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Commit 4c7493fe authored by Ard Kastrati's avatar Ard Kastrati
Browse files

Finished the experiment for pyramidal CNN without shuffling

parent 5cda2853
......@@ -42,7 +42,7 @@ Cluster can be set to clustering(), clustering2() or clustering3(), where differ
"""
# Choosing model
config['model'] = 'inception'
config['model'] = 'pyramidal_cnn'
config['downsampled'] = False
config['split'] = False
config['cluster'] = clustering()
......
This diff is collapsed.
INFO:root:Started the Logging
INFO:root:X training loaded.
INFO:root:(129, 500, 36223)
INFO:root:y training loaded.
INFO:root:(1, 36223)
INFO:root:Setting the shapes
INFO:root:(36223, 500, 129)
INFO:root:(36223, 1)
INFO:root:Started running pyramidal_cnn. If you want to run other methods please choose another model in the config.py file.
INFO:root:Parameters:
INFO:root:--------------- use residual : False
INFO:root:--------------- depth : 6
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 16
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:Parameters:
INFO:root:--------------- use residual : False
INFO:root:--------------- depth : 6
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 16
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:Parameters:
INFO:root:--------------- use residual : False
INFO:root:--------------- depth : 6
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 16
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:Parameters:
INFO:root:--------------- use residual : False
INFO:root:--------------- depth : 6
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 16
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:Parameters:
INFO:root:--------------- use residual : False
INFO:root:--------------- depth : 6
INFO:root:--------------- batch size : 64
INFO:root:--------------- kernel size : 16
INFO:root:--------------- nb filters : 16
INFO:root:--------------- preprocessing: False
INFO:root:**********
INFO:root:--- Runtime: 4385.55873465538 seconds ---
INFO:root:Finished Logging
This diff is collapsed.
best_model_train_loss,best_model_val_loss,best_model_train_acc,best_model_val_acc
0.015998361632227898,0.18427009880542755,0.9940705895423889,0.9355509355509356
loss,accuracy,val_loss,val_accuracy
0.4764048457145691,0.7602730393409729,0.36191967129707336,0.8475398475398476
0.25724494457244873,0.8903405666351318,0.28241175413131714,0.8931392931392932
0.19149522483348846,0.920539140701294,0.2897370457649231,0.8801108801108801
0.1611756980419159,0.9340871572494507,0.22746485471725464,0.9148995148995149
0.13734370470046997,0.943739652633667,0.19978728890419006,0.9237699237699237
0.11813688278198242,0.9514961242675781,0.18352124094963074,0.93000693000693
0.10276415199041367,0.9598386883735657,0.1938869059085846,0.918918918918919
0.08878175169229507,0.9649062156677246,0.20606273412704468,0.9190575190575191
0.0723208338022232,0.972800612449646,0.19561436772346497,0.9173943173943174
0.06434523314237595,0.9761790037155151,0.19195745885372162,0.9223839223839224
0.053618937730789185,0.9800055027008057,0.18783912062644958,0.9234927234927235
0.04484820365905762,0.9835562705993652,0.2106543332338333,0.9100485100485101
0.04149951785802841,0.9840733408927917,0.18253885209560394,0.9225225225225225
0.0404784269630909,0.9856246709823608,0.20997869968414307,0.9167013167013167
0.030217930674552917,0.9891409277915955,0.24433661997318268,0.8828828828828829
0.03244226053357124,0.988623857498169,0.1922852247953415,0.9215523215523216
0.026851007714867592,0.9902785420417786,0.23004288971424103,0.9279279279279279
0.023497726768255234,0.9918298125267029,0.19656917452812195,0.9252945252945253
0.02674519456923008,0.9902785420417786,0.23503363132476807,0.9129591129591129
0.02193380519747734,0.9920711517333984,0.202240988612175,0.9162855162855162
0.020589010789990425,0.9929329752922058,0.208555206656456,0.9167013167013167
0.01889936253428459,0.9936913847923279,0.20776838064193726,0.9179487179487179
0.02025654911994934,0.9920711517333984,0.18817034363746643,0.9322245322245323
0.017306949943304062,0.9937947988510132,0.1834825575351715,0.9308385308385309
0.023727459833025932,0.9913127422332764,0.18858602643013,0.9280665280665281
0.014888867735862732,0.995208203792572,0.18189498782157898,0.9325017325017325
0.013862574473023415,0.9948635101318359,0.193190336227417,0.9287595287595287
0.01641395129263401,0.9937947988510132,0.21891357004642487,0.9191961191961192
0.013660856522619724,0.9950358271598816,0.18422821164131165,0.9318087318087318
0.01614476926624775,0.9946566224098206,0.18277159333229065,0.9333333333333333
0.007447440177202225,0.9972766041755676,0.20422905683517456,0.9280665280665281
0.01959548331797123,0.9926571846008301,0.2136637568473816,0.9167013167013167
0.013943370431661606,0.9950013756752014,0.19268900156021118,0.9347193347193348
0.00835932232439518,0.9975179433822632,0.21381810307502747,0.9293139293139293
0.021312842145562172,0.9927605986595154,0.19657018780708313,0.9290367290367291
0.0104135787114501,0.9964837431907654,0.20536072552204132,0.927096327096327
0.008009511977434158,0.9973455667495728,0.18802785873413086,0.9315315315315316
0.011838924139738083,0.9956908226013184,0.2566244602203369,0.9068607068607069
0.012200768105685711,0.9955874085426331,0.18894194066524506,0.9327789327789328
0.010845660232007504,0.9961734414100647,0.2005389928817749,0.928898128898129
0.0069356802850961685,0.9973800182342529,0.19547949731349945,0.9319473319473319
0.015998361632227898,0.9940705895423889,0.18427009880542755,0.9355509355509356
0.007555769290775061,0.9974834322929382,0.18633264303207397,0.9337491337491337
0.0077914041467010975,0.997759222984314,0.20254862308502197,0.9311157311157311
0.009187227115035057,0.9968629479408264,0.19707944989204407,0.9336105336105336
0.013306550681591034,0.9955874085426331,0.20513388514518738,0.9214137214137215
0.007872995920479298,0.9973111152648926,0.2373199164867401,0.9218295218295218
0.009518194012343884,0.9971731901168823,0.19580458104610443,0.928898128898129
0.009910705499351025,0.9967939853668213,0.19054722785949707,0.9302841302841303
0.006065532565116882,0.9976903200149536,0.2001960277557373,0.9316701316701317
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