epoch 0: {'accuracy': 0.8967889908256881} , current_best_acc: 0.8967889908256881 train_loss: 0.4169226288795471
epoch 1: {'accuracy': 0.9346330275229358} , current_best_acc: 0.9346330275229358 train_loss: 0.2006998062133789
epoch 2: {'accuracy': 0.930045871559633} , current_best_acc: 0.9346330275229358 train_loss: 0.34855836629867554
epoch 3: {'accuracy': 0.9311926605504587} , current_best_acc: 0.9346330275229358 train_loss: 0.06796910613775253
epoch 4: {'accuracy': 0.9311926605504587} , current_best_acc: 0.9346330275229358 train_loss: 0.39601558446884155
epoch 5: {'accuracy': 0.9277522935779816} , current_best_acc: 0.9346330275229358 train_loss: 0.14314958453178406
epoch 6: {'accuracy': 0.9288990825688074} , current_best_acc: 0.9346330275229358 train_loss: 0.20489774644374847
epoch 7: {'accuracy': 0.9380733944954128} , current_best_acc: 0.9380733944954128 train_loss: 0.22955356538295746
epoch 8: {'accuracy': 0.9288990825688074} , current_best_acc: 0.9380733944954128 train_loss: 0.36724820733070374
epoch 9: {'accuracy': 0.9357798165137615} , current_best_acc: 0.9380733944954128 train_loss: 0.13666680455207825
epoch 10: {'accuracy': 0.926605504587156} , current_best_acc: 0.9380733944954128 train_loss: 0.3585853576660156
epoch 11: {'accuracy': 0.926605504587156} , current_best_acc: 0.9380733944954128 train_loss: 0.22212250530719757
epoch 12: {'accuracy': 0.9369266055045872} , current_best_acc: 0.9380733944954128 train_loss: 0.28659719228744507
epoch 13: {'accuracy': 0.9426605504587156} , current_best_acc: 0.9426605504587156 train_loss: 0.20873896777629852
epoch 14: {'accuracy': 0.9346330275229358} , current_best_acc: 0.9426605504587156 train_loss: 0.36839672923088074
epoch 15: {'accuracy': 0.9231651376146789} , current_best_acc: 0.9426605504587156 train_loss: 0.3648007810115814
epoch 16: {'accuracy': 0.9323394495412844} , current_best_acc: 0.9426605504587156 train_loss: 0.1443691998720169
epoch 17: {'accuracy': 0.9461009174311926} , current_best_acc: 0.9461009174311926 train_loss: 0.46830010414123535
epoch 18: {'accuracy': 0.9380733944954128} , current_best_acc: 0.9461009174311926 train_loss: 0.30988791584968567
epoch 19: {'accuracy': 0.9346330275229358} , current_best_acc: 0.9461009174311926 train_loss: 0.24698135256767273
epoch 20: {'accuracy': 0.9369266055045872} , current_best_acc: 0.9461009174311926 train_loss: 0.18486620485782623
epoch 21: {'accuracy': 0.9380733944954128} , current_best_acc: 0.9461009174311926 train_loss: 0.17878802120685577
epoch 22: {'accuracy': 0.9346330275229358} , current_best_acc: 0.9461009174311926 train_loss: 0.3699135482311249
epoch 23: {'accuracy': 0.9369266055045872} , current_best_acc: 0.9461009174311926 train_loss: 0.0986592173576355
epoch 24: {'accuracy': 0.9403669724770642} , current_best_acc: 0.9461009174311926 train_loss: 0.3929610550403595
epoch 25: {'accuracy': 0.9415137614678899} , current_best_acc: 0.9461009174311926 train_loss: 0.13758136332035065
epoch 26: {'accuracy': 0.9334862385321101} , current_best_acc: 0.9461009174311926 train_loss: 0.2511243224143982
epoch 27: {'accuracy': 0.9392201834862385} , current_best_acc: 0.9461009174311926 train_loss: 0.13183918595314026
epoch 28: {'accuracy': 0.9277522935779816} , current_best_acc: 0.9461009174311926 train_loss: 0.08656521886587143
epoch 29: {'accuracy': 0.9403669724770642} , current_best_acc: 0.9461009174311926 train_loss: 0.11692367494106293

