epoch 0: {'accuracy': 0.5018050541516246} , current_best_acc: 0.5018050541516246 train_loss: 0.829047441482544
epoch 1: {'accuracy': 0.5342960288808665} , current_best_acc: 0.5342960288808665 train_loss: 0.7011020183563232
epoch 2: {'accuracy': 0.5703971119133574} , current_best_acc: 0.5703971119133574 train_loss: 0.680405855178833
epoch 3: {'accuracy': 0.5270758122743683} , current_best_acc: 0.5703971119133574 train_loss: 0.6941745281219482
epoch 4: {'accuracy': 0.5595667870036101} , current_best_acc: 0.5703971119133574 train_loss: 0.6811736822128296
epoch 5: {'accuracy': 0.7509025270758123} , current_best_acc: 0.7509025270758123 train_loss: 0.6989826560020447
epoch 6: {'accuracy': 0.7292418772563177} , current_best_acc: 0.7509025270758123 train_loss: 0.4037659466266632
epoch 7: {'accuracy': 0.779783393501805} , current_best_acc: 0.779783393501805 train_loss: 0.38674381375312805
epoch 8: {'accuracy': 0.8375451263537906} , current_best_acc: 0.8375451263537906 train_loss: 0.27233797311782837
epoch 9: {'accuracy': 0.7256317689530686} , current_best_acc: 0.8375451263537906 train_loss: 0.6086398959159851
epoch 10: {'accuracy': 0.8231046931407943} , current_best_acc: 0.8375451263537906 train_loss: 0.39014557003974915
epoch 11: {'accuracy': 0.5451263537906137} , current_best_acc: 0.8375451263537906 train_loss: 0.7161166667938232
epoch 12: {'accuracy': 0.6137184115523465} , current_best_acc: 0.8375451263537906 train_loss: 0.6593247652053833
epoch 13: {'accuracy': 0.6389891696750902} , current_best_acc: 0.8375451263537906 train_loss: 0.7493563294410706
epoch 14: {'accuracy': 0.7436823104693141} , current_best_acc: 0.8375451263537906 train_loss: 0.5567919611930847
epoch 15: {'accuracy': 0.779783393501805} , current_best_acc: 0.8375451263537906 train_loss: 0.31946536898612976
epoch 16: {'accuracy': 0.8122743682310469} , current_best_acc: 0.8375451263537906 train_loss: 0.3024049699306488
epoch 17: {'accuracy': 0.8339350180505415} , current_best_acc: 0.8375451263537906 train_loss: 0.35375526547431946
epoch 18: {'accuracy': 0.8483754512635379} , current_best_acc: 0.8483754512635379 train_loss: 0.3710496723651886
epoch 19: {'accuracy': 0.8267148014440433} , current_best_acc: 0.8483754512635379 train_loss: 0.5199189782142639
epoch 20: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8592057761732852 train_loss: 0.36389854550361633
epoch 21: {'accuracy': 0.855595667870036} , current_best_acc: 0.8592057761732852 train_loss: 0.3006477952003479
epoch 22: {'accuracy': 0.8411552346570397} , current_best_acc: 0.8592057761732852 train_loss: 0.3008865714073181
epoch 23: {'accuracy': 0.851985559566787} , current_best_acc: 0.8592057761732852 train_loss: 0.2150099128484726
epoch 24: {'accuracy': 0.851985559566787} , current_best_acc: 0.8592057761732852 train_loss: 0.1297999769449234
epoch 25: {'accuracy': 0.8194945848375451} , current_best_acc: 0.8592057761732852 train_loss: 0.0756375715136528
epoch 26: {'accuracy': 0.851985559566787} , current_best_acc: 0.8592057761732852 train_loss: 0.6966813802719116
epoch 27: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8592057761732852 train_loss: 0.24496494233608246
epoch 28: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8592057761732852 train_loss: 0.2398642748594284
epoch 29: {'accuracy': 0.8447653429602888} , current_best_acc: 0.8592057761732852 train_loss: 0.11047094315290451
epoch 30: {'accuracy': 0.855595667870036} , current_best_acc: 0.8592057761732852 train_loss: 0.06660948693752289
epoch 31: {'accuracy': 0.8628158844765343} , current_best_acc: 0.8628158844765343 train_loss: 0.08518191426992416
epoch 32: {'accuracy': 0.8628158844765343} , current_best_acc: 0.8628158844765343 train_loss: 0.16175292432308197
epoch 33: {'accuracy': 0.8700361010830325} , current_best_acc: 0.8700361010830325 train_loss: 0.26580360531806946
epoch 34: {'accuracy': 0.8736462093862816} , current_best_acc: 0.8736462093862816 train_loss: 0.01971231959760189
epoch 35: {'accuracy': 0.8628158844765343} , current_best_acc: 0.8736462093862816 train_loss: 0.07404253631830215
epoch 36: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8736462093862816 train_loss: 0.21063362061977386
epoch 37: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8736462093862816 train_loss: 0.3592805862426758
epoch 38: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8736462093862816 train_loss: 0.14811545610427856
epoch 39: {'accuracy': 0.8700361010830325} , current_best_acc: 0.8736462093862816 train_loss: 0.07222877442836761
epoch 40: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8736462093862816 train_loss: 0.09076304733753204
epoch 41: {'accuracy': 0.8844765342960289} , current_best_acc: 0.8844765342960289 train_loss: 0.15491904318332672
epoch 42: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8844765342960289 train_loss: 0.21674726903438568
epoch 43: {'accuracy': 0.8628158844765343} , current_best_acc: 0.8844765342960289 train_loss: 0.09601567685604095
epoch 44: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8844765342960289 train_loss: 0.21782270073890686
epoch 45: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8844765342960289 train_loss: 0.017935022711753845
epoch 46: {'accuracy': 0.8592057761732852} , current_best_acc: 0.8844765342960289 train_loss: 0.23184658586978912
epoch 47: {'accuracy': 0.8628158844765343} , current_best_acc: 0.8844765342960289 train_loss: 0.059439726173877716
epoch 48: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8844765342960289 train_loss: 0.06990738213062286
epoch 49: {'accuracy': 0.8664259927797834} , current_best_acc: 0.8844765342960289 train_loss: 0.12307988852262497
