Adding Lab3
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{
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"seed": 42,
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"latent_dimensions": [
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2,
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8,
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16,
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64
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],
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"beta": 1.0,
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"epochs": 8,
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"batch_size": 256,
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"learning_rate": 0.001,
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"active_kl_threshold": 0.01,
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"device": "cpu"
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}
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epoch,train_loss,train_reconstruction,train_kl,test_loss,test_reconstruction,test_kl
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1,194.58393379720053,175.48489509684245,19.09903873833815,130.93381232910156,108.26412487792969,22.669688568115234
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2,124.60164559326172,101.15291471761067,23.44873085123698,118.81840416259766,95.25473420410157,23.563670153808594
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3,116.78998135172526,92.74015213216146,24.049829255167644,113.08031853027343,88.582109375,24.498209783935547
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4,112.71829342041016,88.43491739501953,24.28337615661621,110.41185048828125,86.33808363037109,24.073766467285157
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5,110.3596667602539,86.0051683959961,24.35449857076009,108.8561907836914,83.92672475585937,24.929465832519533
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6,108.77466271565756,84.42341725260417,24.35124549560547,107.3223890625,83.26506918945313,24.057319537353514
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7,107.5822222290039,83.25968048095703,24.322541959635416,106.22459836425782,81.54324875488281,24.681349908447267
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8,106.67053671875,82.37358662516276,24.29695024922689,105.60406574707031,80.82425764160156,24.77980806274414
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epoch,train_loss,train_reconstruction,train_kl,test_loss,test_reconstruction,test_kl
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1,214.50344514160156,206.6360744140625,7.867370829008023,180.69990083007812,175.01709204101562,5.682808818817139
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2,176.8603714436849,171.43450122884116,5.425870570882162,173.6909063232422,168.53819150390626,5.152714322662353
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3,172.14672754720053,166.94108987630207,5.205637788136801,170.06085971679687,164.89225100097656,5.168609001922608
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4,168.69642669270834,163.50723880208332,5.189188002268473,167.1127751953125,161.8381774658203,5.274598063659668
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5,165.9270773844401,160.73688623860676,5.190190850575765,164.90293757324218,159.94551962890625,4.957417066955567
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6,163.64551680501302,158.44852639160158,5.196989870452881,162.63473374023437,157.47572224121095,5.159009851837158
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7,161.6512779703776,156.37544615071616,5.2758320025126135,160.93336838378906,155.6678894042969,5.265479164123535
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8,159.87877953287762,154.53332881673177,5.345450691477458,159.42389772949218,153.81529624023437,5.608600630950928
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epoch,train_loss,train_reconstruction,train_kl,test_loss,test_reconstruction,test_kl
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1,179.3074365641276,155.7149076131185,23.59252906471888,131.67581762695312,101.02223177490234,30.653585943603517
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2,122.59562550455729,91.83565464274089,30.759970919799805,115.52319572753906,84.367188671875,31.156007104492186
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3,113.6100835571289,83.19448351236979,30.41560001627604,110.70017164306641,80.19446899414062,30.505702603149413
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4,110.41267469075521,80.4962550415039,29.916419713338215,108.54279274902343,78.06112868652343,30.481663970947267
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5,108.68612502034505,79.15287654622396,29.5332484954834,107.24194914550782,78.06970739746093,29.17224097290039
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6,107.45811442057291,78.25812352294922,29.199991138712566,106.32864702148437,75.58045902099609,30.748187512207032
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7,106.58018358968098,77.66063642985026,28.91954721984863,105.446982421875,77.35936909179688,28.087613525390626
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8,105.86727047526041,77.17564948323567,28.69162111002604,104.82540803222656,75.97232977294922,28.853078353881838
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epoch,train_loss,train_reconstruction,train_kl,test_loss,test_reconstruction,test_kl
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1,194.38905454915366,179.37971506347657,15.009339568354687,142.19221296386718,126.5895224609375,15.602690301513672
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2,135.9645408610026,120.53864139404297,15.425899491373698,129.71243697509766,113.97722583007813,15.735211050415039
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3,128.11734686279297,112.35682171223958,15.760525179036458,125.09155083007812,108.70252813720703,16.389023248291014
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4,124.2283656616211,108.36162486979167,15.866740420532226,121.64499807128907,105.43607805175782,16.208919818115234
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5,121.65717885335286,105.76112994791667,15.896048705546061,119.75198037109375,103.7866158569336,15.965363806152343
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6,119.75065758056641,103.79047712809245,15.960180529785156,117.79170933837891,101.54909013671875,16.242619421386717
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7,118.16403889973958,102.14432193603515,16.019716856384278,116.644436328125,100.65633608398437,15.988100588989258
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8,116.85729860026042,100.73877130940755,16.118527282714844,115.50761174316406,99.42716062011719,16.080450680541993
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Latent dim,Parameters,Test negative ELBO,Test reconstruction,Test KL,Active dimensions,Active fraction,Training seconds
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2,88645,159.42389772949218,153.81529624023437,5.608600630950928,2,1.0,259.9766161441803
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8,145105,115.50761174316406,99.42716062011719,16.080450680541993,8,1.0,270.2368748188019
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16,220385,105.60406574707031,80.82425764160156,24.77980806274414,16,1.0,256.8563587665558
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64,672065,104.82540803222656,75.97232977294922,28.853078353881838,42,0.65625,266.9931149482727
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\begin{tabular}{rrrrrrrr}
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\toprule
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Latent dim & Parameters & Test negative ELBO & Test reconstruction & Test KL & Active dimensions & Active fraction & Training seconds \\
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\midrule
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2 & 88645 & 159.424 & 153.815 & 5.609 & 2 & 1.000 & 259.977 \\
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8 & 145105 & 115.508 & 99.427 & 16.080 & 8 & 1.000 & 270.237 \\
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16 & 220385 & 105.604 & 80.824 & 24.780 & 16 & 1.000 & 256.856 \\
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64 & 672065 & 104.825 & 75.972 & 28.853 & 42 & 0.656 & 266.993 \\
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\bottomrule
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\end{tabular}
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