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New hyperparamter scan results

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Lars Bogner
2025-11-25 22:38:54 +01:00
parent 5fb29df06c
commit 5951475586
3 changed files with 546 additions and 546 deletions
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Code/python/notebooks/03_visualize_hyperparameters.ipynb
+430 -430
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File diff suppressed because one or more lines are too long
Code/python/notebooks/hyperparameter_scan.py
+8 -8
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@@ -185,14 +185,14 @@ def run_mode_2():
base_ds = dataloader.SaveDataset(torch.load("dataset.pt"), step=step) base_ds = dataloader.SaveDataset(torch.load("dataset.pt"), step=step)
train_ds, val_ds = split_dataset(base_ds) train_ds, val_ds = split_dataset(base_ds)
base_name = "GRU" base_name = "LSTM"
cls = models.ThreeInputGRU cls = models.ThreeInputLSTM
hidden_size = 32 hidden_size = 16
rnn_size = 64 rnn_size = 64
for hl in [0, 1, 2, 4]: for hl in [0, 1, 2, 4]:
for rl in [2, 3, 4, 5]: for rl in [2, 3, 4, 5]:
for dropout in [0.0, 0.1, 0.2, 0.3]: for dropout in [0.0, 0.05, 0.1, 0.15]:
model = cls( model = cls(
time_in=2, time_in=2,
@@ -229,13 +229,13 @@ def run_mode_3():
results = [] results = []
step = 1 step = 1
base_name = "GRU" base_name = "LSTM"
cls = models.ThreeInputGRU cls = models.ThreeInputLSTM
hidden_size = 32 hidden_size = 16
rnn_size = 64 rnn_size = 64
hidden_layers = 1 hidden_layers = 1
rnn_layers = 3 rnn_layers = 3
rnn_dropout = 0.1 rnn_dropout = 0.0
for warm in [300, 600, 900, 1800]: for warm in [300, 600, 900, 1800]:
for pred in [150, 300, 600, 900, 1800]: for pred in [150, 300, 600, 900, 1800]:
Code/python/notebooks/hyperparameter_scan_results.csv
+108 -108
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@@ -1,109 +1,109 @@
Model,Hidden Size,RNN Size,Step,Final Loss Model,Hidden Size,RNN Size,Step,Final Loss
RNN,16,32,1,372.1873533829399 RNN,16,32,1,261.2352640931035
RNN,16,64,1,371.67606353759766 RNN,16,64,1,154.6564223061145
RNN,16,128,1,328.19922903309697 RNN,16,128,1,196.3427066534338
RNN,32,32,1,376.71770842179006 RNN,32,32,1,384.9678237270301
RNN,32,64,1,369.6340640524159 RNN,32,64,1,410.67893423161036
RNN,32,128,1,281.8589802617612 RNN,32,128,1,291.4480094372387
RNN,64,32,1,378.75125188412875 RNN,64,32,1,405.7067755040988
RNN,64,64,1,405.08673095703125 RNN,64,64,1,2116.495914942782
RNN,64,128,1,1088.4633191979449 RNN,64,128,1,2116.4957490303145
LSTM,16,32,1,152.01849580847698 LSTM,16,32,1,30.830584109669
LSTM,16,64,1,152.46532937754756 LSTM,16,64,1,24.41159848763909
LSTM,16,128,1,39.81503051260243 LSTM,16,128,1,
LSTM,32,32,1,45.500295265861176 LSTM,32,32,1,18.46859591443774
LSTM,32,64,1,51.218478575996734 LSTM,32,64,1,20.514015533554723
LSTM,32,128,1,32.29804623645285 LSTM,32,128,1,16.6853289604187
LSTM,64,32,1,105.44863045733908 LSTM,64,32,1,64.03490912746376
LSTM,64,64,1,62.87264318051545 LSTM,64,64,1,15.621828354580302
LSTM,64,128,1,170.77305080579674 LSTM,64,128,1,23.594708127035222
GRU,16,32,1,23.525951261105746 GRU,16,32,1,
GRU,16,64,1,20.953380501788594 GRU,16,64,1,
GRU,16,128,1,50.10249718375828 GRU,16,128,1,35.8418803282187
GRU,32,32,1,149.08109225397524 GRU,32,32,1,
GRU,32,64,1,40.437404922817066 GRU,32,64,1,19.816746349066076
GRU,32,128,1,34.31250389762547 GRU,32,128,1,
GRU,64,32,1,154.5310813240383 GRU,64,32,1,
GRU,64,64,1,47.95653426128885 GRU,64,64,1,99.63193988800049
GRU,64,128,1,263.4846937760063 GRU,64,128,1,62.531928075871
RNN,16,32,5,326.2015085634978 RNN,16,32,5,215.5662602169413
RNN,16,64,5,384.77328723409903 RNN,16,64,5,458.9189094221088
RNN,16,128,5,1099.3475819463315 RNN,16,128,5,568.8256333042199
RNN,32,32,5,246.47076250159222 RNN,32,32,5,367.05963134765625
RNN,32,64,5,329.85308439835256 RNN,32,64,5,391.08609277429713
RNN,32,128,5,1098.7943765391474 RNN,32,128,5,86.18239271137077
RNN,64,32,5,477.369012583857 RNN,64,32,5,379.8394951618893
RNN,64,64,5,365.6013999607252 RNN,64,64,5,217.72880833585498
RNN,64,128,5,413.95318603515625 RNN,64,128,5,193.88096043761348
LSTM,16,32,5,24.514795303344727 LSTM,16,32,5,17.732036187615194
LSTM,16,64,5,24.9299375285273 LSTM,16,64,5,12.483971592406151
LSTM,16,128,5,34.382882035296895 LSTM,16,128,5,18.235054378778162
LSTM,32,32,5,171.14435179337212 LSTM,32,32,5,16.88911421869842
LSTM,32,64,5,185.21222504325536 LSTM,32,64,5,13.982023883873309
LSTM,32,128,5,24.800554503565248 LSTM,32,128,5,13.012413780454178
LSTM,64,32,5,183.13448831309444 LSTM,64,32,5,18.227851189358134
LSTM,64,64,5,37.47129328354545 LSTM,64,64,5,18.786675762122787
LSTM,64,128,5,51.097612007804535 LSTM,64,128,5,25.950177515056772
GRU,16,32,5,30.631973432457965 GRU,16,32,5,19.275062708787516
GRU,16,64,5,30.393669625987176 GRU,16,64,5,29.5315320995492
GRU,16,128,5,55.05557930987814 GRU,16,128,5,44.03425704257589
GRU,32,32,5,54.14869615306025 GRU,32,32,5,25.158055748738033
GRU,32,64,5,167.3384770932405 GRU,32,64,5,17.85035125302597
GRU,32,128,5,50.49319474593453 GRU,32,128,5,92.48385832343303
GRU,64,32,5,170.90516430398694 GRU,64,32,5,92.20544084360901
GRU,64,64,5,153.55044091266134 GRU,64,64,5,108.83066752259161
GRU,64,128,5,53.40392129317574 GRU,64,128,5,168.5157569562885
RNN,16,32,10,285.0945102857507 RNN,16,32,10,331.5480924794372
RNN,16,64,10,361.18107339610225 RNN,16,64,10,328.6068296835456
RNN,16,128,10,320.00166884712553 RNN,16,128,10,134.54841076488225
RNN,32,32,10,359.23063095756197 RNN,32,32,10,299.88682910758007
RNN,32,64,10,351.7510011092476 RNN,32,64,10,306.9416514651876
RNN,32,128,10,126.81333442356275 RNN,32,128,10,162.43678724262077
RNN,64,32,10,336.1739501953125 RNN,64,32,10,329.1637651685258
RNN,64,64,10,342.61622918170434 RNN,64,64,10,334.56139105138647
RNN,64,128,10,208.79256007982337 RNN,64,128,10,141.24655634920362
LSTM,16,32,10,47.18654777692712 LSTM,16,32,10,92.42624144486977
LSTM,16,64,10,35.0142301061879 LSTM,16,64,10,14.689397603693143
LSTM,16,128,10,31.15265079166578 LSTM,16,128,10,11.110472313115295
LSTM,32,32,10,57.50707398290219 LSTM,32,32,10,20.380187215939372
LSTM,32,64,10,21.263865159905475 LSTM,32,64,10,15.061512013556252
LSTM,32,128,10,39.93263937079388 LSTM,32,128,10,22.62677042249223
LSTM,64,32,10,57.33804578366487 LSTM,64,32,10,26.77031899170137
LSTM,64,64,10,52.7249521587206 LSTM,64,64,10,24.62572886910237
LSTM,64,128,10,59.768143446549125 LSTM,64,128,10,26.26676934873554
GRU,16,32,10,28.489941555520762 GRU,16,32,10,21.257314131293498
GRU,16,64,10,25.493946241295856 GRU,16,64,10,19.206207382846888
GRU,16,128,10,35.874996682871945 GRU,16,128,10,43.89531944167446
GRU,32,32,10,39.71779649154 GRU,32,32,10,20.500510410523752
GRU,32,64,10,33.58222509467083 GRU,32,64,10,21.27962108397148
GRU,32,128,10,36.87489372750987 GRU,32,128,10,26.415901694499272
GRU,64,32,10,55.22760449285092 GRU,64,32,10,102.7421861836608
GRU,64,64,10,168.17254008417544 GRU,64,64,10,108.29447157953827
GRU,64,128,10,76.96743749535602 GRU,64,128,10,144.37117619581625
RNN,16,32,30,245.38945504893428 RNN,16,32,30,207.72070333991252
RNN,16,64,30,303.7835593845533 RNN,16,64,30,259.24992929378027
RNN,16,128,30,1168.2417987325916 RNN,16,128,30,106.49237761698978
RNN,32,32,30,221.63304668924084 RNN,32,32,30,108.70668032471563
RNN,32,64,30,274.024205746858 RNN,32,64,30,292.42346556757536
RNN,32,128,30,1167.9884391452956 RNN,32,128,30,2260.9625183965118
RNN,64,32,30,316.6191160782524 RNN,64,32,30,255.18154520384022
RNN,64,64,30,252.00204235574475 RNN,64,64,30,275.74408292098786
RNN,64,128,30,1168.0314676036005 RNN,64,128,30,303.8554754122882
LSTM,16,32,30,46.3279622119406 LSTM,16,32,30,120.18003799545933
LSTM,16,64,30,32.77271196116572 LSTM,16,64,30,32.07153643352885
LSTM,16,128,30,1168.1180778171706 LSTM,16,128,30,29.8134809682067
LSTM,32,32,30,192.53192719169286 LSTM,32,32,30,30.940696246187454
LSTM,32,64,30,40.278250404026195 LSTM,32,64,30,27.958127700107198
LSTM,32,128,30,35.424202234848686 LSTM,32,128,30,112.83767892273379
LSTM,64,32,30,51.08382113083549 LSTM,64,32,30,130.2808960928044
LSTM,64,64,30,186.7356419770614 LSTM,64,64,30,117.1968483589065
LSTM,64,128,30,177.50895442133364 LSTM,64,128,30,109.4370427198813
GRU,16,32,30,35.31677892933721 GRU,16,32,30,56.353233820955516
GRU,16,64,30,34.573822394661285 GRU,16,64,30,33.99593487591811
GRU,16,128,30,55.778304846390434 GRU,16,128,30,59.830814415300395
GRU,32,32,30,65.31020172782566 GRU,32,32,30,33.456441832260346
GRU,32,64,30,37.21405522719674 GRU,32,64,30,34.80982407046036
GRU,32,128,30,38.621485295503035 GRU,32,128,30,136.90971965521155
GRU,64,32,30,120.50829563970152 GRU,64,32,30,139.1069736480713
GRU,64,64,30,75.70721891651984 GRU,64,64,30,62.417733837181416
GRU,64,128,30,189.14709671683934 GRU,64,128,30,64.40956481073944
1 Model Hidden Size RNN Size Step Final Loss
2 RNN 16 32 1 372.1873533829399 261.2352640931035
3 RNN 16 64 1 371.67606353759766 154.6564223061145
4 RNN 16 128 1 328.19922903309697 196.3427066534338
5 RNN 32 32 1 376.71770842179006 384.9678237270301
6 RNN 32 64 1 369.6340640524159 410.67893423161036
7 RNN 32 128 1 281.8589802617612 291.4480094372387
8 RNN 64 32 1 378.75125188412875 405.7067755040988
9 RNN 64 64 1 405.08673095703125 2116.495914942782
10 RNN 64 128 1 1088.4633191979449 2116.4957490303145
11 LSTM 16 32 1 152.01849580847698 30.830584109669
12 LSTM 16 64 1 152.46532937754756 24.41159848763909
13 LSTM 16 128 1 39.81503051260243
14 LSTM 32 32 1 45.500295265861176 18.46859591443774
15 LSTM 32 64 1 51.218478575996734 20.514015533554723
16 LSTM 32 128 1 32.29804623645285 16.6853289604187
17 LSTM 64 32 1 105.44863045733908 64.03490912746376
18 LSTM 64 64 1 62.87264318051545 15.621828354580302
19 LSTM 64 128 1 170.77305080579674 23.594708127035222
20 GRU 16 32 1 23.525951261105746
21 GRU 16 64 1 20.953380501788594
22 GRU 16 128 1 50.10249718375828 35.8418803282187
23 GRU 32 32 1 149.08109225397524
24 GRU 32 64 1 40.437404922817066 19.816746349066076
25 GRU 32 128 1 34.31250389762547
26 GRU 64 32 1 154.5310813240383
27 GRU 64 64 1 47.95653426128885 99.63193988800049
28 GRU 64 128 1 263.4846937760063 62.531928075871
29 RNN 16 32 5 326.2015085634978 215.5662602169413
30 RNN 16 64 5 384.77328723409903 458.9189094221088
31 RNN 16 128 5 1099.3475819463315 568.8256333042199
32 RNN 32 32 5 246.47076250159222 367.05963134765625
33 RNN 32 64 5 329.85308439835256 391.08609277429713
34 RNN 32 128 5 1098.7943765391474 86.18239271137077
35 RNN 64 32 5 477.369012583857 379.8394951618893
36 RNN 64 64 5 365.6013999607252 217.72880833585498
37 RNN 64 128 5 413.95318603515625 193.88096043761348
38 LSTM 16 32 5 24.514795303344727 17.732036187615194
39 LSTM 16 64 5 24.9299375285273 12.483971592406151
40 LSTM 16 128 5 34.382882035296895 18.235054378778162
41 LSTM 32 32 5 171.14435179337212 16.88911421869842
42 LSTM 32 64 5 185.21222504325536 13.982023883873309
43 LSTM 32 128 5 24.800554503565248 13.012413780454178
44 LSTM 64 32 5 183.13448831309444 18.227851189358134
45 LSTM 64 64 5 37.47129328354545 18.786675762122787
46 LSTM 64 128 5 51.097612007804535 25.950177515056772
47 GRU 16 32 5 30.631973432457965 19.275062708787516
48 GRU 16 64 5 30.393669625987176 29.5315320995492
49 GRU 16 128 5 55.05557930987814 44.03425704257589
50 GRU 32 32 5 54.14869615306025 25.158055748738033
51 GRU 32 64 5 167.3384770932405 17.85035125302597
52 GRU 32 128 5 50.49319474593453 92.48385832343303
53 GRU 64 32 5 170.90516430398694 92.20544084360901
54 GRU 64 64 5 153.55044091266134 108.83066752259161
55 GRU 64 128 5 53.40392129317574 168.5157569562885
56 RNN 16 32 10 285.0945102857507 331.5480924794372
57 RNN 16 64 10 361.18107339610225 328.6068296835456
58 RNN 16 128 10 320.00166884712553 134.54841076488225
59 RNN 32 32 10 359.23063095756197 299.88682910758007
60 RNN 32 64 10 351.7510011092476 306.9416514651876
61 RNN 32 128 10 126.81333442356275 162.43678724262077
62 RNN 64 32 10 336.1739501953125 329.1637651685258
63 RNN 64 64 10 342.61622918170434 334.56139105138647
64 RNN 64 128 10 208.79256007982337 141.24655634920362
65 LSTM 16 32 10 47.18654777692712 92.42624144486977
66 LSTM 16 64 10 35.0142301061879 14.689397603693143
67 LSTM 16 128 10 31.15265079166578 11.110472313115295
68 LSTM 32 32 10 57.50707398290219 20.380187215939372
69 LSTM 32 64 10 21.263865159905475 15.061512013556252
70 LSTM 32 128 10 39.93263937079388 22.62677042249223
71 LSTM 64 32 10 57.33804578366487 26.77031899170137
72 LSTM 64 64 10 52.7249521587206 24.62572886910237
73 LSTM 64 128 10 59.768143446549125 26.26676934873554
74 GRU 16 32 10 28.489941555520762 21.257314131293498
75 GRU 16 64 10 25.493946241295856 19.206207382846888
76 GRU 16 128 10 35.874996682871945 43.89531944167446
77 GRU 32 32 10 39.71779649154 20.500510410523752
78 GRU 32 64 10 33.58222509467083 21.27962108397148
79 GRU 32 128 10 36.87489372750987 26.415901694499272
80 GRU 64 32 10 55.22760449285092 102.7421861836608
81 GRU 64 64 10 168.17254008417544 108.29447157953827
82 GRU 64 128 10 76.96743749535602 144.37117619581625
83 RNN 16 32 30 245.38945504893428 207.72070333991252
84 RNN 16 64 30 303.7835593845533 259.24992929378027
85 RNN 16 128 30 1168.2417987325916 106.49237761698978
86 RNN 32 32 30 221.63304668924084 108.70668032471563
87 RNN 32 64 30 274.024205746858 292.42346556757536
88 RNN 32 128 30 1167.9884391452956 2260.9625183965118
89 RNN 64 32 30 316.6191160782524 255.18154520384022
90 RNN 64 64 30 252.00204235574475 275.74408292098786
91 RNN 64 128 30 1168.0314676036005 303.8554754122882
92 LSTM 16 32 30 46.3279622119406 120.18003799545933
93 LSTM 16 64 30 32.77271196116572 32.07153643352885
94 LSTM 16 128 30 1168.1180778171706 29.8134809682067
95 LSTM 32 32 30 192.53192719169286 30.940696246187454
96 LSTM 32 64 30 40.278250404026195 27.958127700107198
97 LSTM 32 128 30 35.424202234848686 112.83767892273379
98 LSTM 64 32 30 51.08382113083549 130.2808960928044
99 LSTM 64 64 30 186.7356419770614 117.1968483589065
100 LSTM 64 128 30 177.50895442133364 109.4370427198813
101 GRU 16 32 30 35.31677892933721 56.353233820955516
102 GRU 16 64 30 34.573822394661285 33.99593487591811
103 GRU 16 128 30 55.778304846390434 59.830814415300395
104 GRU 32 32 30 65.31020172782566 33.456441832260346
105 GRU 32 64 30 37.21405522719674 34.80982407046036
106 GRU 32 128 30 38.621485295503035 136.90971965521155
107 GRU 64 32 30 120.50829563970152 139.1069736480713
108 GRU 64 64 30 75.70721891651984 62.417733837181416
109 GRU 64 128 30 189.14709671683934 64.40956481073944