/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/bin/java "-javaagent:/Applications/IntelliJ IDEA.app/Contents/lib/idea_rt.jar=55827:/Applications/IntelliJ IDEA.app/Contents/bin" -Dfile.encoding=UTF-8 -classpath /Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/charsets.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/deploy.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/cldrdata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/dnsns.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/jaccess.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/jfxrt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/localedata.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/nashorn.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/sunec.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/sunjce_provider.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/sunpkcs11.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/ext/zipfs.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/javaws.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/jce.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/jfr.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/jfxswt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/jsse.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/management-agent.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/plugin.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/resources.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/rt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/ant-javafx.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/dt.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/javafx-mx.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/jconsole.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/packager.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/sa-jdi.jar:/Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/lib/tools.jar:/Users/weijiayi/Programming/ATP/target/scala-2.12/classes:/Users/weijiayi/.ivy2/cache/be.botkop/numsca_2.12/jars/numsca_2.12-0.1.3.jar:/Users/weijiayi/.ivy2/cache/ch.qos.logback/logback-classic/jars/logback-classic-1.2.3.jar:/Users/weijiayi/.ivy2/cache/ch.qos.logback/logback-core/jars/logback-core-1.2.3.jar:/Users/weijiayi/.ivy2/cache/com.github.stephenc.findbugs/findbugs-annotations/jars/findbugs-annotations-1.3.9-1.jar:/Applications/activator-dist-1.3.10/repository/com.google.guava/guava/18.0/bundles/guava.jar:/Users/weijiayi/.ivy2/cache/com.lihaoyi/ammonite-ops_2.12/jars/ammonite-ops_2.12-1.0.3.jar:/Users/weijiayi/.ivy2/cache/com.lihaoyi/fastparse_2.12/jars/fastparse_2.12-2.0.4.jar:/Users/weijiayi/.ivy2/cache/com.lihaoyi/geny_2.12/jars/geny_2.12-0.1.2.jar:/Users/weijiayi/.ivy2/cache/com.lihaoyi/sourcecode_2.12/bundles/sourcecode_2.12-0.1.4.jar:/Users/weijiayi/.ivy2/cache/com.typesafe/config/bundles/config-1.3.2.jar:/Users/weijiayi/.ivy2/cache/com.typesafe.akka/akka-actor_2.12/jars/akka-actor_2.12-2.5.12.jar:/Users/weijiayi/.ivy2/cache/com.typesafe.scala-logging/scala-logging_2.12/bundles/scala-logging_2.12-3.7.2.jar:/Users/weijiayi/.ivy2/cache/commons-io/commons-io/jars/commons-io-2.4.jar:/Users/weijiayi/.ivy2/cache/joda-time/joda-time/jars/joda-time-2.2.jar:/Users/weijiayi/.ivy2/cache/junit/junit/jars/junit-4.8.2.jar:/Users/weijiayi/.ivy2/cache/net.ericaro/neoitertools/jars/neoitertools-1.0.0.jar:/Users/weijiayi/.ivy2/cache/org.apache.commons/commons-lang3/jars/commons-lang3-3.3.1.jar:/Users/weijiayi/.ivy2/cache/org.apache.commons/commons-math3/jars/commons-math3-3.4.1.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco/javacpp/jars/javacpp-1.3.3.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-android-arm.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-android-x86.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-linux-armhf.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-linux-ppc64le.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-linux-x86.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-linux-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-macosx-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-windows-x86.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas/jars/openblas-0.2.19-1.3-windows-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.bytedeco.javacpp-presets/openblas-platform/jars/openblas-platform-0.2.19-1.3.jar:/Users/weijiayi/.ivy2/cache/org.codehaus.woodstox/stax2-api/bundles/stax2-api-3.1.4.jar:/Users/weijiayi/.ivy2/cache/org.javassist/javassist/bundles/javassist-3.18.2-GA.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/jackson/jars/jackson-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-api/jars/nd4j-api-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-buffer/jars/nd4j-buffer-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-common/jars/nd4j-common-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-context/jars/nd4j-context-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-android-arm.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-android-x86.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-linux-ppc64le.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-linux-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-macosx-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native/jars/nd4j-native-0.9.1-windows-x86_64.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native-api/jars/nd4j-native-api-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.nd4j/nd4j-native-platform/jars/nd4j-native-platform-0.9.1.jar:/Users/weijiayi/.ivy2/cache/org.projectlombok/lombok/jars/lombok-1.16.16.jar:/Users/weijiayi/.ivy2/cache/org.reflections/reflections/jars/reflections-0.9.10.jar:/Users/weijiayi/.ivy2/cache/org.scala-lang/scala-library/jars/scala-library-2.12.7.jar:/Users/weijiayi/.ivy2/cache/org.scala-lang/scala-reflect/jars/scala-reflect-2.12.7.jar:/Users/weijiayi/.ivy2/cache/org.scala-lang.modules/scala-java8-compat_2.12/bundles/scala-java8-compat_2.12-0.8.0.jar:/Users/weijiayi/.ivy2/cache/org.scala-sbt/test-interface/jars/test-interface-1.0.jar:/Users/weijiayi/.ivy2/cache/org.scalacheck/scalacheck_2.12/jars/scalacheck_2.12-1.14.0.jar:/Users/weijiayi/.ivy2/cache/org.slf4j/slf4j-api/jars/slf4j-api-1.7.25.jar:/Users/weijiayi/.ivy2/cache/org.yaml/snakeyaml/bundles/snakeyaml-1.12.jar gtype.TypeEncoder
objc[13151]: Class JavaLaunchHelper is implemented in both /Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/bin/java (0x105d694c0) and /Library/Java/JavaVirtualMachines/jdk1.8.0_121.jdk/Contents/Home/jre/lib/libinstrument.dylib (0x105de34e0). One of the two will be used. Which one is undefined.
Encoder params: EncoderParams(80,80,80,Attention,Separate,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: 244
pos relations: 1248, neg relations: 58044, reflexivity: 244
test set graph size: 276
pos relations: 1229, neg relations: 74671, reflexivity: 276
[0] Train129 	 loss: 0.69,	 accuracy = 0.4516
[1] Train197 	 loss: 0.69,	 accuracy = 0.5078
[2] JSCore175 	 loss: 0.69,	 accuracy = 0.5069
[3] Train107 	 loss: 0.69,	 accuracy = 0.5000
[4] Train112 	 loss: 0.69,	 accuracy = 0.5000
[5] JSCore188 	 loss: 0.69,	 accuracy = 0.5000
[6] JSCore101 	 loss: 0.69,	 accuracy = 0.5000
[7] Train126 	 loss: 0.69,	 accuracy = 0.5000
[8] JSCore124 	 loss: 0.69,	 accuracy = 0.5000
[9] Train190 	 loss: 0.69,	 accuracy = 0.5000
[10] Train103 	 loss: 0.69,	 accuracy = 0.5000
[11] JSCore179 	 loss: 0.69,	 accuracy = 0.5000
[12] Train197 	 loss: 0.69,	 accuracy = 0.5000
[13] Train194 	 loss: 0.68,	 accuracy = 0.5000
[14] JSCore174 	 loss: 0.67,	 accuracy = 0.5000
[15] JSCore186 	 loss: 0.66,	 accuracy = 0.4997
[16] Train184 	 loss: 0.64,	 accuracy = 0.5159
[17] Train130 	 loss: 0.63,	 accuracy = 0.6662
[18] Train128 	 loss: 0.67,	 accuracy = 0.6232
[19] JSCore182 	 loss: 0.63,	 accuracy = 0.6854
[20] JSCore145 	 loss: 0.63,	 accuracy = 0.6975
[21] Train200 	 loss: 0.63,	 accuracy = 0.7337
[22] Train188 	 loss: 0.62,	 accuracy = 0.7319
[23] JSCore186 	 loss: 0.60,	 accuracy = 0.7169
[24] Train126 	 loss: 0.65,	 accuracy = 0.7384
[25] JSCore141 	 loss: 0.59,	 accuracy = 0.7258
[25] dev set  	 loss: 0.60,	 accuracy = 0.7300
[25] test set 	 loss: 0.60,	 accuracy = 0.7367
[26] JSCore142 	 loss: 0.60,	 accuracy = 0.7223
[27] JSCore152 	 loss: 0.60,	 accuracy = 0.7276
[28] Train173 	 loss: 0.59,	 accuracy = 0.7322
[29] Train174 	 loss: 0.59,	 accuracy = 0.7212
[30] Train190 	 loss: 0.58,	 accuracy = 0.7262
[31] JSCore195 	 loss: 0.61,	 accuracy = 0.7316
[32] Train190 	 loss: 0.56,	 accuracy = 0.7382
[33] JSCore160 	 loss: 0.60,	 accuracy = 0.7281
[34] JSCore129 	 loss: 0.57,	 accuracy = 0.7549
[35] Train185 	 loss: 0.57,	 accuracy = 0.7103
[36] Train155 	 loss: 0.54,	 accuracy = 0.7271
[37] JSCore138 	 loss: 0.56,	 accuracy = 0.7503
[38] Train106 	 loss: 0.56,	 accuracy = 0.7242
[39] Train119 	 loss: 0.50,	 accuracy = 0.7605
[40] JSCore121 	 loss: 0.55,	 accuracy = 0.7450
[41] Train169 	 loss: 0.51,	 accuracy = 0.7196
[42] Train128 	 loss: 0.47,	 accuracy = 0.7297
[43] Train199 	 loss: 0.52,	 accuracy = 0.7218
[44] JSCore192 	 loss: 0.50,	 accuracy = 0.7373
[45] Train162 	 loss: 0.53,	 accuracy = 0.7224
[46] JSCore192 	 loss: 0.51,	 accuracy = 0.7328
[47] Train188 	 loss: 0.49,	 accuracy = 0.7521
[48] Train173 	 loss: 0.49,	 accuracy = 0.7335
[49] Train143 	 loss: 0.50,	 accuracy = 0.7529
[50] Train116 	 loss: 0.49,	 accuracy = 0.7088
[50] dev set  	 loss: 0.49,	 accuracy = 0.7567
[50] test set 	 loss: 0.46,	 accuracy = 0.7583
[51] Train105 	 loss: 0.46,	 accuracy = 0.7163
[52] JSCore126 	 loss: 0.47,	 accuracy = 0.7713
[53] Train125 	 loss: 0.45,	 accuracy = 0.7453
[54] Train156 	 loss: 0.48,	 accuracy = 0.7221
[55] JSCore164 	 loss: 0.47,	 accuracy = 0.7691
[56] JSCore119 	 loss: 0.47,	 accuracy = 0.7754
[57] JSCore126 	 loss: 0.46,	 accuracy = 0.7641
[58] Train159 	 loss: 0.50,	 accuracy = 0.7208
[59] Train118 	 loss: 0.44,	 accuracy = 0.7456
[60] JSCore138 	 loss: 0.48,	 accuracy = 0.7923
[61] Train172 	 loss: 0.49,	 accuracy = 0.7474
[62] JSCore106 	 loss: 0.43,	 accuracy = 0.7516
[63] Train192 	 loss: 0.43,	 accuracy = 0.7287
[64] JSCore146 	 loss: 0.45,	 accuracy = 0.7592
[65] JSCore187 	 loss: 0.45,	 accuracy = 0.7481
[66] Train182 	 loss: 0.45,	 accuracy = 0.7543
[67] Train153 	 loss: 0.42,	 accuracy = 0.7500
[68] JSCore199 	 loss: 0.51,	 accuracy = 0.7321
[69] Train158 	 loss: 0.42,	 accuracy = 0.7695
[70] JSCore118 	 loss: 0.44,	 accuracy = 0.7575
[71] Train184 	 loss: 0.42,	 accuracy = 0.7713
[72] JSCore193 	 loss: 0.43,	 accuracy = 0.7934
[73] JSCore147 	 loss: 0.40,	 accuracy = 0.8245
[74] JSCore129 	 loss: 0.44,	 accuracy = 0.7950
[75] JSCore103 	 loss: 0.43,	 accuracy = 0.7929
[75] dev set  	 loss: 0.40,	 accuracy = 0.8283
[75] test set 	 loss: 0.39,	 accuracy = 0.8333
[76] Train115 	 loss: 0.43,	 accuracy = 0.8188
[77] Train145 	 loss: 0.40,	 accuracy = 0.8259
[78] JSCore148 	 loss: 0.39,	 accuracy = 0.7462
[79] Train181 	 loss: 0.41,	 accuracy = 0.7961
[80] Train144 	 loss: 0.40,	 accuracy = 0.8297
[81] JSCore190 	 loss: 0.43,	 accuracy = 0.8046
[82] Train153 	 loss: 0.39,	 accuracy = 0.8339
[83] Train181 	 loss: 0.38,	 accuracy = 0.8341
[84] Train123 	 loss: 0.33,	 accuracy = 0.8899
[85] Train195 	 loss: 0.46,	 accuracy = 0.7033
[86] JSCore100 	 loss: 0.39,	 accuracy = 0.8305
[87] Train179 	 loss: 0.40,	 accuracy = 0.8243
[88] Train102 	 loss: 0.42,	 accuracy = 0.8084
[89] JSCore128 	 loss: 0.37,	 accuracy = 0.8614
[90] JSCore115 	 loss: 0.36,	 accuracy = 0.8744
[91] Train175 	 loss: 0.39,	 accuracy = 0.8309
[92] JSCore154 	 loss: 0.37,	 accuracy = 0.8089
[93] JSCore154 	 loss: 0.45,	 accuracy = 0.7333
[94] JSCore197 	 loss: 0.38,	 accuracy = 0.8442
[95] JSCore145 	 loss: 0.34,	 accuracy = 0.8844
[96] JSCore189 	 loss: 0.37,	 accuracy = 0.8400
[97] JSCore144 	 loss: 0.33,	 accuracy = 0.8729
[98] Train161 	 loss: 0.38,	 accuracy = 0.8400
[99] Train195 	 loss: 0.37,	 accuracy = 0.8455
[100] JSCore186 	 loss: 0.36,	 accuracy = 0.8446
[100] dev set  	 loss: 0.36,	 accuracy = 0.8517
[100] test set 	 loss: 0.33,	 accuracy = 0.8783
[101] JSCore149 	 loss: 0.38,	 accuracy = 0.8330
[102] JSCore165 	 loss: 0.35,	 accuracy = 0.8531
[103] Train169 	 loss: 0.32,	 accuracy = 0.8746
[104] JSCore140 	 loss: 0.40,	 accuracy = 0.8479
[105] JSCore190 	 loss: 0.35,	 accuracy = 0.8616
[106] Train162 	 loss: 0.39,	 accuracy = 0.8597
[107] Train132 	 loss: 0.33,	 accuracy = 0.8708
[108] Train144 	 loss: 0.32,	 accuracy = 0.8845
[109] Train176 	 loss: 0.33,	 accuracy = 0.8614
[110] Train113 	 loss: 0.33,	 accuracy = 0.8612
[111] Train164 	 loss: 0.35,	 accuracy = 0.8473
[112] Train106 	 loss: 0.35,	 accuracy = 0.8672
[113] JSCore118 	 loss: 0.35,	 accuracy = 0.8718
[114] Train109 	 loss: 0.37,	 accuracy = 0.8779
[115] Train124 	 loss: 0.36,	 accuracy = 0.8707
[116] Train106 	 loss: 0.38,	 accuracy = 0.8426
[117] JSCore129 	 loss: 0.38,	 accuracy = 0.8718
[118] JSCore136 	 loss: 0.31,	 accuracy = 0.8788
[119] Train107 	 loss: 0.35,	 accuracy = 0.8682
[120] JSCore170 	 loss: 0.33,	 accuracy = 0.8771
[121] Train135 	 loss: 0.33,	 accuracy = 0.8829
[122] Train193 	 loss: 0.32,	 accuracy = 0.8874
[123] Train150 	 loss: 0.32,	 accuracy = 0.8835
[124] JSCore111 	 loss: 0.33,	 accuracy = 0.8526
[125] Train124 	 loss: 0.32,	 accuracy = 0.8770
[125] dev set  	 loss: 0.39,	 accuracy = 0.8567
[125] test set 	 loss: 0.33,	 accuracy = 0.8833
[126] Train142 	 loss: 0.31,	 accuracy = 0.8789
[127] JSCore164 	 loss: 0.50,	 accuracy = 0.8418
[128] Train145 	 loss: 0.35,	 accuracy = 0.8690
[129] JSCore105 	 loss: 0.36,	 accuracy = 0.8660
[130] Train172 	 loss: 0.32,	 accuracy = 0.8916
[131] Train147 	 loss: 0.31,	 accuracy = 0.8996
[132] Train139 	 loss: 0.33,	 accuracy = 0.8916
[133] Train168 	 loss: 0.37,	 accuracy = 0.8737
[134] Train127 	 loss: 0.35,	 accuracy = 0.8591
[135] Train123 	 loss: 0.30,	 accuracy = 0.8961
[136] Train110 	 loss: 0.34,	 accuracy = 0.8737
[137] Train137 	 loss: 0.37,	 accuracy = 0.8130
[138] JSCore119 	 loss: 0.37,	 accuracy = 0.8231
[139] Train199 	 loss: 0.37,	 accuracy = 0.8265
[140] JSCore169 	 loss: 0.32,	 accuracy = 0.8634
[141] Train120 	 loss: 0.34,	 accuracy = 0.8575
[142] Train167 	 loss: 0.33,	 accuracy = 0.8714
[143] JSCore146 	 loss: 0.33,	 accuracy = 0.8759
[144] Train164 	 loss: 0.33,	 accuracy = 0.8861
[145] Train138 	 loss: 0.34,	 accuracy = 0.8681
[146] Train158 	 loss: 0.31,	 accuracy = 0.8930
[147] JSCore141 	 loss: 0.28,	 accuracy = 0.9097
[148] Train106 	 loss: 0.30,	 accuracy = 0.8937
[149] JSCore138 	 loss: 0.34,	 accuracy = 0.8561
[150] Train111 	 loss: 0.32,	 accuracy = 0.8702
[150] dev set  	 loss: 0.30,	 accuracy = 0.8783
[150] test set 	 loss: 0.27,	 accuracy = 0.8867
[151] Train102 	 loss: 0.39,	 accuracy = 0.8512
[152] JSCore156 	 loss: 0.32,	 accuracy = 0.8859
[153] Train151 	 loss: 0.36,	 accuracy = 0.8491
[154] JSCore158 	 loss: 0.33,	 accuracy = 0.8793
[155] JSCore119 	 loss: 0.33,	 accuracy = 0.8629
[156] Train143 	 loss: 0.33,	 accuracy = 0.9025
[157] JSCore127 	 loss: 0.28,	 accuracy = 0.8895
[158] JSCore114 	 loss: 0.28,	 accuracy = 0.8999
[159] JSCore112 	 loss: 0.30,	 accuracy = 0.8952
[160] Train123 	 loss: 0.28,	 accuracy = 0.8937
[161] Train104 	 loss: 0.34,	 accuracy = 0.8618
[162] Train101 	 loss: 0.25,	 accuracy = 0.9202
[163] Train188 	 loss: 0.30,	 accuracy = 0.8812
[164] JSCore116 	 loss: 0.34,	 accuracy = 0.8671
[165] Train114 	 loss: 0.27,	 accuracy = 0.9016
[166] JSCore126 	 loss: 0.28,	 accuracy = 0.8970
[167] Train102 	 loss: 0.30,	 accuracy = 0.8911
[168] Train164 	 loss: 0.28,	 accuracy = 0.8997
[169] Train156 	 loss: 0.30,	 accuracy = 0.8836
[170] Train190 	 loss: 0.31,	 accuracy = 0.8970
[171] Train168 	 loss: 0.29,	 accuracy = 0.8875
[172] JSCore158 	 loss: 0.26,	 accuracy = 0.9041
[173] Train145 	 loss: 0.26,	 accuracy = 0.9093
[174] JSCore176 	 loss: 0.30,	 accuracy = 0.8721
[175] Train160 	 loss: 0.29,	 accuracy = 0.8984
[175] dev set  	 loss: 0.28,	 accuracy = 0.8933
[175] test set 	 loss: 0.27,	 accuracy = 0.9000
[176] Train112 	 loss: 0.29,	 accuracy = 0.8865
[177] JSCore134 	 loss: 0.26,	 accuracy = 0.8966
[178] JSCore175 	 loss: 0.28,	 accuracy = 0.8881
[179] Train125 	 loss: 0.27,	 accuracy = 0.8987
[180] Train127 	 loss: 0.27,	 accuracy = 0.8921
[181] Train147 	 loss: 0.27,	 accuracy = 0.8994
[182] Train144 	 loss: 0.27,	 accuracy = 0.9009
[183] Train103 	 loss: 0.27,	 accuracy = 0.9011
[184] JSCore166 	 loss: 0.35,	 accuracy = 0.8553
[185] Train123 	 loss: 0.29,	 accuracy = 0.8912
[186] JSCore180 	 loss: 0.29,	 accuracy = 0.8799
[187] Train136 	 loss: 0.32,	 accuracy = 0.8740
[188] Train180 	 loss: 0.31,	 accuracy = 0.8898
[189] JSCore134 	 loss: 0.28,	 accuracy = 0.9066
[190] JSCore138 	 loss: 0.31,	 accuracy = 0.8808
[191] Train131 	 loss: 0.30,	 accuracy = 0.8952
[192] JSCore108 	 loss: 0.26,	 accuracy = 0.9165
[193] Train156 	 loss: 0.32,	 accuracy = 0.8812
[194] JSCore152 	 loss: 0.28,	 accuracy = 0.9034
[195] JSCore182 	 loss: 0.26,	 accuracy = 0.9107
[196] JSCore147 	 loss: 0.27,	 accuracy = 0.9007
[197] JSCore139 	 loss: 0.28,	 accuracy = 0.8867
[198] Train112 	 loss: 0.26,	 accuracy = 0.9027
[199] Train119 	 loss: 0.25,	 accuracy = 0.9130
[200] JSCore157 	 loss: 0.27,	 accuracy = 0.8979
[200] dev set  	 loss: 0.29,	 accuracy = 0.8867
[200] test set 	 loss: 0.24,	 accuracy = 0.9117
[201] JSCore187 	 loss: 0.29,	 accuracy = 0.8917
[202] Train104 	 loss: 0.27,	 accuracy = 0.8888
[203] JSCore156 	 loss: 0.24,	 accuracy = 0.8904
[204] JSCore170 	 loss: 0.25,	 accuracy = 0.9020
[205] Train191 	 loss: 0.27,	 accuracy = 0.8977
[206] JSCore125 	 loss: 0.28,	 accuracy = 0.8810
[207] JSCore139 	 loss: 0.33,	 accuracy = 0.8515
[208] Train165 	 loss: 0.28,	 accuracy = 0.9014
[209] JSCore165 	 loss: 0.27,	 accuracy = 0.8991
[210] Train164 	 loss: 0.31,	 accuracy = 0.8539
[211] Train131 	 loss: 0.31,	 accuracy = 0.8514
[212] JSCore153 	 loss: 0.24,	 accuracy = 0.9058
[213] Train165 	 loss: 0.28,	 accuracy = 0.9025
[214] JSCore138 	 loss: 0.23,	 accuracy = 0.9114
[215] Train131 	 loss: 0.33,	 accuracy = 0.8685
[216] JSCore185 	 loss: 0.29,	 accuracy = 0.8785
[217] Train119 	 loss: 0.28,	 accuracy = 0.8868
[218] JSCore126 	 loss: 0.28,	 accuracy = 0.8789
[219] Train119 	 loss: 0.29,	 accuracy = 0.8920
[220] Train191 	 loss: 0.32,	 accuracy = 0.8759
[221] Train100 	 loss: 0.26,	 accuracy = 0.9123
[222] JSCore165 	 loss: 0.26,	 accuracy = 0.9117
[223] JSCore196 	 loss: 0.27,	 accuracy = 0.9059
[224] JSCore165 	 loss: 0.25,	 accuracy = 0.9038
[225] Train101 	 loss: 0.21,	 accuracy = 0.9326
[225] dev set  	 loss: 0.28,	 accuracy = 0.8950
[225] test set 	 loss: 0.22,	 accuracy = 0.9167
[226] JSCore105 	 loss: 0.21,	 accuracy = 0.9264
[227] JSCore147 	 loss: 0.27,	 accuracy = 0.8863
[228] Train122 	 loss: 0.24,	 accuracy = 0.9170
[229] JSCore158 	 loss: 0.28,	 accuracy = 0.8938
[230] Train200 	 loss: 0.26,	 accuracy = 0.9037
[231] Train131 	 loss: 0.27,	 accuracy = 0.9034
[232] Train167 	 loss: 0.24,	 accuracy = 0.9167
[233] JSCore151 	 loss: 0.23,	 accuracy = 0.9172
[234] JSCore154 	 loss: 0.25,	 accuracy = 0.9015
[235] JSCore123 	 loss: 0.28,	 accuracy = 0.8900
[236] JSCore166 	 loss: 0.25,	 accuracy = 0.8996
[237] Train133 	 loss: 0.25,	 accuracy = 0.9055
[238] Train181 	 loss: 0.25,	 accuracy = 0.9070
[239] JSCore143 	 loss: 0.24,	 accuracy = 0.9066
[240] Train189 	 loss: 0.23,	 accuracy = 0.9205
[241] JSCore103 	 loss: 0.24,	 accuracy = 0.9097
[242] Train197 	 loss: 0.21,	 accuracy = 0.9246
[243] JSCore196 	 loss: 0.22,	 accuracy = 0.9151
[244] JSCore100 	 loss: 0.24,	 accuracy = 0.9011
[245] JSCore141 	 loss: 0.21,	 accuracy = 0.9227
[246] Train192 	 loss: 0.29,	 accuracy = 0.8815
[247] JSCore161 	 loss: 0.22,	 accuracy = 0.9105
[248] Train156 	 loss: 0.28,	 accuracy = 0.9040
[249] JSCore192 	 loss: 0.31,	 accuracy = 0.8666
[250] JSCore104 	 loss: 0.26,	 accuracy = 0.8887
[250] dev set  	 loss: 0.24,	 accuracy = 0.8933
[250] test set 	 loss: 0.23,	 accuracy = 0.9083
[251] Train101 	 loss: 0.22,	 accuracy = 0.9084
[252] Train148 	 loss: 0.31,	 accuracy = 0.8762
[253] JSCore155 	 loss: 0.33,	 accuracy = 0.8447
[254] JSCore128 	 loss: 0.22,	 accuracy = 0.9151
[255] Train173 	 loss: 0.26,	 accuracy = 0.8932
[256] JSCore112 	 loss: 0.24,	 accuracy = 0.8867
[257] Train181 	 loss: 0.27,	 accuracy = 0.9163
[258] JSCore146 	 loss: 0.23,	 accuracy = 0.9195
[259] Train166 	 loss: 0.25,	 accuracy = 0.9204
[260] Train146 	 loss: 0.26,	 accuracy = 0.9003
[261] Train150 	 loss: 0.27,	 accuracy = 0.9045
[262] Train135 	 loss: 0.26,	 accuracy = 0.8969
[263] Train162 	 loss: 0.25,	 accuracy = 0.9067
[264] Train185 	 loss: 0.24,	 accuracy = 0.9039
[265] JSCore193 	 loss: 0.26,	 accuracy = 0.8970
[266] JSCore193 	 loss: 0.26,	 accuracy = 0.8986
[267] Train158 	 loss: 0.24,	 accuracy = 0.9245
[268] Train146 	 loss: 0.20,	 accuracy = 0.9397
[269] Train164 	 loss: 0.31,	 accuracy = 0.8844
[270] JSCore149 	 loss: 0.23,	 accuracy = 0.9107
[271] Train145 	 loss: 0.28,	 accuracy = 0.9000
[272] JSCore161 	 loss: 0.21,	 accuracy = 0.9179
[273] Train191 	 loss: 0.25,	 accuracy = 0.9040
[274] Train171 	 loss: 0.21,	 accuracy = 0.9273
[275] JSCore121 	 loss: 0.23,	 accuracy = 0.9084
[275] dev set  	 loss: 0.23,	 accuracy = 0.9033
[275] test set 	 loss: 0.18,	 accuracy = 0.9317
[276] JSCore150 	 loss: 0.27,	 accuracy = 0.9038
[277] Train126 	 loss: 0.24,	 accuracy = 0.9117
[278] JSCore155 	 loss: 0.24,	 accuracy = 0.9087
[279] JSCore118 	 loss: 0.19,	 accuracy = 0.9324
[280] Train103 	 loss: 0.21,	 accuracy = 0.9201
[281] JSCore158 	 loss: 0.21,	 accuracy = 0.9173
[282] JSCore170 	 loss: 0.25,	 accuracy = 0.8935
[283] Train146 	 loss: 0.29,	 accuracy = 0.9001
[284] JSCore117 	 loss: 0.21,	 accuracy = 0.9277
[285] JSCore197 	 loss: 0.20,	 accuracy = 0.9286
[286] Train167 	 loss: 0.21,	 accuracy = 0.9316
[287] Train162 	 loss: 0.26,	 accuracy = 0.9085
[288] JSCore157 	 loss: 0.21,	 accuracy = 0.9241
[289] Train189 	 loss: 0.20,	 accuracy = 0.9208
[290] Train122 	 loss: 0.25,	 accuracy = 0.9072
[291] Train188 	 loss: 0.22,	 accuracy = 0.9289
[292] JSCore102 	 loss: 0.14,	 accuracy = 0.9525
[293] Train102 	 loss: 0.20,	 accuracy = 0.9422
[294] JSCore175 	 loss: 0.19,	 accuracy = 0.9293
[295] Train132 	 loss: 0.23,	 accuracy = 0.9181
[296] JSCore105 	 loss: 0.19,	 accuracy = 0.9371
[297] Train159 	 loss: 0.22,	 accuracy = 0.9158
[298] JSCore187 	 loss: 0.20,	 accuracy = 0.9260
[299] JSCore165 	 loss: 0.20,	 accuracy = 0.9270
[300] Train153 	 loss: 0.26,	 accuracy = 0.8973
[300] dev set  	 loss: 0.22,	 accuracy = 0.9200
[300] test set 	 loss: 0.17,	 accuracy = 0.9517
[301] JSCore187 	 loss: 0.20,	 accuracy = 0.9244
[302] JSCore174 	 loss: 0.17,	 accuracy = 0.9399
[303] Train165 	 loss: 0.26,	 accuracy = 0.9025
[304] JSCore128 	 loss: 0.21,	 accuracy = 0.9161
[305] Train112 	 loss: 0.28,	 accuracy = 0.8899
[306] JSCore189 	 loss: 0.22,	 accuracy = 0.9212
[307] JSCore128 	 loss: 0.17,	 accuracy = 0.9427
[308] JSCore108 	 loss: 0.17,	 accuracy = 0.9466
[309] JSCore132 	 loss: 0.16,	 accuracy = 0.9456
[310] JSCore114 	 loss: 0.17,	 accuracy = 0.9372
[311] JSCore144 	 loss: 0.21,	 accuracy = 0.9206
[312] Train159 	 loss: 0.26,	 accuracy = 0.9085
[313] Train173 	 loss: 0.24,	 accuracy = 0.9131
[314] JSCore188 	 loss: 0.25,	 accuracy = 0.9035
[315] JSCore199 	 loss: 0.21,	 accuracy = 0.9211
[316] Train115 	 loss: 0.25,	 accuracy = 0.9023
[317] Train182 	 loss: 0.24,	 accuracy = 0.9126
[318] Train168 	 loss: 0.20,	 accuracy = 0.9298
[319] JSCore198 	 loss: 0.24,	 accuracy = 0.9126
[320] JSCore125 	 loss: 0.15,	 accuracy = 0.9488
[321] JSCore133 	 loss: 0.18,	 accuracy = 0.9331
[322] Train114 	 loss: 0.25,	 accuracy = 0.9076
[323] Train122 	 loss: 0.21,	 accuracy = 0.9238
[324] JSCore165 	 loss: 0.20,	 accuracy = 0.9288
[325] Train126 	 loss: 0.24,	 accuracy = 0.9180
[325] dev set  	 loss: 0.21,	 accuracy = 0.9217
[325] test set 	 loss: 0.15,	 accuracy = 0.9600
[326] Train168 	 loss: 0.25,	 accuracy = 0.9138
[327] JSCore167 	 loss: 0.20,	 accuracy = 0.9277
[328] JSCore104 	 loss: 0.20,	 accuracy = 0.9215
[329] JSCore123 	 loss: 0.19,	 accuracy = 0.9321
[330] JSCore167 	 loss: 0.19,	 accuracy = 0.9330
[331] JSCore167 	 loss: 0.20,	 accuracy = 0.9173
[332] Train125 	 loss: 0.25,	 accuracy = 0.9152
[333] JSCore109 	 loss: 0.20,	 accuracy = 0.9331
[334] JSCore182 	 loss: 0.20,	 accuracy = 0.9315
[335] Train184 	 loss: 0.20,	 accuracy = 0.9392
[336] JSCore144 	 loss: 0.18,	 accuracy = 0.9394
[337] JSCore137 	 loss: 0.22,	 accuracy = 0.9187
[338] Train104 	 loss: 0.20,	 accuracy = 0.9327
[339] JSCore182 	 loss: 0.17,	 accuracy = 0.9467
[340] Train103 	 loss: 0.29,	 accuracy = 0.8891
[341] Train121 	 loss: 0.22,	 accuracy = 0.9271
[342] JSCore120 	 loss: 0.18,	 accuracy = 0.9243
[343] Train156 	 loss: 0.21,	 accuracy = 0.9217
[344] Train104 	 loss: 0.24,	 accuracy = 0.9203
[345] Train138 	 loss: 0.22,	 accuracy = 0.9247
[346] Train109 	 loss: 0.23,	 accuracy = 0.9161
[347] JSCore148 	 loss: 0.18,	 accuracy = 0.9366
[348] JSCore143 	 loss: 0.17,	 accuracy = 0.9439
[349] JSCore180 	 loss: 0.21,	 accuracy = 0.9231
[350] Train141 	 loss: 0.23,	 accuracy = 0.9124
[350] dev set  	 loss: 0.20,	 accuracy = 0.9233
[350] test set 	 loss: 0.16,	 accuracy = 0.9550
[351] JSCore132 	 loss: 0.18,	 accuracy = 0.9288
[352] JSCore155 	 loss: 0.17,	 accuracy = 0.9427
[353] Train116 	 loss: 0.21,	 accuracy = 0.9175
[354] Train155 	 loss: 0.21,	 accuracy = 0.9218
[355] Train129 	 loss: 0.19,	 accuracy = 0.9304
[356] JSCore197 	 loss: 0.21,	 accuracy = 0.9148
[357] JSCore150 	 loss: 0.20,	 accuracy = 0.9338
[358] Train194 	 loss: 0.23,	 accuracy = 0.9264
[359] Train122 	 loss: 0.20,	 accuracy = 0.9281
[360] JSCore124 	 loss: 0.17,	 accuracy = 0.9387
[361] Train154 	 loss: 0.22,	 accuracy = 0.9296
[362] JSCore167 	 loss: 0.18,	 accuracy = 0.9315
[363] JSCore108 	 loss: 0.22,	 accuracy = 0.9208
[364] Train119 	 loss: 0.20,	 accuracy = 0.9382
[365] JSCore140 	 loss: 0.20,	 accuracy = 0.9254
[366] JSCore147 	 loss: 0.22,	 accuracy = 0.9105
[367] Train150 	 loss: 0.21,	 accuracy = 0.9226
[368] Train170 	 loss: 0.18,	 accuracy = 0.9375
[369] JSCore132 	 loss: 0.22,	 accuracy = 0.9127
[370] JSCore103 	 loss: 0.18,	 accuracy = 0.9335
[371] JSCore193 	 loss: 0.23,	 accuracy = 0.9120
[372] JSCore136 	 loss: 0.16,	 accuracy = 0.9343
[373] JSCore167 	 loss: 0.20,	 accuracy = 0.9343
[374] Train169 	 loss: 0.25,	 accuracy = 0.9046
[375] Train163 	 loss: 0.23,	 accuracy = 0.9198
[375] dev set  	 loss: 0.19,	 accuracy = 0.9283
[375] test set 	 loss: 0.15,	 accuracy = 0.9533
[376] JSCore148 	 loss: 0.16,	 accuracy = 0.9446
[377] JSCore123 	 loss: 0.19,	 accuracy = 0.9291
[378] JSCore141 	 loss: 0.15,	 accuracy = 0.9458
[379] JSCore143 	 loss: 0.14,	 accuracy = 0.9525
[380] Train138 	 loss: 0.24,	 accuracy = 0.9126
[381] Train197 	 loss: 0.23,	 accuracy = 0.9156
[382] JSCore148 	 loss: 0.18,	 accuracy = 0.9343
[383] Train200 	 loss: 0.22,	 accuracy = 0.9171
[384] Train143 	 loss: 0.21,	 accuracy = 0.9125
[385] Train192 	 loss: 0.20,	 accuracy = 0.9273
[386] JSCore132 	 loss: 0.18,	 accuracy = 0.9457
[387] JSCore131 	 loss: 0.14,	 accuracy = 0.9561
[388] JSCore130 	 loss: 0.24,	 accuracy = 0.9002
[389] JSCore152 	 loss: 0.17,	 accuracy = 0.9299
[390] JSCore125 	 loss: 0.16,	 accuracy = 0.9501
[391] JSCore111 	 loss: 0.17,	 accuracy = 0.9385
[392] JSCore114 	 loss: 0.15,	 accuracy = 0.9472
[393] Train158 	 loss: 0.18,	 accuracy = 0.9354
[394] Train189 	 loss: 0.17,	 accuracy = 0.9437
[395] JSCore139 	 loss: 0.17,	 accuracy = 0.9397
[396] JSCore187 	 loss: 0.18,	 accuracy = 0.9372
[397] JSCore154 	 loss: 0.18,	 accuracy = 0.9311
[398] Train145 	 loss: 0.23,	 accuracy = 0.9263
[399] JSCore131 	 loss: 0.15,	 accuracy = 0.9426
[400] JSCore152 	 loss: 0.16,	 accuracy = 0.9498
[400] dev set  	 loss: 0.18,	 accuracy = 0.9250
[400] test set 	 loss: 0.15,	 accuracy = 0.9567
[401] Train192 	 loss: 0.16,	 accuracy = 0.9424
[402] Train173 	 loss: 0.23,	 accuracy = 0.9112
[403] Train140 	 loss: 0.22,	 accuracy = 0.9207
[404] JSCore110 	 loss: 0.16,	 accuracy = 0.9477
[405] Train101 	 loss: 0.22,	 accuracy = 0.9142
[406] Train117 	 loss: 0.18,	 accuracy = 0.9386
[407] JSCore165 	 loss: 0.17,	 accuracy = 0.9355
[408] Train187 	 loss: 0.20,	 accuracy = 0.9326
[409] Train167 	 loss: 0.20,	 accuracy = 0.9229
[410] JSCore191 	 loss: 0.19,	 accuracy = 0.9266
[411] JSCore200 	 loss: 0.19,	 accuracy = 0.9308
[412] JSCore119 	 loss: 0.16,	 accuracy = 0.9522
[413] Train125 	 loss: 0.20,	 accuracy = 0.9223
[414] JSCore111 	 loss: 0.13,	 accuracy = 0.9642
[415] JSCore147 	 loss: 0.15,	 accuracy = 0.9570
[416] JSCore190 	 loss: 0.16,	 accuracy = 0.9386
[417] Train191 	 loss: 0.21,	 accuracy = 0.9216
[418] JSCore157 	 loss: 0.16,	 accuracy = 0.9434
[419] JSCore125 	 loss: 0.15,	 accuracy = 0.9466
[420] Train200 	 loss: 0.20,	 accuracy = 0.9329
[421] JSCore144 	 loss: 0.21,	 accuracy = 0.9272
[422] JSCore119 	 loss: 0.17,	 accuracy = 0.9312
[423] Train111 	 loss: 0.24,	 accuracy = 0.9031
[424] Train148 	 loss: 0.23,	 accuracy = 0.9158
[425] Train168 	 loss: 0.18,	 accuracy = 0.9382
[425] dev set  	 loss: 0.18,	 accuracy = 0.9300
[425] test set 	 loss: 0.13,	 accuracy = 0.9567
[426] JSCore108 	 loss: 0.15,	 accuracy = 0.9459
[427] JSCore190 	 loss: 0.17,	 accuracy = 0.9331
[428] JSCore144 	 loss: 0.18,	 accuracy = 0.9288
[429] JSCore191 	 loss: 0.15,	 accuracy = 0.9499
[430] Train161 	 loss: 0.20,	 accuracy = 0.9312
[431] JSCore177 	 loss: 0.18,	 accuracy = 0.9418
[432] Train163 	 loss: 0.22,	 accuracy = 0.9148
[433] Train128 	 loss: 0.21,	 accuracy = 0.9293
[434] JSCore167 	 loss: 0.14,	 accuracy = 0.9482
[435] Train176 	 loss: 0.21,	 accuracy = 0.9239
[436] JSCore150 	 loss: 0.18,	 accuracy = 0.9340
[437] JSCore101 	 loss: 0.13,	 accuracy = 0.9545
[438] JSCore184 	 loss: 0.20,	 accuracy = 0.9239
[439] Train121 	 loss: 0.18,	 accuracy = 0.9307
[440] Train177 	 loss: 0.22,	 accuracy = 0.9226
[441] Train148 	 loss: 0.16,	 accuracy = 0.9446
[442] JSCore146 	 loss: 0.23,	 accuracy = 0.9057
[443] JSCore167 	 loss: 0.21,	 accuracy = 0.9224
[444] Train142 	 loss: 0.24,	 accuracy = 0.9142
[445] JSCore126 	 loss: 0.17,	 accuracy = 0.9364
[446] JSCore120 	 loss: 0.15,	 accuracy = 0.9470
[447] JSCore194 	 loss: 0.27,	 accuracy = 0.8912
[448] Train134 	 loss: 0.37,	 accuracy = 0.8352
[449] Train191 	 loss: 0.23,	 accuracy = 0.9048
[450] JSCore102 	 loss: 0.15,	 accuracy = 0.9466
[450] dev set  	 loss: 0.22,	 accuracy = 0.9100
[450] test set 	 loss: 0.15,	 accuracy = 0.9467
[451] Train173 	 loss: 0.25,	 accuracy = 0.8958
[452] JSCore129 	 loss: 0.15,	 accuracy = 0.9398
[453] JSCore105 	 loss: 0.17,	 accuracy = 0.9309
[454] Train167 	 loss: 0.23,	 accuracy = 0.9169
[455] JSCore139 	 loss: 0.20,	 accuracy = 0.9216
[456] JSCore190 	 loss: 0.17,	 accuracy = 0.9351
[457] Train167 	 loss: 0.24,	 accuracy = 0.8997
[458] JSCore137 	 loss: 0.19,	 accuracy = 0.9227
[459] Train170 	 loss: 0.23,	 accuracy = 0.9188
[460] Train104 	 loss: 0.26,	 accuracy = 0.9070
[461] Train133 	 loss: 0.19,	 accuracy = 0.9326
[462] Train191 	 loss: 0.25,	 accuracy = 0.9099
[463] Train176 	 loss: 0.23,	 accuracy = 0.9162
[464] Train162 	 loss: 0.21,	 accuracy = 0.9329
[465] JSCore156 	 loss: 0.20,	 accuracy = 0.9184
[466] Train154 	 loss: 0.20,	 accuracy = 0.9286
[467] Train190 	 loss: 0.23,	 accuracy = 0.9045
[468] Train130 	 loss: 0.21,	 accuracy = 0.9258
[469] JSCore187 	 loss: 0.22,	 accuracy = 0.9072
[470] Train137 	 loss: 0.23,	 accuracy = 0.9191
[471] Train114 	 loss: 0.25,	 accuracy = 0.9019
[472] JSCore194 	 loss: 0.21,	 accuracy = 0.9196
[473] JSCore138 	 loss: 0.18,	 accuracy = 0.9287
[474] JSCore163 	 loss: 0.20,	 accuracy = 0.9217
[475] JSCore106 	 loss: 0.13,	 accuracy = 0.9515
[475] dev set  	 loss: 0.17,	 accuracy = 0.9217
[475] test set 	 loss: 0.13,	 accuracy = 0.9483
[476] Train183 	 loss: 0.28,	 accuracy = 0.8978
[477] Train175 	 loss: 0.26,	 accuracy = 0.8991
[478] JSCore122 	 loss: 0.16,	 accuracy = 0.9432
[479] Train110 	 loss: 0.23,	 accuracy = 0.9247
[480] JSCore141 	 loss: 0.19,	 accuracy = 0.9237
[481] Train107 	 loss: 0.20,	 accuracy = 0.9308
[482] JSCore107 	 loss: 0.16,	 accuracy = 0.9446
[483] JSCore148 	 loss: 0.19,	 accuracy = 0.9350
[484] Train161 	 loss: 0.18,	 accuracy = 0.9291
[485] JSCore137 	 loss: 0.16,	 accuracy = 0.9468
[486] JSCore126 	 loss: 0.13,	 accuracy = 0.9582
[487] Train164 	 loss: 0.20,	 accuracy = 0.9273
[488] Train126 	 loss: 0.18,	 accuracy = 0.9410
[489] Train169 	 loss: 0.23,	 accuracy = 0.9166
[490] Train102 	 loss: 0.19,	 accuracy = 0.9429
[491] Train166 	 loss: 0.19,	 accuracy = 0.9306
[492] Train100 	 loss: 0.18,	 accuracy = 0.9344
[493] Train113 	 loss: 0.26,	 accuracy = 0.9049
[494] JSCore165 	 loss: 0.21,	 accuracy = 0.9388
[495] Train136 	 loss: 0.20,	 accuracy = 0.9352
[496] JSCore140 	 loss: 0.18,	 accuracy = 0.9328
[497] JSCore156 	 loss: 0.16,	 accuracy = 0.9383
[498] JSCore126 	 loss: 0.22,	 accuracy = 0.9187
[499] JSCore166 	 loss: 0.14,	 accuracy = 0.9510
[500] JSCore110 	 loss: 0.16,	 accuracy = 0.9490
[500] dev set  	 loss: 0.17,	 accuracy = 0.9317
[500] test set 	 loss: 0.12,	 accuracy = 0.9583
[501] Train134 	 loss: 0.20,	 accuracy = 0.9416
[502] Train106 	 loss: 0.19,	 accuracy = 0.9448
[503] Train100 	 loss: 0.22,	 accuracy = 0.9184
[504] JSCore135 	 loss: 0.17,	 accuracy = 0.9365
[505] Train102 	 loss: 0.23,	 accuracy = 0.9160
[506] Train136 	 loss: 0.19,	 accuracy = 0.9312
[507] Train162 	 loss: 0.19,	 accuracy = 0.9357
[508] JSCore146 	 loss: 0.14,	 accuracy = 0.9515
[509] JSCore183 	 loss: 0.18,	 accuracy = 0.9315
[510] Train104 	 loss: 0.22,	 accuracy = 0.9315
[511] Train184 	 loss: 0.23,	 accuracy = 0.9205
[512] JSCore141 	 loss: 0.19,	 accuracy = 0.9273
[513] JSCore155 	 loss: 0.15,	 accuracy = 0.9508
[514] JSCore139 	 loss: 0.15,	 accuracy = 0.9468
[515] JSCore119 	 loss: 0.15,	 accuracy = 0.9424
[516] JSCore101 	 loss: 0.21,	 accuracy = 0.9184
[517] Train160 	 loss: 0.24,	 accuracy = 0.9048
[518] JSCore191 	 loss: 0.15,	 accuracy = 0.9450
[519] Train189 	 loss: 0.20,	 accuracy = 0.9307
[520] JSCore125 	 loss: 0.13,	 accuracy = 0.9407
[521] Train148 	 loss: 0.22,	 accuracy = 0.9230
[522] JSCore115 	 loss: 0.18,	 accuracy = 0.9278
[523] JSCore117 	 loss: 0.17,	 accuracy = 0.9391
[524] JSCore145 	 loss: 0.16,	 accuracy = 0.9369
[525] Train135 	 loss: 0.23,	 accuracy = 0.9145
[525] dev set  	 loss: 0.20,	 accuracy = 0.9183
[525] test set 	 loss: 0.12,	 accuracy = 0.9567
[526] Train174 	 loss: 0.24,	 accuracy = 0.9052
[527] Train188 	 loss: 0.21,	 accuracy = 0.9253
[528] Train171 	 loss: 0.23,	 accuracy = 0.9164
[529] Train154 	 loss: 0.19,	 accuracy = 0.9339
[530] JSCore140 	 loss: 0.20,	 accuracy = 0.9190
[531] Train103 	 loss: 0.18,	 accuracy = 0.9382
[532] JSCore167 	 loss: 0.16,	 accuracy = 0.9428
[533] Train176 	 loss: 0.19,	 accuracy = 0.9495
[534] JSCore105 	 loss: 0.16,	 accuracy = 0.9368
[535] JSCore145 	 loss: 0.13,	 accuracy = 0.9562
[536] JSCore174 	 loss: 0.16,	 accuracy = 0.9342
[537] Train100 	 loss: 0.16,	 accuracy = 0.9489
[538] Train197 	 loss: 0.17,	 accuracy = 0.9302
[539] JSCore170 	 loss: 0.17,	 accuracy = 0.9345
[540] JSCore199 	 loss: 0.14,	 accuracy = 0.9510
[541] JSCore175 	 loss: 0.15,	 accuracy = 0.9419
[542] Train142 	 loss: 0.19,	 accuracy = 0.9311
[543] JSCore191 	 loss: 0.17,	 accuracy = 0.9326
[544] JSCore146 	 loss: 0.17,	 accuracy = 0.9403
[545] JSCore150 	 loss: 0.14,	 accuracy = 0.9503
[546] JSCore102 	 loss: 0.15,	 accuracy = 0.9526
[547] Train151 	 loss: 0.18,	 accuracy = 0.9333
[548] Train181 	 loss: 0.20,	 accuracy = 0.9208
[549] JSCore187 	 loss: 0.16,	 accuracy = 0.9415
[550] JSCore176 	 loss: 0.15,	 accuracy = 0.9434
[550] dev set  	 loss: 0.18,	 accuracy = 0.9283
[550] test set 	 loss: 0.10,	 accuracy = 0.9717
[551] Train132 	 loss: 0.18,	 accuracy = 0.9370
[552] Train116 	 loss: 0.19,	 accuracy = 0.9378
[553] JSCore167 	 loss: 0.22,	 accuracy = 0.9063
[554] Train134 	 loss: 0.15,	 accuracy = 0.9589

took 1h38m
