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training_results_2.txt
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training_results_2.txt
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batch_size 100, epochs 20, learning rate 5e-05, coeff kld 10.0, coeff kd
train epoch 0, iteration 0, loss -29.039718627929688
validation epoch 0, iteration 0, loss 2.3275520751953125
train epoch 0, iteration 50, loss -33.28472900390625
train epoch 0, iteration 100, loss -36.61419677734375
validation epoch 0, iteration 100, loss 1.6700791397094727
train epoch 0, iteration 150, loss -40.614742279052734
train epoch 0, iteration 200, loss -41.10204315185547
validation epoch 0, iteration 200, loss 1.1863704902648926
train epoch 0, iteration 250, loss -42.156005859375
train epoch 0, iteration 300, loss -44.42305374145508
validation epoch 0, iteration 300, loss 0.902183065032959
train epoch 0, iteration 350, loss -45.6060676574707
train epoch 0, iteration 400, loss -46.37647247314453
validation epoch 0, iteration 400, loss 0.7746402992248536
train epoch 0, iteration 450, loss -47.14263153076172
train epoch 0, iteration 500, loss -48.95524978637695
validation epoch 0, iteration 500, loss 0.6906402732849121
train epoch 0, iteration 550, loss -48.872520446777344
train epoch 1, iteration 0, loss -50.03925704956055
validation epoch 1, iteration 0, loss 0.6564342533111572
train epoch 1, iteration 50, loss -50.51865005493164
train epoch 1, iteration 100, loss -51.026451110839844
validation epoch 1, iteration 100, loss 0.6201973609924316
train epoch 1, iteration 150, loss -51.56855392456055
train epoch 1, iteration 200, loss -51.71886444091797
validation epoch 1, iteration 200, loss 0.5976101615905761
train epoch 1, iteration 250, loss -52.52827072143555
train epoch 1, iteration 300, loss -52.642967224121094
validation epoch 1, iteration 300, loss 0.5724206466674805
train epoch 1, iteration 350, loss -53.365272521972656
train epoch 1, iteration 400, loss -54.069190979003906
validation epoch 1, iteration 400, loss 0.557735290145874
train epoch 1, iteration 450, loss -54.294395446777344
train epoch 1, iteration 500, loss -55.113494873046875
validation epoch 1, iteration 500, loss 0.5445579235076904
train epoch 1, iteration 550, loss -55.47344970703125
train epoch 2, iteration 0, loss -55.558998107910156
validation epoch 2, iteration 0, loss 0.540273371887207
train epoch 2, iteration 50, loss -56.422786712646484
train epoch 2, iteration 100, loss -55.9769287109375
validation epoch 2, iteration 100, loss 0.5176151416778565
train epoch 2, iteration 150, loss -56.72385787963867
train epoch 2, iteration 200, loss -57.38581466674805
validation epoch 2, iteration 200, loss 0.5080976577758789
train epoch 2, iteration 250, loss -56.90837860107422
train epoch 2, iteration 300, loss -58.86956024169922
validation epoch 2, iteration 300, loss 0.49577931632995603
train epoch 2, iteration 350, loss -57.959651947021484
train epoch 2, iteration 400, loss -58.52008819580078
validation epoch 2, iteration 400, loss 0.48733782234191897
train epoch 2, iteration 450, loss -59.28629684448242
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train epoch 2, iteration 550, loss -59.05296325683594
train epoch 3, iteration 0, loss -59.83729934692383
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train epoch 3, iteration 50, loss -60.15956115722656
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train epoch 3, iteration 150, loss -60.355323791503906
train epoch 3, iteration 200, loss -61.198455810546875
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train epoch 3, iteration 250, loss -60.952781677246094
train epoch 3, iteration 300, loss -62.064762115478516
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train epoch 3, iteration 350, loss -60.885311126708984
train epoch 3, iteration 400, loss -61.51742935180664
validation epoch 3, iteration 400, loss 0.4395431142807007
train epoch 3, iteration 450, loss -62.22098159790039
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train epoch 3, iteration 550, loss -62.415348052978516
train epoch 4, iteration 0, loss -62.96910095214844
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train epoch 4, iteration 50, loss -63.15620803833008
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train epoch 6, iteration 0, loss -68.09638977050781
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train epoch 6, iteration 450, loss -69.4421157836914
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train epoch 6, iteration 550, loss -69.53943634033203
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train epoch 7, iteration 50, loss -70.0068359375
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train epoch 7, iteration 250, loss -70.60485076904297
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validation epoch 7, iteration 300, loss 0.3362012716293335
train epoch 7, iteration 350, loss -71.29582977294922
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train epoch 7, iteration 450, loss -71.22738647460938
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train epoch 7, iteration 550, loss -71.15745544433594
train epoch 8, iteration 0, loss -71.36495971679688
validation epoch 8, iteration 0, loss 0.33303371906280516
train epoch 8, iteration 50, loss -71.28382873535156
train epoch 8, iteration 100, loss -71.86337280273438
validation epoch 8, iteration 100, loss 0.3335883029937744
train epoch 8, iteration 150, loss -71.82172393798828
train epoch 8, iteration 200, loss -72.50149536132812
validation epoch 8, iteration 200, loss 0.3297873764038086
train epoch 8, iteration 250, loss -71.89471435546875
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validation epoch 8, iteration 300, loss 0.3256505170822144
train epoch 8, iteration 350, loss -72.0065689086914
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train epoch 9, iteration 0, loss -73.07728576660156
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train epoch 10, iteration 250, loss -75.12537384033203
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train epoch 10, iteration 350, loss -75.22636413574219
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train epoch 12, iteration 0, loss -77.49440002441406
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train epoch 15, iteration 50, loss -80.25481414794922
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train epoch 15, iteration 150, loss -80.23179626464844
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train epoch 15, iteration 550, loss -80.57636260986328
train epoch 16, iteration 0, loss -80.46138000488281
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train epoch 16, iteration 50, loss -81.15791320800781
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