2020-11-02 15:37:57.208234: Step [0] train Loss : 4.451777, training accuracy : 0.1875
2020-11-02 15:38:42.723464: Step [0] val Loss : 4.219480, val accuracy : 0.0174923
2020-11-02 15:38:55.136853: Step [100] train Loss : 3.162268, training accuracy : 0
2020-11-02 15:39:07.425743: Step [200] train Loss : 1.888495, training accuracy : 0
2020-11-02 15:39:53.201844: Step [200] val Loss : 13.010412, val accuracy : 0.0197906
2020-11-02 15:40:05.477731: Step [300] train Loss : 1.710598, training accuracy : 0
2020-11-02 15:40:17.726494: Step [400] train Loss : 2.285333, training accuracy : 0.125
2020-11-02 15:41:03.523871: Step [400] val Loss : 9.567571, val accuracy : 0.0194076
2020-11-02 15:41:15.935632: Step [500] train Loss : 0.689892, training accuracy : 0
2020-11-02 15:41:28.475818: Step [600] train Loss : 0.531735, training accuracy : 0
2020-11-02 15:42:14.895427: Step [600] val Loss : 10.680215, val accuracy : 0.0190245
2020-11-02 15:42:27.410021: Step [700] train Loss : 0.294478, training accuracy : 0
2020-11-02 15:42:39.976662: Step [800] train Loss : 0.587241, training accuracy : 0
2020-11-02 15:43:26.770598: Step [800] val Loss : 7.437372, val accuracy : 0.0190245
2020-11-02 15:43:39.309107: Step [900] train Loss : 0.352322, training accuracy : 0
2020-11-02 15:43:51.995333: Step [1000] train Loss : 0.210653, training accuracy : 0
2020-11-02 15:44:39.661366: Step [1000] val Loss : 7.019403, val accuracy : 0.0190245
2020-11-02 15:44:52.410022: Step [1100] train Loss : 0.054857, training accuracy : 0
2020-11-02 15:45:05.355245: Step [1200] train Loss : 0.053495, training accuracy : 0
2020-11-02 15:45:52.886870: Step [1200] val Loss : 6.476278, val accuracy : 0.0190245
2020-11-02 15:46:05.563014: Step [1300] train Loss : 0.017112, training accuracy : 0.0625
2020-11-02 15:46:18.331558: Step [1400] train Loss : 0.276403, training accuracy : 0
2020-11-02 15:47:05.632001: Step [1400] val Loss : 5.955071, val accuracy : 0.0190245
2020-11-02 15:47:18.504530: Step [1500] train Loss : 0.018878, training accuracy : 0
2020-11-02 15:47:31.372758: Step [1600] train Loss : 0.059408, training accuracy : 0
2020-11-02 15:48:18.951162: Step [1600] val Loss : 5.360252, val accuracy : 0.0190245
2020-11-02 15:48:31.887936: Step [1700] train Loss : 0.028561, training accuracy : 0
2020-11-02 15:48:44.865589: Step [1800] train Loss : 0.008514, training accuracy : 0
2020-11-02 15:49:32.827837: Step [1800] val Loss : 4.431525, val accuracy : 0.0194076
2020-11-02 15:49:45.732202: Step [1900] train Loss : 0.191928, training accuracy : 0
2020-11-02 15:49:59.040962: Step [2000] train Loss : 0.014791, training accuracy : 0.0625
2020-11-02 15:50:46.432237: Step [2000] val Loss : 4.476066, val accuracy : 0.0190245
-----save:models/model.ckpt-2000
2020-11-02 15:51:00.828174: Step [2100] train Loss : 0.010766, training accuracy : 0.0625
2020-11-02 15:51:13.764994: Step [2200] train Loss : 0.085822, training accuracy : 0
2020-11-02 15:52:00.938146: Step [2200] val Loss : 4.355613, val accuracy : 0.0110444
2020-11-02 15:52:13.771588: Step [2300] train Loss : 0.119277, training accuracy : 0
2020-11-02 15:52:26.567043: Step [2400] train Loss : 0.024402, training accuracy : 0
2020-11-02 15:53:14.222747: Step [2400] val Loss : 4.345027, val accuracy : 0.0193437
2020-11-02 15:53:27.150898: Step [2500] train Loss : 0.050773, training accuracy : 0
2020-11-02 15:53:39.925711: Step [2600] train Loss : 0.006547, training accuracy : 0
2020-11-02 15:54:27.511248: Step [2600] val Loss : 4.385560, val accuracy : 0.0111721
2020-11-02 15:54:40.305635: Step [2700] train Loss : 0.011848, training accuracy : 0
2020-11-02 15:54:53.234307: Step [2800] train Loss : 0.012595, training accuracy : 0
2020-11-02 15:55:41.143845: Step [2800] val Loss : 4.392406, val accuracy : 0.0110444
2020-11-02 15:55:53.962262: Step [2900] train Loss : 0.018239, training accuracy : 0
2020-11-02 15:56:06.990641: Step [3000] train Loss : 0.067942, training accuracy : 0
2020-11-02 15:56:54.403528: Step [3000] val Loss : 4.526069, val accuracy : 0.0106614
2020-11-02 15:57:07.287715: Step [3100] train Loss : 0.002908, training accuracy : 0
2020-11-02 15:57:20.071291: Step [3200] train Loss : 0.015377, training accuracy : 0
2020-11-02 15:58:07.453693: Step [3200] val Loss : 4.584523, val accuracy : 0.0180031
2020-11-02 15:58:20.484154: Step [3300] train Loss : 0.003488, training accuracy : 0
2020-11-02 15:58:33.126986: Step [3400] train Loss : 0.077828, training accuracy : 0
2020-11-02 15:59:20.953589: Step [3400] val Loss : 4.706525, val accuracy : 0.0118105
2020-11-02 15:59:33.913899: Step [3500] train Loss : 0.002673, training accuracy : 0.0625
2020-11-02 15:59:46.716906: Step [3600] train Loss : 0.086050, training accuracy : 0
2020-11-02 16:00:34.343889: Step [3600] val Loss : 4.733990, val accuracy : 0.0178115
2020-11-02 16:00:47.121723: Step [3700] train Loss : 0.000803, training accuracy : 0
2020-11-02 16:01:00.026031: Step [3800] train Loss : 0.004648, training accuracy : 0.0625
2020-11-02 16:01:47.546183: Step [3800] val Loss : 4.868133, val accuracy : 0.0179392
2020-11-02 16:02:00.286305: Step [3900] train Loss : 0.002961, training accuracy : 0.125
2020-11-02 16:02:13.520870: Step [4000] train Loss : 0.083561, training accuracy : 0.0625
2020-11-02 16:03:00.840206: Step [4000] val Loss : 5.280580, val accuracy : 0.0179392
-----save:models/model.ckpt-4000
2020-11-02 16:03:14.624543: Step [4100] train Loss : 0.028515, training accuracy : 0
2020-11-02 16:03:27.654577: Step [4200] train Loss : 0.083428, training accuracy : 0
2020-11-02 16:04:15.113641: Step [4200] val Loss : 5.515779, val accuracy : 0.0179392
2020-11-02 16:04:28.035244: Step [4300] train Loss : 0.006602, training accuracy : 0.0625
2020-11-02 16:04:41.012877: Step [4400] train Loss : 0.005454, training accuracy : 0
2020-11-02 16:05:28.710228: Step [4400] val Loss : 4.986513, val accuracy : 0.0162794
2020-11-02 16:05:41.649157: Step [4500] train Loss : 0.117655, training accuracy : 0
2020-11-02 16:05:54.546338: Step [4600] train Loss : 0.008130, training accuracy : 0
2020-11-02 16:06:43.125019: Step [4600] val Loss : 5.318214, val accuracy : 0.0138534
2020-11-02 16:06:56.144484: Step [4700] train Loss : 0.198717, training accuracy : 0
2020-11-02 16:07:09.052229: Step [4800] train Loss : 0.166929, training accuracy : 0
2020-11-02 16:07:56.452739: Step [4800] val Loss : 5.759774, val accuracy : 0.0183861
2020-11-02 16:08:09.284685: Step [4900] train Loss : 0.001290, training accuracy : 0.0625
2020-11-02 16:08:22.219911: Step [5000] train Loss : 0.037633, training accuracy : 0.0625
2020-11-02 16:09:10.040866: Step [5000] val Loss : 6.110466, val accuracy : 0.0179392
2020-11-02 16:09:22.748253: Step [5100] train Loss : 0.047009, training accuracy : 0.0625
2020-11-02 16:09:35.874876: Step [5200] train Loss : 0.107128, training accuracy : 0
2020-11-02 16:10:23.152308: Step [5200] val Loss : 6.624900, val accuracy : 0.0179392
2020-11-02 16:10:36.051775: Step [5300] train Loss : 0.085515, training accuracy : 0.0625
2020-11-02 16:10:48.866156: Step [5400] train Loss : 0.409375, training accuracy : 0
2020-11-02 16:11:36.761074: Step [5400] val Loss : 6.839243, val accuracy : 0.0263023
2020-11-02 16:11:49.638604: Step [5500] train Loss : 0.074292, training accuracy : 0.0625
2020-11-02 16:12:02.772029: Step [5600] train Loss : 0.015727, training accuracy : 0
2020-11-02 16:12:50.155442: Step [5600] val Loss : 6.886412, val accuracy : 0.0256639
2020-11-02 16:13:02.860564: Step [5700] train Loss : 0.011184, training accuracy : 0
2020-11-02 16:13:15.807399: Step [5800] train Loss : 0.105041, training accuracy : 0.0625
2020-11-02 16:14:02.974487: Step [5800] val Loss : 6.774150, val accuracy : 0.0195352
2020-11-02 16:14:15.964116: Step [5900] train Loss : 0.006180, training accuracy : 0
2020-11-02 16:14:28.860469: Step [6000] train Loss : 0.002312, training accuracy : 0
2020-11-02 16:15:16.336347: Step [6000] val Loss : 6.687222, val accuracy : 0.0291113
-----save:models/model.ckpt-6000
2020-11-02 16:15:30.259542: Step [6100] train Loss : 0.000506, training accuracy : 0
2020-11-02 16:15:42.874291: Step [6200] train Loss : 0.002289, training accuracy : 0.0625
2020-11-02 16:16:30.261237: Step [6200] val Loss : 7.348487, val accuracy : 0.0201736
2020-11-02 16:16:43.067244: Step [6300] train Loss : 0.007106, training accuracy : 0.125
2020-11-02 16:16:56.013800: Step [6400] train Loss : 0.000544, training accuracy : 0
2020-11-02 16:17:43.874414: Step [6400] val Loss : 7.402358, val accuracy : 0.0302605
2020-11-02 16:17:56.692698: Step [6500] train Loss : 0.012519, training accuracy : 0
2020-11-02 16:18:09.608623: Step [6600] train Loss : 0.020444, training accuracy : 0.0625
2020-11-02 16:18:57.944717: Step [6600] val Loss : 7.957761, val accuracy : 0.032048
2020-11-02 16:19:10.604547: Step [6700] train Loss : 0.057993, training accuracy : 0.125
2020-11-02 16:19:23.401778: Step [6800] train Loss : 0.062361, training accuracy : 0
2020-11-02 16:20:10.866427: Step [6800] val Loss : 6.631777, val accuracy : 0.0329418
2020-11-02 16:20:23.524615: Step [6900] train Loss : 0.028056, training accuracy : 0
2020-11-02 16:20:36.328313: Step [7000] train Loss : 0.002315, training accuracy : 0
2020-11-02 16:21:23.668482: Step [7000] val Loss : 10.059795, val accuracy : 0.0365807
2020-11-02 16:21:36.660421: Step [7100] train Loss : 0.001399, training accuracy : 0.0625
2020-11-02 16:21:50.029407: Step [7200] train Loss : 0.044736, training accuracy : 0.0625
2020-11-02 16:22:37.962835: Step [7200] val Loss : 9.027893, val accuracy : 0.036453
2020-11-02 16:22:50.644555: Step [7300] train Loss : 0.002088, training accuracy : 0
2020-11-02 16:23:03.500411: Step [7400] train Loss : 0.001914, training accuracy : 0
2020-11-02 16:23:50.540379: Step [7400] val Loss : 9.877556, val accuracy : 0.0377937
2020-11-02 16:24:03.278654: Step [7500] train Loss : 0.010749, training accuracy : 0.0625
2020-11-02 16:24:15.917410: Step [7600] train Loss : 0.000708, training accuracy : 0
2020-11-02 16:25:03.002879: Step [7600] val Loss : 6.635362, val accuracy : 0.0444969
2020-11-02 16:25:15.709085: Step [7700] train Loss : 0.001703, training accuracy : 0
2020-11-02 16:25:28.378377: Step [7800] train Loss : 0.000629, training accuracy : 0.0625
2020-11-02 16:26:15.486690: Step [7800] val Loss : 6.803297, val accuracy : 0.0425179
2020-11-02 16:26:28.027219: Step [7900] train Loss : 0.061680, training accuracy : 0
2020-11-02 16:26:40.677709: Step [8000] train Loss : 0.002516, training accuracy : 0
2020-11-02 16:27:27.783940: Step [8000] val Loss : 6.278635, val accuracy : 0.0385598
-----save:models/model.ckpt-8000
2020-11-02 16:27:41.331630: Step [8100] train Loss : 0.001402, training accuracy : 0.0625
2020-11-02 16:27:54.020844: Step [8200] train Loss : 0.001184, training accuracy : 0.1875
2020-11-02 16:28:41.079053: Step [8200] val Loss : 4.479759, val accuracy : 0.0701609
2020-11-02 16:28:53.780333: Step [8300] train Loss : 0.000839, training accuracy : 0
2020-11-02 16:29:06.536083: Step [8400] train Loss : 0.001597, training accuracy : 0.0625
2020-11-02 16:29:53.773071: Step [8400] val Loss : 4.883051, val accuracy : 0.0725868
2020-11-02 16:30:06.546049: Step [8500] train Loss : 0.013211, training accuracy : 0.0625
2020-11-02 16:30:19.321398: Step [8600] train Loss : 0.004649, training accuracy : 0
2020-11-02 16:31:06.456382: Step [8600] val Loss : 8.681377, val accuracy : 0.0537538
2020-11-02 16:31:19.036534: Step [8700] train Loss : 0.006653, training accuracy : 0.125
2020-11-02 16:31:31.854400: Step [8800] train Loss : 0.002683, training accuracy : 0
2020-11-02 16:32:18.938620: Step [8800] val Loss : 4.728459, val accuracy : 0.104635
2020-11-02 16:32:31.707159: Step [8900] train Loss : 0.020025, training accuracy : 0.125
2020-11-02 16:32:44.462050: Step [9000] train Loss : 0.008877, training accuracy : 0.0625
2020-11-02 16:33:31.752998: Step [9000] val Loss : 3.812795, val accuracy : 0.199694
2020-11-02 16:33:44.462998: Step [9100] train Loss : 0.001572, training accuracy : 0.1875
2020-11-02 16:33:57.337466: Step [9200] train Loss : 0.005766, training accuracy : 0.125
2020-11-02 16:34:44.460697: Step [9200] val Loss : 3.064202, val accuracy : 0.234359
2020-11-02 16:34:57.289857: Step [9300] train Loss : 0.001191, training accuracy : 0
2020-11-02 16:35:09.949805: Step [9400] train Loss : 0.003511, training accuracy : 0.1875
2020-11-02 16:35:57.668908: Step [9400] val Loss : 2.668586, val accuracy : 0.291433
2020-11-02 16:36:10.336091: Step [9500] train Loss : 0.030213, training accuracy : 0.625
2020-11-02 16:36:23.274206: Step [9600] train Loss : 0.000295, training accuracy : 0.875
2020-11-02 16:37:11.567725: Step [9600] val Loss : 1.537270, val accuracy : 0.569523
2020-11-02 16:37:24.354095: Step [9700] train Loss : 0.000855, training accuracy : 0.5
2020-11-02 16:37:37.440869: Step [9800] train Loss : 0.000576, training accuracy : 0.625
2020-11-02 16:38:24.862105: Step [9800] val Loss : 1.792353, val accuracy : 0.449694
2020-11-02 16:38:37.705421: Step [9900] train Loss : 0.137523, training accuracy : 0.625
2020-11-02 16:38:51.008138: Step [10000] train Loss : 0.000887, training accuracy : 0.8125
2020-11-02 16:39:38.602564: Step [10000] val Loss : 1.078526, val accuracy : 0.668156
-----save:models/model.ckpt-10000
2020-11-02 15:37:57.208234: Step [0] train Loss : 4.451777, training accuracy : 0.1875
2020-11-02 15:38:42.723464: Step [0] val Loss : 4.219480, val accuracy : 0.0174923
2020-11-02 15:38:55.136853: Step [100] train Loss : 3.162268, training accuracy : 0
2020-11-02 15:39:07.425743: Step [200] train Loss : 1.888495, training accuracy : 0
2020-11-02 15:39:53.201844: Step [200] val Loss : 13.010412, val accuracy : 0.0197906
2020-11-02 15:40:05.477731: Step [300] train Loss : 1.710598, training accuracy : 0
2020-11-02 15:40:17.726494: Step [400] train Loss : 2.285333, training accuracy : 0.125
2020-11-02 15:41:03.523871: Step [400] val Loss : 9.567571, val accuracy : 0.0194076
2020-11-02 15:41:15.935632: Step [500] train Loss : 0.689892, training accuracy : 0
2020-11-02 15:41:28.475818: Step [600] train Loss : 0.531735, training accuracy : 0
2020-11-02 15:42:14.895427: Step [600] val Loss : 10.680215, val accuracy : 0.0190245
2020-11-02 15:42:27.410021: Step [700] train Loss : 0.294478, training accuracy : 0
2020-11-02 15:42:39.976662: Step [800] train Loss : 0.587241, training accuracy : 0
2020-11-02 15:43:26.770598: Step [800] val Loss : 7.437372, val accuracy : 0.0190245
2020-11-02 15:43:39.309107: Step [900] train Loss : 0.352322, training accuracy : 0
2020-11-02 15:43:51.995333: Step [1000] train Loss : 0.210653, training accuracy : 0
2020-11-02 15:44:39.661366: Step [1000] val Loss : 7.019403, val accuracy : 0.0190245
2020-11-02 15:44:52.410022: Step [1100] train Loss : 0.054857, training accuracy : 0
2020-11-02 15:45:05.355245: Step [1200] train Loss : 0.053495, training accuracy : 0
2020-11-02 15:45:52.886870: Step [1200] val Loss : 6.476278, val accuracy : 0.0190245
2020-11-02 15:46:05.563014: Step [1300] train Loss : 0.017112, training accuracy : 0.0625
2020-11-02 15:46:18.331558: Step [1400] train Loss : 0.276403, training accuracy : 0
2020-11-02 15:47:05.632001: Step [1400] val Loss : 5.955071, val accuracy : 0.0190245
2020-11-02 15:47:18.504530: Step [1500] train Loss : 0.018878, training accuracy : 0
2020-11-02 15:47:31.372758: Step [1600] train Loss : 0.059408, training accuracy : 0
2020-11-02 15:48:18.951162: Step [1600] val Loss : 5.360252, val accuracy : 0.0190245
2020-11-02 15:48:31.887936: Step [1700] train Loss : 0.028561, training accuracy : 0
2020-11-02 15:48:44.865589: Step [1800] train Loss : 0.008514, training accuracy : 0
2020-11-02 15:49:32.827837: Step [1800] val Loss : 4.431525, val accuracy : 0.0194076
2020-11-02 15:49:45.732202: Step [1900] train Loss : 0.191928, training accuracy : 0
2020-11-02 15:49:59.040962: Step [2000] train Loss : 0.014791, training accuracy : 0.0625
2020-11-02 15:50:46.432237: Step [2000] val Loss : 4.476066, val accuracy : 0.0190245
-----save:models/model.ckpt-2000
2020-11-02 15:51:00.828174: Step [2100] train Loss : 0.010766, training accuracy : 0.0625
2020-11-02 15:51:13.764994: Step [2200] train Loss : 0.085822, training accuracy : 0
2020-11-02 15:52:00.938146: Step [2200] val Loss : 4.355613, val accuracy : 0.0110444
2020-11-02 15:52:13.771588: Step [2300] train Loss : 0.119277, training accuracy : 0
2020-11-02 15:52:26.567043: Step [2400] train Loss : 0.024402, training accuracy : 0
2020-11-02 15:53:14.222747: Step [2400] val Loss : 4.345027, val accuracy : 0.0193437
2020-11-02 15:53:27.150898: Step [2500] train Loss : 0.050773, training accuracy : 0
2020-11-02 15:53:39.925711: Step [2600] train Loss : 0.006547, training accuracy : 0
2020-11-02 15:54:27.511248: Step [2600] val Loss : 4.385560, val accuracy : 0.0111721
2020-11-02 15:54:40.305635: Step [2700] train Loss : 0.011848, training accuracy : 0
2020-11-02 15:54:53.234307: Step [2800] train Loss : 0.012595, training accuracy : 0
2020-11-02 15:55:41.143845: Step [2800] val Loss : 4.392406, val accuracy : 0.0110444
2020-11-02 15:55:53.962262: Step [2900] train Loss : 0.018239, training accuracy : 0
2020-11-02 15:56:06.990641: Step [3000] train Loss : 0.067942, training accuracy : 0
2020-11-02 15:56:54.403528: Step [3000] val Loss : 4.526069, val accuracy : 0.0106614
2020-11-02 15:57:07.287715: Step [3100] train Loss : 0.002908, training accuracy : 0
2020-11-02 15:57:20.071291: Step [3200] train Loss : 0.015377, training accuracy : 0
2020-11-02 15:58:07.453693: Step [3200] val Loss : 4.584523, val accuracy : 0.0180031
2020-11-02 15:58:20.484154: Step [3300] train Loss : 0.003488, training accuracy : 0
2020-11-02 15:58:33.126986: Step [3400] train Loss : 0.077828, training accuracy : 0
2020-11-02 15:59:20.953589: Step [3400] val Loss : 4.706525, val accuracy : 0.0118105
2020-11-02 15:59:33.913899: Step [3500] train Loss : 0.002673, training accuracy : 0.0625
2020-11-02 15:59:46.716906: Step [3600] train Loss : 0.086050, training accuracy : 0
2020-11-02 16:00:34.343889: Step [3600] val Loss : 4.733990, val accuracy : 0.0178115
2020-11-02 16:00:47.121723: Step [3700] train Loss : 0.000803, training accuracy : 0
2020-11-02 16:01:00.026031: Step [3800] train Loss : 0.004648, training accuracy : 0.0625
2020-11-02 16:01:47.546183: Step [3800] val Loss : 4.868133, val accuracy : 0.0179392
2020-11-02 16:02:00.286305: Step [3900] train Loss : 0.002961, training accuracy : 0.125
2020-11-02 16:02:13.520870: Step [4000] train Loss : 0.083561, training accuracy : 0.0625
2020-11-02 16:03:00.840206: Step [4000] val Loss : 5.280580, val accuracy : 0.0179392
-----save:models/model.ckpt-4000
2020-11-02 16:03:14.624543: Step [4100] train Loss : 0.028515, training accuracy : 0
2020-11-02 16:03:27.654577: Step [4200] train Loss : 0.083428, training accuracy : 0
2020-11-02 16:04:15.113641: Step [4200] val Loss : 5.515779, val accuracy : 0.0179392
2020-11-02 16:04:28.035244: Step [4300] train Loss : 0.006602, training accuracy : 0.0625
2020-11-02 16:04:41.012877: Step [4400] train Loss : 0.005454, training accuracy : 0
2020-11-02 16:05:28.710228: Step [4400] val Loss : 4.986513, val accuracy : 0.0162794
2020-11-02 16:05:41.649157: Step [4500] train Loss : 0.117655, training accuracy : 0
2020-11-02 16:05:54.546338: Step [4600] train Loss : 0.008130, training accuracy : 0
2020-11-02 16:06:43.125019: Step [4600] val Loss : 5.318214, val accuracy : 0.0138534
2020-11-02 16:06:56.144484: Step [4700] train Loss : 0.198717, training accuracy : 0
2020-11-02 16:07:09.052229: Step [4800] train Loss : 0.166929, training accuracy : 0
2020-11-02 16:07:56.452739: Step [4800] val Loss : 5.759774, val accuracy : 0.0183861
2020-11-02 16:08:09.284685: Step [4900] train Loss : 0.001290, training accuracy : 0.0625
2020-11-02 16:08:22.219911: Step [5000] train Loss : 0.037633, training accuracy : 0.0625
2020-11-02 16:09:10.040866: Step [5000] val Loss : 6.110466, val accuracy : 0.0179392
2020-11-02 16:09:22.748253: Step [5100] train Loss : 0.047009, training accuracy : 0.0625
2020-11-02 16:09:35.874876: Step [5200] train Loss : 0.107128, training accuracy : 0
2020-11-02 16:10:23.152308: Step [5200] val Loss : 6.624900, val accuracy : 0.0179392
2020-11-02 16:10:36.051775: Step [5300] train Loss : 0.085515, training accuracy : 0.0625
2020-11-02 16:10:48.866156: Step [5400] train Loss : 0.409375, training accuracy : 0
2020-11-02 16:11:36.761074: Step [5400] val Loss : 6.839243, val accuracy : 0.0263023
2020-11-02 16:11:49.638604: Step [5500] train Loss : 0.074292, training accuracy : 0.0625
2020-11-02 16:12:02.772029: Step [5600] train Loss : 0.015727, training accuracy : 0
2020-11-02 16:12:50.155442: Step [5600] val Loss : 6.886412, val accuracy : 0.0256639
2020-11-02 16:13:02.860564: Step [5700] train Loss : 0.011184, training accuracy : 0
2020-11-02 16:13:15.807399: Step [5800] train Loss : 0.105041, training accuracy : 0.0625
2020-11-02 16:14:02.974487: Step [5800] val Loss : 6.774150, val accuracy : 0.0195352
2020-11-02 16:14:15.964116: Step [5900] train Loss : 0.006180, training accuracy : 0
2020-11-02 16:14:28.860469: Step [6000] train Loss : 0.002312, training accuracy : 0
2020-11-02 16:15:16.336347: Step [6000] val Loss : 6.687222, val accuracy : 0.0291113
-----save:models/model.ckpt-6000
2020-11-02 16:15:30.259542: Step [6100] train Loss : 0.000506, training accuracy : 0
2020-11-02 16:15:42.874291: Step [6200] train Loss : 0.002289, training accuracy : 0.0625
2020-11-02 16:16:30.261237: Step [6200] val Loss : 7.348487, val accuracy : 0.0201736
2020-11-02 16:16:43.067244: Step [6300] train Loss : 0.007106, training accuracy : 0.125
2020-11-02 16:16:56.013800: Step [6400] train Loss : 0.000544, training accuracy : 0
2020-11-02 16:17:43.874414: Step [6400] val Loss : 7.402358, val accuracy : 0.0302605
2020-11-02 16:17:56.692698: Step [6500] train Loss : 0.012519, training accuracy : 0
2020-11-02 16:18:09.608623: Step [6600] train Loss : 0.020444, training accuracy : 0.0625
2020-11-02 16:18:57.944717: Step [6600] val Loss : 7.957761, val accuracy : 0.032048
2020-11-02 16:19:10.604547: Step [6700] train Loss : 0.057993, training accuracy : 0.125
2020-11-02 16:19:23.401778: Step [6800] train Loss : 0.062361, training accuracy : 0
2020-11-02 16:20:10.866427: Step [6800] val Loss : 6.631777, val accuracy : 0.0329418
2020-11-02 16:20:23.524615: Step [6900] train Loss : 0.028056, training accuracy : 0
2020-11-02 16:20:36.328313: Step [7000] train Loss : 0.002315, training accuracy : 0
2020-11-02 16:21:23.668482: Step [7000] val Loss : 10.059795, val accuracy : 0.0365807
2020-11-02 16:21:36.660421: Step [7100] train Loss : 0.001399, training accuracy : 0.0625
2020-11-02 16:21:50.029407: Step [7200] train Loss : 0.044736, training accuracy : 0.0625
2020-11-02 16:22:37.962835: Step [7200] val Loss : 9.027893, val accuracy : 0.036453
2020-11-02 16:22:50.644555: Step [7300] train Loss : 0.002088, training accuracy : 0
2020-11-02 16:23:03.500411: Step [7400] train Loss : 0.001914, training accuracy : 0
2020-11-02 16:23:50.540379: Step [7400] val Loss : 9.877556, val accuracy : 0.0377937
2020-11-02 16:24:03.278654: Step [7500] train Loss : 0.010749, training accuracy : 0.0625
2020-11-02 16:24:15.917410: Step [7600] train Loss : 0.000708, training accuracy : 0
2020-11-02 16:25:03.002879: Step [7600] val Loss : 6.635362, val accuracy : 0.0444969
2020-11-02 16:25:15.709085: Step [7700] train Loss : 0.001703, training accuracy : 0
2020-11-02 16:25:28.378377: Step [7800] train Loss : 0.000629, training accuracy : 0.0625
2020-11-02 16:26:15.486690: Step [7800] val Loss : 6.803297, val accuracy : 0.0425179
2020-11-02 16:26:28.027219: Step [7900] train Loss : 0.061680, training accuracy : 0
2020-11-02 16:26:40.677709: Step [8000] train Loss : 0.002516, training accuracy : 0
2020-11-02 16:27:27.783940: Step [8000] val Loss : 6.278635, val accuracy : 0.0385598
-----save:models/model.ckpt-8000
2020-11-02 16:27:41.331630: Step [8100] train Loss : 0.001402, training accuracy : 0.0625
2020-11-02 16:27:54.020844: Step [8200] train Loss : 0.001184, training accuracy : 0.1875
2020-11-02 16:28:41.079053: Step [8200] val Loss : 4.479759, val accuracy : 0.0701609
2020-11-02 16:28:53.780333: Step [8300] train Loss : 0.000839, training accuracy : 0
2020-11-02 16:29:06.536083: Step [8400] train Loss : 0.001597, training accuracy : 0.0625
2020-11-02 16:29:53.773071: Step [8400] val Loss : 4.883051, val accuracy : 0.0725868
2020-11-02 16:30:06.546049: Step [8500] train Loss : 0.013211, training accuracy : 0.0625
2020-11-02 16:30:19.321398: Step [8600] train Loss : 0.004649, training accuracy : 0
2020-11-02 16:31:06.456382: Step [8600] val Loss : 8.681377, val accuracy : 0.0537538
2020-11-02 16:31:19.036534: Step [8700] train Loss : 0.006653, training accuracy : 0.125
2020-11-02 16:31:31.854400: Step [8800] train Loss : 0.002683, training accuracy : 0
2020-11-02 16:32:18.938620: Step [8800] val Loss : 4.728459, val accuracy : 0.104635
2020-11-02 16:32:31.707159: Step [8900] train Loss : 0.020025, training accuracy : 0.125
2020-11-02 16:32:44.462050: Step [9000] train Loss : 0.008877, training accuracy : 0.0625
2020-11-02 16:33:31.752998: Step [9000] val Loss : 3.812795, val accuracy : 0.199694
2020-11-02 16:33:44.462998: Step [9100] train Loss : 0.001572, training accuracy : 0.1875
2020-11-02 16:33:57.337466: Step [9200] train Loss : 0.005766, training accuracy : 0.125
2020-11-02 16:34:44.460697: Step [9200] val Loss : 3.064202, val accuracy : 0.234359
2020-11-02 16:34:57.289857: Step [9300] train Loss : 0.001191, training accuracy : 0
2020-11-02 16:35:09.949805: Step [9400] train Loss : 0.003511, training accuracy : 0.1875
2020-11-02 16:35:57.668908: Step [9400] val Loss : 2.668586, val accuracy : 0.291433
2020-11-02 16:36:10.336091: Step [9500] train Loss : 0.030213, training accuracy : 0.625
2020-11-02 16:36:23.274206: Step [9600] train Loss : 0.000295, training accuracy : 0.875
2020-11-02 16:37:11.567725: Step [9600] val Loss : 1.537270, val accuracy : 0.569523
2020-11-02 16:37:24.354095: Step [9700] train Loss : 0.000855, training accuracy : 0.5
2020-11-02 16:37:37.440869: Step [9800] train Loss : 0.000576, training accuracy : 0.625
2020-11-02 16:38:24.862105: Step [9800] val Loss : 1.792353, val accuracy : 0.449694
2020-11-02 16:38:37.705421: Step [9900] train Loss : 0.137523, training accuracy : 0.625
2020-11-02 16:38:51.008138: Step [10000] train Loss : 0.000887, training accuracy : 0.8125
2020-11-02 16:39:38.602564: Step [10000] val Loss : 1.078526, val accuracy : 0.668156
-----save:models/model.ckpt-10000