 | Val Loss: 0.007969 | Val MAE: 0.063384 | Val R²: 0.619745
Epoch 173/200 | Train Loss: 0.009577 | Val Loss: 0.007841 | Val MAE: 0.062519 | Val R²: 0.627520
Epoch 174/200 | Train Loss: 0.009655 | Val Loss: 0.007980 | Val MAE: 0.064717 | Val R²: 0.619932
Epoch 175/200 | Train Loss: 0.009542 | Val Loss: 0.007724 | Val MAE: 0.061828 | Val R²: 0.630648
Epoch 176/200 | Train Loss: 0.009473 | Val Loss: 0.007831 | Val MAE: 0.062297 | Val R²: 0.623843
Epoch 177/200 | Train Loss: 0.009609 | Val Loss: 0.007698 | Val MAE: 0.061767 | Val R²: 0.630617
Epoch 178/200 | Train Loss: 0.009469 | Val Loss: 0.007710 | Val MAE: 0.062834 | Val R²: 0.631882
Epoch 179/200 | Train Loss: 0.009458 | Val Loss: 0.007804 | Val MAE: 0.063567 | Val R²: 0.626120
Epoch 180/200 | Train Loss: 0.009453 | Val Loss: 0.007726 | Val MAE: 0.061646 | Val R²: 0.631709
Epoch 181/200 | Train Loss: 0.009284 | Val Loss: 0.007651 | Val MAE: 0.062748 | Val R²: 0.633585
Epoch 182/200 | Train Loss: 0.009407 | Val Loss: 0.007743 | Val MAE: 0.062822 | Val R²: 0.630794
Epoch 183/200 | Train Loss: 0.009494 | Val Loss: 0.007991 | Val MAE: 0.064221 | Val R²: 0.621467
Epoch 184/200 | Train Loss: 0.009460 | Val Loss: 0.007704 | Val MAE: 0.062497 | Val R²: 0.631785
Epoch 185/200 | Train Loss: 0.009333 | Val Loss: 0.007994 | Val MAE: 0.064646 | Val R²: 0.618533
Epoch 186/200 | Train Loss: 0.009351 | Val Loss: 0.007819 | Val MAE: 0.062095 | Val R²: 0.626712
Epoch 187/200 | Train Loss: 0.009375 | Val Loss: 0.007659 | Val MAE: 0.062085 | Val R²: 0.634665
Epoch 188/200 | Train Loss: 0.009374 | Val Loss: 0.007722 | Val MAE: 0.062012 | Val R²: 0.629723
Epoch 189/200 | Train Loss: 0.009337 | Val Loss: 0.007681 | Val MAE: 0.062779 | Val R²: 0.633673
Epoch 190/200 | Train Loss: 0.009223 | Val Loss: 0.007808 | Val MAE: 0.062065 | Val R²: 0.630821
Epoch 191/200 | Train Loss: 0.009341 | Val Loss: 0.007787 | Val MAE: 0.062840 | Val R²: 0.625738
Epoch 192/200 | Train Loss: 0.009257 | Val Loss: 0.008084 | Val MAE: 0.065057 | Val R²: 0.617277
Epoch 193/200 | Train Loss: 0.009077 | Val Loss: 0.007655 | Val MAE: 0.062197 | Val R²: 0.634637
Epoch 194/200 | Train Loss: 0.009002 | Val Loss: 0.007572 | Val MAE: 0.061112 | Val R²: 0.638323
Epoch 195/200 | Train Loss: 0.009006 | Val Loss: 0.007554 | Val MAE: 0.061318 | Val R²: 0.639251
Epoch 196/200 | Train Loss: 0.009097 | Val Loss: 0.007613 | Val MAE: 0.062081 | Val R²: 0.636324
Epoch 197/200 | Train Loss: 0.009096 | Val Loss: 0.007637 | Val MAE: 0.062302 | Val R²: 0.636061
Epoch 198/200 | Train Loss: 0.009080 | Val Loss: 0.007538 | Val MAE: 0.061453 | Val R²: 0.638084
Epoch 199/200 | Train Loss: 0.009091 | Val Loss: 0.007617 | Val MAE: 0.061330 | Val R²: 0.636072
Epoch 200/200 | Train Loss: 0.009049 | Val Loss: 0.007608 | Val MAE: 0.062118 | Val R²: 0.635310
Training completed. Best validation loss: 0.007538
8: Plotting training curves...
Saved training curves to training_curves.pdf
9: Evaluating on test set...
10: Saving artifacts for downstream code...
Saved model weights to: model_results/model_weights.pth
Saved test predictions to: model_results/test_predictions.npz
Test Set Performance:
Equatorial - MAE: 0.0574, RMSE: 0.0774, R²: 0.5849
Axial - MAE: 0.0697, RMSE: 0.0992, R²: 0.6970