epoch 0: {'accuracy': 0.8544755628775398} , current_best_acc: 0.8544755628775398 train_loss: 0.30724185705184937
epoch 1: {'accuracy': 0.8861431447922387} , current_best_acc: 0.8861431447922387 train_loss: 0.357625812292099
epoch 2: {'accuracy': 0.8850448471535787} , current_best_acc: 0.8861431447922387 train_loss: 0.8529186248779297
epoch 3: {'accuracy': 0.9011532125205931} , current_best_acc: 0.9011532125205931 train_loss: 0.13504037261009216
epoch 4: {'accuracy': 0.8932820794435292} , current_best_acc: 0.9011532125205931 train_loss: 0.780263364315033
epoch 5: {'accuracy': 0.885777045579352} , current_best_acc: 0.9011532125205931 train_loss: 0.07824008166790009
epoch 6: {'accuracy': 0.8971261211788395} , current_best_acc: 0.9011532125205931 train_loss: 0.08556803315877914
epoch 7: {'accuracy': 0.9024345597656965} , current_best_acc: 0.9024345597656965 train_loss: 0.4892178177833557
epoch 8: {'accuracy': 0.8925498810177558} , current_best_acc: 0.9024345597656965 train_loss: 0.20233555138111115
epoch 9: {'accuracy': 0.9046311550430166} , current_best_acc: 0.9046311550430166 train_loss: 0.1322474330663681
epoch 10: {'accuracy': 0.9070107999267801} , current_best_acc: 0.9070107999267801 train_loss: 0.2448350042104721
epoch 11: {'accuracy': 0.8991396668497162} , current_best_acc: 0.9070107999267801 train_loss: 0.5570254325866699
epoch 12: {'accuracy': 0.90481420464946} , current_best_acc: 0.9070107999267801 train_loss: 0.58100426197052
epoch 13: {'accuracy': 0.9097565440234303} , current_best_acc: 0.9097565440234303 train_loss: 0.11313031613826752
epoch 14: {'accuracy': 0.9049972542559034} , current_best_acc: 0.9097565440234303 train_loss: 0.3972558379173279
epoch 15: {'accuracy': 0.9035328574043566} , current_best_acc: 0.9097565440234303 train_loss: 0.06224667280912399
epoch 16: {'accuracy': 0.9038989566172433} , current_best_acc: 0.9097565440234303 train_loss: 0.1223926991224289
epoch 17: {'accuracy': 0.90536335346879} , current_best_acc: 0.9097565440234303 train_loss: 0.6587172746658325
epoch 18: {'accuracy': 0.9033498077979132} , current_best_acc: 0.9097565440234303 train_loss: 0.7596402764320374
epoch 19: {'accuracy': 0.9092073952041003} , current_best_acc: 0.9097565440234303 train_loss: 0.27409827709198
epoch 20: {'accuracy': 0.8967600219659527} , current_best_acc: 0.9097565440234303 train_loss: 0.8621534705162048
epoch 21: {'accuracy': 0.9125022881200805} , current_best_acc: 0.9125022881200805 train_loss: 0.2224067598581314
epoch 22: {'accuracy': 0.9121361889071938} , current_best_acc: 0.9125022881200805 train_loss: 0.6823095083236694
epoch 23: {'accuracy': 0.9114039904814205} , current_best_acc: 0.9125022881200805 train_loss: 0.38040804862976074
epoch 24: {'accuracy': 0.9132344865458539} , current_best_acc: 0.9132344865458539 train_loss: 0.05233647674322128
epoch 25: {'accuracy': 0.9121361889071938} , current_best_acc: 0.9132344865458539 train_loss: 0.1203313022851944
epoch 26: {'accuracy': 0.9121361889071938} , current_best_acc: 0.9132344865458539 train_loss: 0.06449035555124283
epoch 27: {'accuracy': 0.9163463298553908} , current_best_acc: 0.9163463298553908 train_loss: 0.06753043830394745
epoch 28: {'accuracy': 0.9139666849716274} , current_best_acc: 0.9163463298553908 train_loss: 0.878234326839447
epoch 29: {'accuracy': 0.917993776313381} , current_best_acc: 0.917993776313381 train_loss: 0.033591046929359436
epoch 30: {'accuracy': 0.909024345597657} , current_best_acc: 0.917993776313381 train_loss: 0.12006623297929764
epoch 31: {'accuracy': 0.917993776313381} , current_best_acc: 0.917993776313381 train_loss: 0.07693494111299515
epoch 32: {'accuracy': 0.9152480322167308} , current_best_acc: 0.917993776313381 train_loss: 0.18533030152320862
epoch 33: {'accuracy': 0.9170785282811642} , current_best_acc: 0.917993776313381 train_loss: 0.613854706287384
epoch 34: {'accuracy': 0.9115870400878638} , current_best_acc: 0.917993776313381 train_loss: 0.20700645446777344
epoch 35: {'accuracy': 0.9157971810360608} , current_best_acc: 0.917993776313381 train_loss: 0.40383318066596985
epoch 36: {'accuracy': 0.9178107267069375} , current_best_acc: 0.917993776313381 train_loss: 0.20173631608486176
epoch 37: {'accuracy': 0.9150649826102873} , current_best_acc: 0.917993776313381 train_loss: 0.046105582267045975
epoch 38: {'accuracy': 0.9146988833974007} , current_best_acc: 0.917993776313381 train_loss: 0.0631871297955513
epoch 39: {'accuracy': 0.9159802306425041} , current_best_acc: 0.917993776313381 train_loss: 0.12905873358249664
