Encoder params: EncoderParams(80,80,80,Attention,Unified,false,gtype.EncoderParams$$$Lambda$6/759156157@61832929)
encodingIterations: 10
trainingEncodingBatch: 1
optimizer: Adam(0.002,0.9,0.999,1.0E-8)
dev set graph size: 252
pos relations: 934, neg relations: 62318, reflexivity: 252
test set graph size: 277
pos relations: 1287, neg relations: 75165, reflexivity: 277
[0] JSCore104 	 loss: 0.69,	 accuracy = 0.5149
[1] Train173 	 loss: 0.69,	 accuracy = 0.4891
[2] JSCore133 	 loss: 0.69,	 accuracy = 0.5935
[3] Train116 	 loss: 0.69,	 accuracy = 0.4986
[4] Train131 	 loss: 0.69,	 accuracy = 0.5181
[5] Train129 	 loss: 0.69,	 accuracy = 0.7197
[6] Train123 	 loss: 0.69,	 accuracy = 0.6731
[7] Train151 	 loss: 0.69,	 accuracy = 0.6313
[8] Train155 	 loss: 0.68,	 accuracy = 0.6505
[9] JSCore176 	 loss: 0.68,	 accuracy = 0.6367
[10] JSCore125 	 loss: 0.69,	 accuracy = 0.5498
[11] JSCore113 	 loss: 0.67,	 accuracy = 0.5458
[12] Train115 	 loss: 0.66,	 accuracy = 0.6567
[13] JSCore119 	 loss: 0.66,	 accuracy = 0.5388
[14] JSCore119 	 loss: 0.65,	 accuracy = 0.6552
[15] JSCore182 	 loss: 0.64,	 accuracy = 0.6355
[16] JSCore170 	 loss: 0.64,	 accuracy = 0.6127
[17] JSCore112 	 loss: 0.64,	 accuracy = 0.5598
[18] JSCore101 	 loss: 0.63,	 accuracy = 0.5241
[19] JSCore197 	 loss: 0.62,	 accuracy = 0.5740
[20] Train179 	 loss: 0.58,	 accuracy = 0.7527
[21] JSCore174 	 loss: 0.59,	 accuracy = 0.6679
[22] JSCore176 	 loss: 0.56,	 accuracy = 0.6750
[23] Train197 	 loss: 0.51,	 accuracy = 0.7130
[24] JSCore184 	 loss: 0.55,	 accuracy = 0.5583
[25] JSCore123 	 loss: 0.52,	 accuracy = 0.6279
[25] dev set  	 loss: 0.56,	 accuracy = 0.6567
[25] test set 	 loss: 0.52,	 accuracy = 0.6783
[26] JSCore172 	 loss: 0.61,	 accuracy = 0.5904
[27] Train116 	 loss: 0.48,	 accuracy = 0.7889
[28] Train159 	 loss: 0.54,	 accuracy = 0.5804
[29] JSCore125 	 loss: 0.55,	 accuracy = 0.5574
[30] Train153 	 loss: 0.50,	 accuracy = 0.6416
[31] JSCore193 	 loss: 0.52,	 accuracy = 0.7259
[32] JSCore148 	 loss: 0.55,	 accuracy = 0.6749
[33] Train187 	 loss: 0.53,	 accuracy = 0.7235
[34] JSCore171 	 loss: 0.53,	 accuracy = 0.7237
[35] JSCore185 	 loss: 0.53,	 accuracy = 0.6827
[36] Train174 	 loss: 0.48,	 accuracy = 0.7527
[37] JSCore138 	 loss: 0.58,	 accuracy = 0.5720
[38] Train194 	 loss: 0.48,	 accuracy = 0.7062
[39] Train190 	 loss: 0.44,	 accuracy = 0.7752
[40] Train120 	 loss: 0.49,	 accuracy = 0.7843
[41] JSCore130 	 loss: 0.56,	 accuracy = 0.7030
[42] JSCore127 	 loss: 0.53,	 accuracy = 0.6867
[43] JSCore165 	 loss: 0.48,	 accuracy = 0.7448
[44] JSCore117 	 loss: 0.51,	 accuracy = 0.7007
[45] JSCore163 	 loss: 0.54,	 accuracy = 0.6298
[46] Train119 	 loss: 0.47,	 accuracy = 0.7620
[47] Train189 	 loss: 0.50,	 accuracy = 0.6951
[48] Train179 	 loss: 0.49,	 accuracy = 0.7678
[49] Train163 	 loss: 0.46,	 accuracy = 0.7784
[50] JSCore132 	 loss: 0.50,	 accuracy = 0.7305
[50] dev set  	 loss: 0.51,	 accuracy = 0.7300
[50] test set 	 loss: 0.46,	 accuracy = 0.7533
[51] JSCore181 	 loss: 0.46,	 accuracy = 0.7527
[52] JSCore169 	 loss: 0.52,	 accuracy = 0.7191
[53] JSCore191 	 loss: 0.54,	 accuracy = 0.7020
[54] Train101 	 loss: 0.48,	 accuracy = 0.7643
[55] Train106 	 loss: 0.47,	 accuracy = 0.7348
[56] Train181 	 loss: 0.45,	 accuracy = 0.7776
[57] JSCore164 	 loss: 0.51,	 accuracy = 0.6998
[58] JSCore142 	 loss: 0.49,	 accuracy = 0.7553
[59] JSCore197 	 loss: 0.52,	 accuracy = 0.7530
[60] JSCore185 	 loss: 0.57,	 accuracy = 0.6957
[61] Train130 	 loss: 0.51,	 accuracy = 0.8010
[62] Train194 	 loss: 0.44,	 accuracy = 0.8287
[63] Train128 	 loss: 0.48,	 accuracy = 0.7439
[64] Train111 	 loss: 0.52,	 accuracy = 0.6421
[65] Train196 	 loss: 0.45,	 accuracy = 0.7735
[66] Train187 	 loss: 0.47,	 accuracy = 0.7899
[67] JSCore145 	 loss: 0.50,	 accuracy = 0.7625
[68] Train193 	 loss: 0.47,	 accuracy = 0.8352
[69] JSCore116 	 loss: 0.46,	 accuracy = 0.7889
[70] Train196 	 loss: 0.47,	 accuracy = 0.7965
[71] Train187 	 loss: 0.44,	 accuracy = 0.8362
[72] JSCore169 	 loss: 0.48,	 accuracy = 0.7762
[73] JSCore129 	 loss: 0.51,	 accuracy = 0.7831
[74] JSCore192 	 loss: 0.51,	 accuracy = 0.7192
[75] Train125 	 loss: 0.42,	 accuracy = 0.8109
[75] dev set  	 loss: 0.48,	 accuracy = 0.8100
[75] test set 	 loss: 0.44,	 accuracy = 0.8117
[76] JSCore200 	 loss: 0.51,	 accuracy = 0.7818
[77] Train153 	 loss: 0.43,	 accuracy = 0.8031
[78] JSCore162 	 loss: 0.47,	 accuracy = 0.8068
[79] JSCore130 	 loss: 0.48,	 accuracy = 0.7728
[80] Train101 	 loss: 0.40,	 accuracy = 0.8298
[81] Train196 	 loss: 0.43,	 accuracy = 0.8403
[82] JSCore123 	 loss: 0.46,	 accuracy = 0.8215
[83] JSCore128 	 loss: 0.43,	 accuracy = 0.8524
[84] JSCore103 	 loss: 0.40,	 accuracy = 0.8407
[85] Train144 	 loss: 0.42,	 accuracy = 0.8225
[86] Train140 	 loss: 0.35,	 accuracy = 0.8478
[87] JSCore159 	 loss: 0.41,	 accuracy = 0.8145
[88] JSCore117 	 loss: 0.45,	 accuracy = 0.7801
[89] Train157 	 loss: 0.47,	 accuracy = 0.7733
[90] JSCore108 	 loss: 0.40,	 accuracy = 0.8443
[91] Train185 	 loss: 0.44,	 accuracy = 0.8265
[92] JSCore177 	 loss: 0.41,	 accuracy = 0.8156
[93] JSCore101 	 loss: 0.38,	 accuracy = 0.8344
[94] Train114 	 loss: 0.36,	 accuracy = 0.8604
[95] Train183 	 loss: 0.39,	 accuracy = 0.8235
[96] Train166 	 loss: 0.42,	 accuracy = 0.8100
[97] Train149 	 loss: 0.42,	 accuracy = 0.8366
[98] JSCore106 	 loss: 0.37,	 accuracy = 0.8503
[99] JSCore154 	 loss: 0.38,	 accuracy = 0.8355
[100] Train128 	 loss: 0.35,	 accuracy = 0.8625
[100] dev set  	 loss: 0.39,	 accuracy = 0.8567
[100] test set 	 loss: 0.37,	 accuracy = 0.8550
[101] Train133 	 loss: 0.36,	 accuracy = 0.8781
[102] Train135 	 loss: 0.36,	 accuracy = 0.8640
[103] Train156 	 loss: 0.35,	 accuracy = 0.8497
[104] Train165 	 loss: 0.35,	 accuracy = 0.8583
[105] Train113 	 loss: 0.34,	 accuracy = 0.8664
[106] Train184 	 loss: 0.37,	 accuracy = 0.8380
[107] Train173 	 loss: 0.36,	 accuracy = 0.8365
[108] JSCore164 	 loss: 0.39,	 accuracy = 0.8083
[109] Train166 	 loss: 0.36,	 accuracy = 0.8286
[110] JSCore173 	 loss: 0.38,	 accuracy = 0.8452
[111] JSCore117 	 loss: 0.40,	 accuracy = 0.8414
[112] JSCore125 	 loss: 0.40,	 accuracy = 0.8176
[113] Train106 	 loss: 0.32,	 accuracy = 0.8947
[114] Train157 	 loss: 0.38,	 accuracy = 0.8607
[115] Train155 	 loss: 0.33,	 accuracy = 0.8823
[116] Train123 	 loss: 0.35,	 accuracy = 0.8722
[117] JSCore194 	 loss: 0.43,	 accuracy = 0.7956
[118] Train116 	 loss: 0.35,	 accuracy = 0.8624
[119] Train138 	 loss: 0.39,	 accuracy = 0.8647
[120] Train139 	 loss: 0.33,	 accuracy = 0.8859
[121] Train155 	 loss: 0.35,	 accuracy = 0.8529
[122] JSCore102 	 loss: 0.42,	 accuracy = 0.8286
[123] Train152 	 loss: 0.33,	 accuracy = 0.8821
[124] JSCore149 	 loss: 0.39,	 accuracy = 0.8480
[125] JSCore171 	 loss: 0.39,	 accuracy = 0.8355
[125] dev set  	 loss: 0.37,	 accuracy = 0.8633
[125] test set 	 loss: 0.36,	 accuracy = 0.8350
[126] JSCore132 	 loss: 0.32,	 accuracy = 0.8678
[127] JSCore127 	 loss: 0.38,	 accuracy = 0.8422
[128] JSCore115 	 loss: 0.38,	 accuracy = 0.8564
[129] Train114 	 loss: 0.31,	 accuracy = 0.8808
[130] Train137 	 loss: 0.40,	 accuracy = 0.8181
[131] Train130 	 loss: 0.33,	 accuracy = 0.8700
[132] JSCore166 	 loss: 0.39,	 accuracy = 0.8303
[133] JSCore184 	 loss: 0.46,	 accuracy = 0.7891
[134] JSCore144 	 loss: 0.38,	 accuracy = 0.8304
[135] Train174 	 loss: 0.37,	 accuracy = 0.8301
[136] JSCore158 	 loss: 0.38,	 accuracy = 0.8352
[137] Train145 	 loss: 0.32,	 accuracy = 0.8709
[138] Train125 	 loss: 0.33,	 accuracy = 0.8682
[139] JSCore168 	 loss: 0.35,	 accuracy = 0.8608
[140] Train196 	 loss: 0.30,	 accuracy = 0.8874
[141] JSCore177 	 loss: 0.40,	 accuracy = 0.8434
[142] Train105 	 loss: 0.36,	 accuracy = 0.8432
[143] Train114 	 loss: 0.39,	 accuracy = 0.7777
[144] Train119 	 loss: 0.37,	 accuracy = 0.8415
[145] JSCore174 	 loss: 0.40,	 accuracy = 0.8133
[146] Train121 	 loss: 0.39,	 accuracy = 0.8281
[147] JSCore104 	 loss: 0.42,	 accuracy = 0.8101
[148] JSCore151 	 loss: 0.36,	 accuracy = 0.8214
[149] JSCore142 	 loss: 0.39,	 accuracy = 0.8193
[150] JSCore103 	 loss: 0.35,	 accuracy = 0.8441
[150] dev set  	 loss: 0.38,	 accuracy = 0.8667
[150] test set 	 loss: 0.34,	 accuracy = 0.8517
[151] Train107 	 loss: 0.32,	 accuracy = 0.8706
[152] JSCore131 	 loss: 0.31,	 accuracy = 0.8664
[153] JSCore195 	 loss: 0.41,	 accuracy = 0.8301
[154] Train175 	 loss: 0.37,	 accuracy = 0.8443
[155] Train135 	 loss: 0.45,	 accuracy = 0.8137
[156] Train151 	 loss: 0.36,	 accuracy = 0.8650
[157] Train149 	 loss: 0.45,	 accuracy = 0.8525
[158] JSCore102 	 loss: 0.36,	 accuracy = 0.8462
[159] JSCore136 	 loss: 0.41,	 accuracy = 0.8282
[160] JSCore106 	 loss: 0.42,	 accuracy = 0.8430
[161] JSCore146 	 loss: 0.41,	 accuracy = 0.8480
[162] Train108 	 loss: 0.34,	 accuracy = 0.8893
[163] Train114 	 loss: 0.36,	 accuracy = 0.8709
[164] Train199 	 loss: 0.34,	 accuracy = 0.8884
[165] Train198 	 loss: 0.39,	 accuracy = 0.8610
[166] Train184 	 loss: 0.34,	 accuracy = 0.8683
[167] JSCore189 	 loss: 0.37,	 accuracy = 0.8454
[168] JSCore155 	 loss: 0.37,	 accuracy = 0.8406
[169] Train118 	 loss: 0.34,	 accuracy = 0.8605
[170] JSCore168 	 loss: 0.39,	 accuracy = 0.8299
[171] JSCore177 	 loss: 0.33,	 accuracy = 0.8691
[172] Train192 	 loss: 0.35,	 accuracy = 0.8610
[173] Train183 	 loss: 0.34,	 accuracy = 0.8595
[174] JSCore176 	 loss: 0.35,	 accuracy = 0.8331
[175] JSCore146 	 loss: 0.35,	 accuracy = 0.8386
[175] dev set  	 loss: 0.34,	 accuracy = 0.8617
[175] test set 	 loss: 0.32,	 accuracy = 0.8650
[176] JSCore122 	 loss: 0.31,	 accuracy = 0.8625
[177] Train178 	 loss: 0.26,	 accuracy = 0.9076
[178] Train104 	 loss: 0.30,	 accuracy = 0.8666
[179] JSCore161 	 loss: 0.40,	 accuracy = 0.8185
[180] JSCore135 	 loss: 0.31,	 accuracy = 0.8770
[181] Train127 	 loss: 0.38,	 accuracy = 0.8181
[182] Train171 	 loss: 0.34,	 accuracy = 0.8492
[183] Train194 	 loss: 0.32,	 accuracy = 0.8865
[184] Train178 	 loss: 0.38,	 accuracy = 0.8526
[185] JSCore129 	 loss: 0.31,	 accuracy = 0.8856
[186] Train156 	 loss: 0.42,	 accuracy = 0.7993
[187] JSCore117 	 loss: 0.36,	 accuracy = 0.8333
[188] JSCore140 	 loss: 0.33,	 accuracy = 0.8723
[189] JSCore170 	 loss: 0.31,	 accuracy = 0.8732
[190] JSCore188 	 loss: 0.40,	 accuracy = 0.8006
[191] Train141 	 loss: 0.34,	 accuracy = 0.8802
[192] JSCore173 	 loss: 0.31,	 accuracy = 0.8723
[193] Train106 	 loss: 0.33,	 accuracy = 0.8797
[194] Train158 	 loss: 0.39,	 accuracy = 0.8447
[195] JSCore138 	 loss: 0.34,	 accuracy = 0.8662
[196] Train119 	 loss: 0.37,	 accuracy = 0.8643
[197] Train107 	 loss: 0.33,	 accuracy = 0.8984
[198] JSCore150 	 loss: 0.30,	 accuracy = 0.8941
[199] JSCore116 	 loss: 0.34,	 accuracy = 0.8779
[200] JSCore142 	 loss: 0.34,	 accuracy = 0.8608
[200] dev set  	 loss: 0.35,	 accuracy = 0.8700
[200] test set 	 loss: 0.30,	 accuracy = 0.8817
[201] JSCore175 	 loss: 0.31,	 accuracy = 0.8730
[202] JSCore126 	 loss: 0.32,	 accuracy = 0.8792
[203] Train130 	 loss: 0.35,	 accuracy = 0.8671
[204] JSCore108 	 loss: 0.30,	 accuracy = 0.8826
[205] Train116 	 loss: 0.33,	 accuracy = 0.8763
[206] JSCore191 	 loss: 0.31,	 accuracy = 0.8713
[207] Train121 	 loss: 0.29,	 accuracy = 0.8852
[208] Train101 	 loss: 0.28,	 accuracy = 0.8977
[209] JSCore123 	 loss: 0.31,	 accuracy = 0.8725
[210] JSCore155 	 loss: 0.35,	 accuracy = 0.8465
[211] Train156 	 loss: 0.42,	 accuracy = 0.8191
[212] JSCore161 	 loss: 0.28,	 accuracy = 0.8940
[213] Train164 	 loss: 0.34,	 accuracy = 0.8642
[214] JSCore155 	 loss: 0.26,	 accuracy = 0.8950
[215] JSCore158 	 loss: 0.28,	 accuracy = 0.8870
[216] JSCore139 	 loss: 0.31,	 accuracy = 0.8888
[217] JSCore171 	 loss: 0.30,	 accuracy = 0.8920
[218] Train159 	 loss: 0.36,	 accuracy = 0.8638
[219] Train159 	 loss: 0.29,	 accuracy = 0.8859
[220] Train103 	 loss: 0.31,	 accuracy = 0.8938
[221] JSCore192 	 loss: 0.31,	 accuracy = 0.8725
[222] Train147 	 loss: 0.33,	 accuracy = 0.8831
[223] Train183 	 loss: 0.36,	 accuracy = 0.8613
[224] JSCore177 	 loss: 0.28,	 accuracy = 0.8836
[225] JSCore124 	 loss: 0.34,	 accuracy = 0.8482
[225] dev set  	 loss: 0.27,	 accuracy = 0.9017
[225] test set 	 loss: 0.29,	 accuracy = 0.8783
[226] JSCore136 	 loss: 0.30,	 accuracy = 0.8781
[227] JSCore193 	 loss: 0.31,	 accuracy = 0.8774
[228] Train197 	 loss: 0.31,	 accuracy = 0.8736
[229] Train200 	 loss: 0.36,	 accuracy = 0.7971
[230] Train166 	 loss: 0.29,	 accuracy = 0.8830
[231] JSCore175 	 loss: 0.33,	 accuracy = 0.8643
[232] JSCore119 	 loss: 0.27,	 accuracy = 0.8980
[233] Train188 	 loss: 0.34,	 accuracy = 0.8638
[234] Train188 	 loss: 0.29,	 accuracy = 0.8951
[235] JSCore190 	 loss: 0.29,	 accuracy = 0.8754
[236] JSCore151 	 loss: 0.24,	 accuracy = 0.9121
[237] JSCore198 	 loss: 0.25,	 accuracy = 0.9009
[238] JSCore155 	 loss: 0.25,	 accuracy = 0.9089
[239] Train176 	 loss: 0.33,	 accuracy = 0.8628
[240] JSCore192 	 loss: 0.37,	 accuracy = 0.8442
[241] JSCore155 	 loss: 0.30,	 accuracy = 0.8859
[242] Train169 	 loss: 0.30,	 accuracy = 0.8938
[243] Train175 	 loss: 0.35,	 accuracy = 0.8433
[244] Train147 	 loss: 0.31,	 accuracy = 0.8762
[245] Train165 	 loss: 0.27,	 accuracy = 0.8996
[246] JSCore121 	 loss: 0.31,	 accuracy = 0.8434
[247] JSCore136 	 loss: 0.29,	 accuracy = 0.8722
[248] Train133 	 loss: 0.31,	 accuracy = 0.8885
[249] JSCore178 	 loss: 0.28,	 accuracy = 0.8958
[250] JSCore169 	 loss: 0.30,	 accuracy = 0.8903
[250] dev set  	 loss: 0.32,	 accuracy = 0.8567
[250] test set 	 loss: 0.29,	 accuracy = 0.8800
[251] Train128 	 loss: 0.32,	 accuracy = 0.8738
[252] JSCore171 	 loss: 0.31,	 accuracy = 0.8877
[253] JSCore140 	 loss: 0.23,	 accuracy = 0.9267
[254] Train193 	 loss: 0.34,	 accuracy = 0.8730
[255] JSCore172 	 loss: 0.33,	 accuracy = 0.8826
[256] JSCore196 	 loss: 0.22,	 accuracy = 0.9331
[257] JSCore129 	 loss: 0.22,	 accuracy = 0.9127
[258] JSCore189 	 loss: 0.29,	 accuracy = 0.8717
[259] Train200 	 loss: 0.28,	 accuracy = 0.8771
[260] JSCore125 	 loss: 0.31,	 accuracy = 0.8548
[261] JSCore170 	 loss: 0.30,	 accuracy = 0.8794
[262] JSCore173 	 loss: 0.26,	 accuracy = 0.8946
[263] JSCore154 	 loss: 0.23,	 accuracy = 0.9179
[264] Train186 	 loss: 0.32,	 accuracy = 0.8714
[265] JSCore167 	 loss: 0.27,	 accuracy = 0.8783
[266] Train159 	 loss: 0.24,	 accuracy = 0.9099
[267] JSCore101 	 loss: 0.24,	 accuracy = 0.9108
[268] JSCore137 	 loss: 0.28,	 accuracy = 0.8844
[269] Train198 	 loss: 0.31,	 accuracy = 0.8821
[270] Train174 	 loss: 0.33,	 accuracy = 0.8767
[271] JSCore101 	 loss: 0.27,	 accuracy = 0.8791
[272] JSCore151 	 loss: 0.28,	 accuracy = 0.8857
[273] JSCore108 	 loss: 0.25,	 accuracy = 0.9028
[274] JSCore184 	 loss: 0.25,	 accuracy = 0.9010
[275] JSCore184 	 loss: 0.30,	 accuracy = 0.8814
[275] dev set  	 loss: 0.27,	 accuracy = 0.9017
[275] test set 	 loss: 0.28,	 accuracy = 0.8950
[276] Train147 	 loss: 0.28,	 accuracy = 0.8912
[277] JSCore198 	 loss: 0.26,	 accuracy = 0.8979
[278] Train127 	 loss: 0.27,	 accuracy = 0.8992
[279] JSCore109 	 loss: 0.26,	 accuracy = 0.9003
[280] Train198 	 loss: 0.33,	 accuracy = 0.8659
[281] JSCore119 	 loss: 0.27,	 accuracy = 0.8883
[282] Train132 	 loss: 0.23,	 accuracy = 0.9230
[283] JSCore189 	 loss: 0.24,	 accuracy = 0.8935
[284] Train170 	 loss: 0.29,	 accuracy = 0.8874
[285] Train180 	 loss: 0.28,	 accuracy = 0.8882
[286] Train134 	 loss: 0.22,	 accuracy = 0.9235
[287] JSCore184 	 loss: 0.24,	 accuracy = 0.9134
[288] Train150 	 loss: 0.31,	 accuracy = 0.8892
[289] JSCore137 	 loss: 0.27,	 accuracy = 0.8937
[290] JSCore176 	 loss: 0.27,	 accuracy = 0.8894
[291] JSCore156 	 loss: 0.25,	 accuracy = 0.8930
[292] Train187 	 loss: 0.29,	 accuracy = 0.8790
[293] Train122 	 loss: 0.29,	 accuracy = 0.8784
[294] JSCore124 	 loss: 0.27,	 accuracy = 0.9083
[295] JSCore180 	 loss: 0.24,	 accuracy = 0.9116
[296] JSCore108 	 loss: 0.22,	 accuracy = 0.9282
[297] Train186 	 loss: 0.30,	 accuracy = 0.8726
[298] JSCore155 	 loss: 0.29,	 accuracy = 0.8798
[299] JSCore103 	 loss: 0.25,	 accuracy = 0.9056
[300] JSCore126 	 loss: 0.25,	 accuracy = 0.9110
[300] dev set  	 loss: 0.27,	 accuracy = 0.8817
[300] test set 	 loss: 0.26,	 accuracy = 0.8933
[301] Train123 	 loss: 0.26,	 accuracy = 0.9106
[302] JSCore102 	 loss: 0.23,	 accuracy = 0.9142
[303] JSCore155 	 loss: 0.32,	 accuracy = 0.8543
[304] Train136 	 loss: 0.32,	 accuracy = 0.8688
[305] Train192 	 loss: 0.27,	 accuracy = 0.8973
[306] JSCore110 	 loss: 0.22,	 accuracy = 0.9162
[307] JSCore119 	 loss: 0.28,	 accuracy = 0.8834
[308] JSCore164 	 loss: 0.20,	 accuracy = 0.9347
[309] Train103 	 loss: 0.23,	 accuracy = 0.9205
[310] JSCore105 	 loss: 0.23,	 accuracy = 0.9170
[311] JSCore136 	 loss: 0.25,	 accuracy = 0.9029
[312] JSCore186 	 loss: 0.26,	 accuracy = 0.8942
[313] JSCore193 	 loss: 0.19,	 accuracy = 0.9292
[314] JSCore126 	 loss: 0.29,	 accuracy = 0.8872
[315] JSCore163 	 loss: 0.27,	 accuracy = 0.8997
[316] Train110 	 loss: 0.30,	 accuracy = 0.9042
[317] JSCore164 	 loss: 0.26,	 accuracy = 0.9009
[318] JSCore156 	 loss: 0.23,	 accuracy = 0.9166
[319] JSCore175 	 loss: 0.27,	 accuracy = 0.9137
[320] JSCore176 	 loss: 0.28,	 accuracy = 0.8956
[321] JSCore147 	 loss: 0.24,	 accuracy = 0.9199
[322] Train103 	 loss: 0.26,	 accuracy = 0.9021
[323] Train181 	 loss: 0.35,	 accuracy = 0.8388
[324] JSCore114 	 loss: 0.25,	 accuracy = 0.9108
[325] Train154 	 loss: 0.30,	 accuracy = 0.8884
[325] dev set  	 loss: 0.22,	 accuracy = 0.9133
[325] test set 	 loss: 0.24,	 accuracy = 0.9133
[326] Train169 	 loss: 0.30,	 accuracy = 0.8747
[327] Train145 	 loss: 0.26,	 accuracy = 0.9003
[328] JSCore179 	 loss: 0.25,	 accuracy = 0.9068
[329] JSCore101 	 loss: 0.25,	 accuracy = 0.9168
[330] Train114 	 loss: 0.27,	 accuracy = 0.8927
[331] Train104 	 loss: 0.31,	 accuracy = 0.8793
[332] Train143 	 loss: 0.27,	 accuracy = 0.9051
[333] Train174 	 loss: 0.27,	 accuracy = 0.9084
[334] Train161 	 loss: 0.28,	 accuracy = 0.8967
[335] Train124 	 loss: 0.29,	 accuracy = 0.8777
[336] Train166 	 loss: 0.29,	 accuracy = 0.8805
[337] JSCore184 	 loss: 0.31,	 accuracy = 0.8720
[338] JSCore109 	 loss: 0.30,	 accuracy = 0.8633
[339] Train125 	 loss: 0.27,	 accuracy = 0.8907
[340] JSCore143 	 loss: 0.30,	 accuracy = 0.8776
[341] Train142 	 loss: 0.22,	 accuracy = 0.9163
[342] JSCore192 	 loss: 0.26,	 accuracy = 0.9008
[343] Train155 	 loss: 0.40,	 accuracy = 0.8372
[344] JSCore149 	 loss: 0.25,	 accuracy = 0.9075
[345] Train115 	 loss: 0.22,	 accuracy = 0.9245
[346] Train128 	 loss: 0.28,	 accuracy = 0.8852
[347] JSCore185 	 loss: 0.24,	 accuracy = 0.9064
[348] Train199 	 loss: 0.25,	 accuracy = 0.8975
[349] Train166 	 loss: 0.25,	 accuracy = 0.8968
[350] JSCore196 	 loss: 0.24,	 accuracy = 0.9214
[350] dev set  	 loss: 0.20,	 accuracy = 0.9250
[350] test set 	 loss: 0.24,	 accuracy = 0.9067
[351] Train121 	 loss: 0.22,	 accuracy = 0.9160
[352] Train138 	 loss: 0.25,	 accuracy = 0.9020
[353] JSCore125 	 loss: 0.27,	 accuracy = 0.8946
[354] JSCore169 	 loss: 0.23,	 accuracy = 0.9046
[355] Train125 	 loss: 0.26,	 accuracy = 0.8956
[356] JSCore185 	 loss: 0.21,	 accuracy = 0.9221
[357] JSCore146 	 loss: 0.24,	 accuracy = 0.9026
[358] JSCore102 	 loss: 0.22,	 accuracy = 0.9238
[359] Train189 	 loss: 0.34,	 accuracy = 0.8645
[360] JSCore106 	 loss: 0.22,	 accuracy = 0.9222
[361] JSCore150 	 loss: 0.24,	 accuracy = 0.9141
[362] Train192 	 loss: 0.25,	 accuracy = 0.9105
[363] JSCore195 	 loss: 0.25,	 accuracy = 0.9117
[364] JSCore122 	 loss: 0.19,	 accuracy = 0.9328
[365] Train171 	 loss: 0.27,	 accuracy = 0.9036
[366] JSCore103 	 loss: 0.26,	 accuracy = 0.8986
[367] JSCore123 	 loss: 0.22,	 accuracy = 0.9174
[368] JSCore176 	 loss: 0.21,	 accuracy = 0.9171
[369] JSCore116 	 loss: 0.23,	 accuracy = 0.9150
[370] Train179 	 loss: 0.22,	 accuracy = 0.9201
[371] Train195 	 loss: 0.26,	 accuracy = 0.9077
[372] JSCore176 	 loss: 0.19,	 accuracy = 0.9332
[373] JSCore143 	 loss: 0.22,	 accuracy = 0.9198
[374] JSCore175 	 loss: 0.24,	 accuracy = 0.8993
[375] Train162 	 loss: 0.29,	 accuracy = 0.8932
[375] dev set  	 loss: 0.20,	 accuracy = 0.9317
[375] test set 	 loss: 0.22,	 accuracy = 0.9200
[376] Train143 	 loss: 0.20,	 accuracy = 0.9308
[377] Train115 	 loss: 0.28,	 accuracy = 0.9311
[378] JSCore176 	 loss: 0.25,	 accuracy = 0.9024
[379] JSCore136 	 loss: 0.27,	 accuracy = 0.9071
[380] Train195 	 loss: 0.28,	 accuracy = 0.8928
[381] Train116 	 loss: 0.21,	 accuracy = 0.9283
[382] JSCore118 	 loss: 0.22,	 accuracy = 0.9094
[383] Train144 	 loss: 0.25,	 accuracy = 0.9053
[384] Train126 	 loss: 0.25,	 accuracy = 0.9139
[385] Train123 	 loss: 0.26,	 accuracy = 0.8966
[386] JSCore141 	 loss: 0.21,	 accuracy = 0.9217
[387] Train192 	 loss: 0.23,	 accuracy = 0.9195
[388] JSCore163 	 loss: 0.20,	 accuracy = 0.9246
[389] JSCore151 	 loss: 0.24,	 accuracy = 0.8916
[390] JSCore194 	 loss: 0.14,	 accuracy = 0.9503
[391] JSCore117 	 loss: 0.21,	 accuracy = 0.9188
[392] JSCore197 	 loss: 0.25,	 accuracy = 0.9012
[393] Train102 	 loss: 0.21,	 accuracy = 0.9177
[394] JSCore168 	 loss: 0.21,	 accuracy = 0.9177
[395] Train177 	 loss: 0.29,	 accuracy = 0.8907
[396] JSCore166 	 loss: 0.25,	 accuracy = 0.8915
[397] JSCore197 	 loss: 0.18,	 accuracy = 0.9333
[398] JSCore199 	 loss: 0.18,	 accuracy = 0.9367
[399] Train161 	 loss: 0.28,	 accuracy = 0.8974
[400] Train184 	 loss: 0.27,	 accuracy = 0.8956
[400] dev set  	 loss: 0.21,	 accuracy = 0.9200
[400] test set 	 loss: 0.22,	 accuracy = 0.9150
[401] Train198 	 loss: 0.27,	 accuracy = 0.8925
[402] JSCore186 	 loss: 0.26,	 accuracy = 0.8891
[403] JSCore150 	 loss: 0.30,	 accuracy = 0.8733
[404] JSCore172 	 loss: 0.21,	 accuracy = 0.9259
[405] JSCore143 	 loss: 0.24,	 accuracy = 0.8988
[406] Train127 	 loss: 0.22,	 accuracy = 0.9120
[407] Train129 	 loss: 0.28,	 accuracy = 0.8932
[408] JSCore182 	 loss: 0.24,	 accuracy = 0.9104
[409] JSCore103 	 loss: 0.18,	 accuracy = 0.9307
[410] JSCore189 	 loss: 0.20,	 accuracy = 0.9263
[411] Train163 	 loss: 0.24,	 accuracy = 0.9127
[412] JSCore106 	 loss: 0.24,	 accuracy = 0.9067
[413] Train125 	 loss: 0.32,	 accuracy = 0.8564
[414] Train112 	 loss: 0.24,	 accuracy = 0.9069
[415] Train152 	 loss: 0.30,	 accuracy = 0.8829
[416] JSCore115 	 loss: 0.18,	 accuracy = 0.9400
[417] JSCore146 	 loss: 0.23,	 accuracy = 0.9210
[418] JSCore152 	 loss: 0.24,	 accuracy = 0.9105
[419] Train169 	 loss: 0.19,	 accuracy = 0.9350
[420] Train150 	 loss: 0.31,	 accuracy = 0.8527
[421] JSCore186 	 loss: 0.22,	 accuracy = 0.9226
[422] Train104 	 loss: 0.21,	 accuracy = 0.9242
[423] Train196 	 loss: 0.23,	 accuracy = 0.9186
[424] JSCore151 	 loss: 0.21,	 accuracy = 0.9202
[425] Train192 	 loss: 0.23,	 accuracy = 0.9290
[425] dev set  	 loss: 0.20,	 accuracy = 0.9317
[425] test set 	 loss: 0.25,	 accuracy = 0.9133
[426] JSCore124 	 loss: 0.25,	 accuracy = 0.9029
[427] JSCore100 	 loss: 0.26,	 accuracy = 0.9028
[428] JSCore128 	 loss: 0.20,	 accuracy = 0.9304
[429] JSCore140 	 loss: 0.19,	 accuracy = 0.9280
[430] JSCore134 	 loss: 0.22,	 accuracy = 0.9128
[431] JSCore110 	 loss: 0.20,	 accuracy = 0.9097
[432] JSCore138 	 loss: 0.17,	 accuracy = 0.9374
[433] Train101 	 loss: 0.27,	 accuracy = 0.8890
[434] Train132 	 loss: 0.25,	 accuracy = 0.9003
[435] Train192 	 loss: 0.25,	 accuracy = 0.9054
[436] Train131 	 loss: 0.20,	 accuracy = 0.9377
[437] Train177 	 loss: 0.30,	 accuracy = 0.8697
[438] Train145 	 loss: 0.27,	 accuracy = 0.9032
[439] JSCore123 	 loss: 0.21,	 accuracy = 0.9267
[440] JSCore102 	 loss: 0.22,	 accuracy = 0.9096
[441] Train181 	 loss: 0.26,	 accuracy = 0.9215
[442] Train102 	 loss: 0.24,	 accuracy = 0.9082
[443] Train153 	 loss: 0.20,	 accuracy = 0.9254
[444] JSCore156 	 loss: 0.23,	 accuracy = 0.9084
[445] Train165 	 loss: 0.36,	 accuracy = 0.8493
[446] Train111 	 loss: 0.24,	 accuracy = 0.8977
[447] JSCore156 	 loss: 0.23,	 accuracy = 0.9065
[448] JSCore178 	 loss: 0.17,	 accuracy = 0.9349
[449] JSCore176 	 loss: 0.18,	 accuracy = 0.9327
[450] JSCore104 	 loss: 0.25,	 accuracy = 0.8974
[450] dev set  	 loss: 0.24,	 accuracy = 0.9083
[450] test set 	 loss: 0.24,	 accuracy = 0.9100
[451] JSCore179 	 loss: 0.23,	 accuracy = 0.9063
[452] Train179 	 loss: 0.27,	 accuracy = 0.8948
[453] Train185 	 loss: 0.31,	 accuracy = 0.8739
[454] JSCore106 	 loss: 0.25,	 accuracy = 0.8933
[455] JSCore137 	 loss: 0.24,	 accuracy = 0.8986
[456] Train159 	 loss: 0.23,	 accuracy = 0.9173
[457] JSCore134 	 loss: 0.19,	 accuracy = 0.9179
[458] Train157 	 loss: 0.22,	 accuracy = 0.9185
[459] Train154 	 loss: 0.22,	 accuracy = 0.9204
[460] JSCore168 	 loss: 0.23,	 accuracy = 0.9045
[461] JSCore194 	 loss: 0.22,	 accuracy = 0.9176
[462] Train164 	 loss: 0.27,	 accuracy = 0.9093
[463] JSCore107 	 loss: 0.22,	 accuracy = 0.9071
[464] Train105 	 loss: 0.23,	 accuracy = 0.9067
[465] JSCore163 	 loss: 0.22,	 accuracy = 0.9222
[466] Train173 	 loss: 0.23,	 accuracy = 0.9173
[467] Train135 	 loss: 0.27,	 accuracy = 0.9048
[468] JSCore190 	 loss: 0.23,	 accuracy = 0.9238
[469] JSCore155 	 loss: 0.25,	 accuracy = 0.8950
[470] JSCore169 	 loss: 0.22,	 accuracy = 0.9203
[471] JSCore146 	 loss: 0.17,	 accuracy = 0.9381
[472] JSCore148 	 loss: 0.20,	 accuracy = 0.9240
[473] Train199 	 loss: 0.23,	 accuracy = 0.9170
[474] JSCore161 	 loss: 0.26,	 accuracy = 0.8907
[475] JSCore133 	 loss: 0.17,	 accuracy = 0.9431
[475] dev set  	 loss: 0.20,	 accuracy = 0.9283
[475] test set 	 loss: 0.23,	 accuracy = 0.8967
[476] Train173 	 loss: 0.31,	 accuracy = 0.8743
[477] Train105 	 loss: 0.24,	 accuracy = 0.9090
[478] JSCore163 	 loss: 0.22,	 accuracy = 0.9222
[479] JSCore178 	 loss: 0.20,	 accuracy = 0.9202
[480] Train178 	 loss: 0.27,	 accuracy = 0.9001
[481] Train166 	 loss: 0.24,	 accuracy = 0.9192
[482] Train177 	 loss: 0.25,	 accuracy = 0.9058
[483] JSCore169 	 loss: 0.17,	 accuracy = 0.9313
[484] Train103 	 loss: 0.21,	 accuracy = 0.9259
[485] Train125 	 loss: 0.18,	 accuracy = 0.9491
[486] JSCore108 	 loss: 0.20,	 accuracy = 0.9260
[487] JSCore103 	 loss: 0.19,	 accuracy = 0.9215
[488] Train180 	 loss: 0.21,	 accuracy = 0.9271
[489] JSCore107 	 loss: 0.18,	 accuracy = 0.9413
[490] Train144 	 loss: 0.27,	 accuracy = 0.8961
[491] Train136 	 loss: 0.26,	 accuracy = 0.8916
[492] JSCore117 	 loss: 0.18,	 accuracy = 0.9306
[493] JSCore200 	 loss: 0.23,	 accuracy = 0.9208
[494] JSCore127 	 loss: 0.19,	 accuracy = 0.9397
[495] JSCore108 	 loss: 0.21,	 accuracy = 0.9238
[496] JSCore117 	 loss: 0.18,	 accuracy = 0.9359
[497] JSCore190 	 loss: 0.17,	 accuracy = 0.9363
[498] JSCore162 	 loss: 0.20,	 accuracy = 0.9279
[499] JSCore199 	 loss: 0.21,	 accuracy = 0.9184
[500] JSCore161 	 loss: 0.23,	 accuracy = 0.9172
[500] dev set  	 loss: 0.22,	 accuracy = 0.9100
[500] test set 	 loss: 0.25,	 accuracy = 0.8850
[501] Train130 	 loss: 0.31,	 accuracy = 0.8528
[502] Train194 	 loss: 0.31,	 accuracy = 0.8557
[503] Train132 	 loss: 0.24,	 accuracy = 0.9286
[504] JSCore119 	 loss: 0.21,	 accuracy = 0.9201
[505] JSCore103 	 loss: 0.16,	 accuracy = 0.9430
[506] Train189 	 loss: 0.23,	 accuracy = 0.9101
[507] Train172 	 loss: 0.28,	 accuracy = 0.8875
[508] Train197 	 loss: 0.25,	 accuracy = 0.8988
[509] JSCore167 	 loss: 0.18,	 accuracy = 0.9336
[510] JSCore100 	 loss: 0.16,	 accuracy = 0.9397
[511] Train185 	 loss: 0.23,	 accuracy = 0.9222
[512] JSCore166 	 loss: 0.21,	 accuracy = 0.9366
[513] JSCore112 	 loss: 0.17,	 accuracy = 0.9368
[514] Train105 	 loss: 0.19,	 accuracy = 0.9336
[515] JSCore100 	 loss: 0.15,	 accuracy = 0.9474
[516] Train193 	 loss: 0.22,	 accuracy = 0.9232
[517] JSCore185 	 loss: 0.17,	 accuracy = 0.9305
[518] JSCore101 	 loss: 0.21,	 accuracy = 0.9187
[519] Train134 	 loss: 0.20,	 accuracy = 0.9216
[520] Train177 	 loss: 0.22,	 accuracy = 0.9195
[521] JSCore163 	 loss: 0.21,	 accuracy = 0.9247
[522] JSCore125 	 loss: 0.17,	 accuracy = 0.9530

training took 1h20m