	Train size: 80 Test size: 20
Tokenizer: allenai/longformer-base-4096 Model: allenai/longformer-base-4096


		-------------RUN 1-----------
			------------EPOCH 1---------------
Loss:  tensor(2403.2153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1409.2084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1660.9039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1814.0017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1561.3966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2582.7590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1214.2073, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1922.7441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2038.3810, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1231.6514, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2478.6108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1829.6870, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1783.8223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1357.9861, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2069.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1446.8513, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1276.5627, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2522.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2463.6284, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1860.5748, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2556.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1578.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1726.7695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(628.7643, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1106.9677, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1073.5536, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1562.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1298.9762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1239.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1810.3584, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1499.4249, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2114.8652, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2542.8315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3781.4705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2318.2837, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2780.3210, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1140.7097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1366.0920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1210.6777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(773.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2592.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2148.8379, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1427.8389, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1759.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1531.9370, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1100.3021, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1905.4583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2693.3994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2329.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2083.0498, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1495.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2151.5229, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2110.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2932.0254, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2347.4199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2840.8059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1730.2534, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.07692307692307693, 'recall': 0.007407407407407408, 'f1': 0.013513513513513514, 'number': 270}, 'P': {'precision': 0.06976744186046512, 'recall': 0.16883116883116883, 'f1': 0.09873417721518986, 'number': 462}, 'overall_precision': 0.06993006993006994, 'overall_recall': 0.1092896174863388, 'overall_f1': 0.08528784648187633, 'overall_accuracy': 0.5771664374140303}
				Near DM Metrics: {'C': {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 111}, 'P': {'precision': 0.08565310492505353, 'recall': 0.21978021978021978, 'f1': 0.12326656394453006, 'number': 182}, 'overall_precision': 0.0847457627118644, 'overall_recall': 0.13651877133105803, 'overall_f1': 0.10457516339869281, 'overall_accuracy': 0.7640165061898212}
				Far DM Metrics: {'C': {'precision': 0.08695652173913043, 'recall': 0.012578616352201259, 'f1': 0.02197802197802198, 'number': 159}, 'P': {'precision': 0.05637982195845697, 'recall': 0.1357142857142857, 'f1': 0.07966457023060795, 'number': 280}, 'overall_precision': 0.05738880918220947, 'overall_recall': 0.09111617312072894, 'overall_f1': 0.07042253521126761, 'overall_accuracy': 0.7021733149931224}
			------------EPOCH 2---------------
Loss:  tensor(1770.3311, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1043.7883, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1263.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1405.2340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1241.6631, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2006.1565, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1002.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1587.9919, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1702.3029, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(902.7034, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1850.0496, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1320.7847, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1342.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1029.9651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1530.5280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1159.2012, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1078.2314, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2051.9875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2086.1694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1512.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2172.3623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1244.1243, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1501.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(556.4668, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(905.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(914.1713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1261.2234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1050.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1024.7864, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1469.2581, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1211.5146, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1691.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2201.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3239.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1990.2051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2460.6516, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(933.7621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1173.8958, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1078.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(695.9501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2229.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1841.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1147.1489, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1488.4503, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1367.6683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(945.4521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1538.1626, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2320.0754, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2000.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1839.2550, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1231.5023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1670.4095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1772.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2618.4509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2011.0160, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2471.6868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1508.7339, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.265625, 'recall': 0.06296296296296296, 'f1': 0.10179640718562873, 'number': 270}, 'P': {'precision': 0.2556213017751479, 'recall': 0.4675324675324675, 'f1': 0.33052792654934965, 'number': 462}, 'overall_precision': 0.2563256325632563, 'overall_recall': 0.31830601092896177, 'overall_f1': 0.28397318708104813, 'overall_accuracy': 0.6477028885832187}
				Near DM Metrics: {'C': {'precision': 0.1111111111111111, 'recall': 0.02702702702702703, 'f1': 0.043478260869565216, 'number': 111}, 'P': {'precision': 0.25936599423631124, 'recall': 0.4945054945054945, 'f1': 0.3402646502835539, 'number': 182}, 'overall_precision': 0.24866310160427807, 'overall_recall': 0.3174061433447099, 'overall_f1': 0.27886056971514245, 'overall_accuracy': 0.8084181568088034}
				Far DM Metrics: {'C': {'precision': 0.27450980392156865, 'recall': 0.0880503144654088, 'f1': 0.13333333333333333, 'number': 159}, 'P': {'precision': 0.25149700598802394, 'recall': 0.45, 'f1': 0.322663252240717, 'number': 280}, 'overall_precision': 0.2536231884057971, 'overall_recall': 0.31890660592255127, 'overall_f1': 0.2825428859737639, 'overall_accuracy': 0.7627510316368639}
			------------EPOCH 3---------------
Loss:  tensor(1476.7350, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(881.3026, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1114.9233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1213.7004, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1060.6790, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1717.7416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(850.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1361.3191, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1397.6353, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(730.1366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1563.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1058.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1118.2130, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(867.8483, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1230.9685, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1067.6901, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(846.8589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1617.3534, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1747.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1304.7399, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1848.4016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1009.4097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1209.6638, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.6678, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(1025.8301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(876.4956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(862.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1237.8921, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(954.0472, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1364.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1932.4886, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2863.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1658.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2207.7002, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(752.0569, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1011.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(934.3684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(606.1895, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1941.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1558.0103, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(933.3792, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1246.4609, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1219.3440, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(832.8894, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1229.0887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1997.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1621.5146, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1623.0415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(993.0707, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1403.4513, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1498.3282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2236.9094, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1622.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2024.1953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1293.0911, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3017241379310345, 'recall': 0.12962962962962962, 'f1': 0.18134715025906734, 'number': 270}, 'P': {'precision': 0.3079625292740047, 'recall': 0.5692640692640693, 'f1': 0.39969604863221886, 'number': 462}, 'overall_precision': 0.30721649484536084, 'overall_recall': 0.40710382513661203, 'overall_f1': 0.3501762632197415, 'overall_accuracy': 0.6720220082530949}
				Near DM Metrics: {'C': {'precision': 0.16071428571428573, 'recall': 0.08108108108108109, 'f1': 0.10778443113772455, 'number': 111}, 'P': {'precision': 0.3180428134556575, 'recall': 0.5714285714285714, 'f1': 0.4086444007858546, 'number': 182}, 'overall_precision': 0.2950391644908616, 'overall_recall': 0.3856655290102389, 'overall_f1': 0.3343195266272189, 'overall_accuracy': 0.8173865199449794}
				Far DM Metrics: {'C': {'precision': 0.3170731707317073, 'recall': 0.16352201257861634, 'f1': 0.21576763485477177, 'number': 159}, 'P': {'precision': 0.301707779886148, 'recall': 0.5678571428571428, 'f1': 0.39405204460966536, 'number': 280}, 'overall_precision': 0.30377668308702793, 'overall_recall': 0.4214123006833713, 'overall_f1': 0.3530534351145038, 'overall_accuracy': 0.7943878954607978}
			------------EPOCH 4---------------
Loss:  tensor(1164.2808, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(678.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(965.1680, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(556.1992, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(1278.1855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1473.8947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(730.5060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1110.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1219.4062, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1921.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1341.5015, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1658.7650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1052.3058, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.36904761904761907, 'recall': 0.22962962962962963, 'f1': 0.2831050228310502, 'number': 270}, 'P': {'precision': 0.44040697674418605, 'recall': 0.6558441558441559, 'f1': 0.5269565217391304, 'number': 462}, 'overall_precision': 0.4264018691588785, 'overall_recall': 0.49863387978142076, 'overall_f1': 0.45969773299748107, 'overall_accuracy': 0.7037689133425035}
				Near DM Metrics: {'C': {'precision': 0.23684210526315788, 'recall': 0.16216216216216217, 'f1': 0.19251336898395724, 'number': 111}, 'P': {'precision': 0.4139194139194139, 'recall': 0.6208791208791209, 'f1': 0.4967032967032967, 'number': 182}, 'overall_precision': 0.3753581661891118, 'overall_recall': 0.447098976109215, 'overall_f1': 0.40809968847352024, 'overall_accuracy': 0.8442916093535076}
				Far DM Metrics: {'C': {'precision': 0.38596491228070173, 'recall': 0.27672955974842767, 'f1': 0.3223443223443223, 'number': 159}, 'P': {'precision': 0.4578313253012048, 'recall': 0.6785714285714286, 'f1': 0.5467625899280576, 'number': 280}, 'overall_precision': 0.44234404536862004, 'overall_recall': 0.5330296127562643, 'overall_f1': 0.4834710743801653, 'overall_accuracy': 0.8217881705639615}
			------------EPOCH 5---------------
Loss:  tensor(938.7667, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(520.2949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(816.7508, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(801.8409, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(687.3541, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(935.2020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(404.6417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(679.4589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(713.7256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(380.3408, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(819.2108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(589.6907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(621.4491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(528.8757, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(707.8909, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(739.8168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(417.8868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(592.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(926.5482, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(780.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1221.4203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(598.3872, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(617.6063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(327.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(530.3994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(527.0511, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(525.2401, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(586.8977, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(592.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(754.0229, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(417.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.2043, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1139.9309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1885.8400, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(854.3259, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1131.7974, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(471.9309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(489.1966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(402.5311, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(358.2922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1227.4249, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(896.6715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(488.0555, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(809.6418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(999.9920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(637.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(576.1984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1299.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(926.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1283.3660, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(554.0236, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(903.5829, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(813.8186, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1354.3088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1011.6285, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1240.1708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(791.5840, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3179190751445087, 'recall': 0.2037037037037037, 'f1': 0.24830699774266365, 'number': 270}, 'P': {'precision': 0.37593984962406013, 'recall': 0.3246753246753247, 'f1': 0.3484320557491289, 'number': 462}, 'overall_precision': 0.3583916083916084, 'overall_recall': 0.28005464480874315, 'overall_f1': 0.31441717791411045, 'overall_accuracy': 0.6029160935350757}
				Near DM Metrics: {'C': {'precision': 0.16279069767441862, 'recall': 0.12612612612612611, 'f1': 0.14213197969543148, 'number': 111}, 'P': {'precision': 0.38461538461538464, 'recall': 0.32967032967032966, 'f1': 0.3550295857988166, 'number': 182}, 'overall_precision': 0.30578512396694213, 'overall_recall': 0.2525597269624573, 'overall_f1': 0.2766355140186916, 'overall_accuracy': 0.8134800550206327}
				Far DM Metrics: {'C': {'precision': 0.3761467889908257, 'recall': 0.2578616352201258, 'f1': 0.30597014925373134, 'number': 159}, 'P': {'precision': 0.37037037037037035, 'recall': 0.32142857142857145, 'f1': 0.3441682600382409, 'number': 280}, 'overall_precision': 0.3721590909090909, 'overall_recall': 0.2984054669703872, 'overall_f1': 0.33122629582806573, 'overall_accuracy': 0.7543878954607978}
			------------EPOCH 6---------------
Loss:  tensor(889.6854, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(366.6739, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(620.5695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(717.1595, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(629.1121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(546.8250, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(311.3983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.3787, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(532.4877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(245.6873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(493.3998, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(355.2017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(406.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(293.6502, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(507.3491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(492.6630, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.9799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(386.3640, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(627.6237, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(449.1755, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1025.1323, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(576.3223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(451.6598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(231.8966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(384.6874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(389.5133, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(359.1491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(433.0108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.5283, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(517.4738, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(297.2497, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(801.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(754.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1394.8132, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(433.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(732.7802, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(324.3487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(289.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(245.0833, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(217.4995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(972.6053, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(562.9280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(277.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(593.6938, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(637.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(336.0604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(683.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(601.5378, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(919.2330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(293.9430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(546.6964, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(483.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(983.9995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(771.1764, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1038.8561, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(514.2930, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.35714285714285715, 'recall': 0.3148148148148148, 'f1': 0.3346456692913386, 'number': 270}, 'P': {'precision': 0.489247311827957, 'recall': 0.5909090909090909, 'f1': 0.5352941176470589, 'number': 462}, 'overall_precision': 0.44974874371859297, 'overall_recall': 0.4890710382513661, 'overall_f1': 0.468586387434555, 'overall_accuracy': 0.6995873452544704}
				Near DM Metrics: {'C': {'precision': 0.29245283018867924, 'recall': 0.27927927927927926, 'f1': 0.2857142857142857, 'number': 111}, 'P': {'precision': 0.47161572052401746, 'recall': 0.5934065934065934, 'f1': 0.5255474452554745, 'number': 182}, 'overall_precision': 0.41492537313432837, 'overall_recall': 0.47440273037542663, 'overall_f1': 0.4426751592356688, 'overall_accuracy': 0.8546905089408529}
				Far DM Metrics: {'C': {'precision': 0.35064935064935066, 'recall': 0.33962264150943394, 'f1': 0.34504792332268375, 'number': 159}, 'P': {'precision': 0.5015197568389058, 'recall': 0.5892857142857143, 'f1': 0.541871921182266, 'number': 280}, 'overall_precision': 0.453416149068323, 'overall_recall': 0.4988610478359909, 'overall_f1': 0.47505422993492413, 'overall_accuracy': 0.8054470426409903}
			------------EPOCH 7---------------
Loss:  tensor(571.3999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(277.3796, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(540.7175, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(706.9521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(370.7804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(281.7462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.1814, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(493.2136, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(290.9827, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(932.0526, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.5855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(377.5870, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(652.8700, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(452.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(240.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(314.8473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(528.8599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1076.9875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(771.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(418.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(192.7215, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(317.7203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.2545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.3297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(327.9556, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(372.6432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(406.8234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(199.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(726.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1023.1803, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1388.6060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(507.0065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.7793, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(227.8868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(186.0644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(149.9760, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(215.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(630.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(411.8977, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.4355, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(413.6584, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(471.9594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(297.9065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.0069, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(592.9172, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(694.6392, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(955.6053, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(342.9794, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(570.1666, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(688.6301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1111.0129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(647.0541, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(891.2203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(400.8800, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.38652482269503546, 'recall': 0.40370370370370373, 'f1': 0.3949275362318841, 'number': 270}, 'P': {'precision': 0.49043478260869566, 'recall': 0.6103896103896104, 'f1': 0.5438765670202507, 'number': 462}, 'overall_precision': 0.456242707117853, 'overall_recall': 0.5341530054644809, 'overall_f1': 0.4921334172435494, 'overall_accuracy': 0.7128473177441541}
				Near DM Metrics: {'C': {'precision': 0.33076923076923076, 'recall': 0.38738738738738737, 'f1': 0.35684647302904565, 'number': 111}, 'P': {'precision': 0.4863636363636364, 'recall': 0.5879120879120879, 'f1': 0.5323383084577115, 'number': 182}, 'overall_precision': 0.42857142857142855, 'overall_recall': 0.5119453924914675, 'overall_f1': 0.4665629860031104, 'overall_accuracy': 0.8554057771664374}
				Far DM Metrics: {'C': {'precision': 0.3793103448275862, 'recall': 0.41509433962264153, 'f1': 0.3963963963963964, 'number': 159}, 'P': {'precision': 0.49295774647887325, 'recall': 0.625, 'f1': 0.5511811023622046, 'number': 280}, 'overall_precision': 0.4555765595463138, 'overall_recall': 0.5489749430523918, 'overall_f1': 0.4979338842975208, 'overall_accuracy': 0.8224484181568088}
			------------EPOCH 8---------------
Loss:  tensor(425.4875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(247.0577, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(298.5560, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(366.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(372.5798, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(267.0151, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(218.1982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.8595, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(273.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.8875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(253.6826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(177.1142, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(234.3454, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.5166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(344.9198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(444.6464, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(256.2538, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(356.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.8746, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.7559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(571.1028, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(382.0118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(351.3989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(199.8017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.5258, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(268.4647, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(212.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(257.4198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(327.4080, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(502.7832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(256.0730, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(758.6793, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(490.7823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(937.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(294.9000, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(738.0356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(154.9595, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.8135, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(125.7330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(137.8283, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(602.5735, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(359.8255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(151.3591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(423.6437, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(344.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.1825, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.7655, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(600.5388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(390.3397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(533.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.7821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(484.2288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(274.5964, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(582.3066, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(381.3629, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(529.2667, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.4200, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3768844221105528, 'recall': 0.2777777777777778, 'f1': 0.3198294243070362, 'number': 270}, 'P': {'precision': 0.4815361890694239, 'recall': 0.7056277056277056, 'f1': 0.5724319578577699, 'number': 462}, 'overall_precision': 0.4577625570776256, 'overall_recall': 0.5478142076502732, 'overall_f1': 0.4987562189054726, 'overall_accuracy': 0.7016231086657496}
				Near DM Metrics: {'C': {'precision': 0.30927835051546393, 'recall': 0.2702702702702703, 'f1': 0.2884615384615385, 'number': 111}, 'P': {'precision': 0.49242424242424243, 'recall': 0.7142857142857143, 'f1': 0.5829596412556054, 'number': 182}, 'overall_precision': 0.44321329639889195, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.4892966360856269, 'overall_accuracy': 0.8585969738651994}
				Far DM Metrics: {'C': {'precision': 0.3629032258064516, 'recall': 0.2830188679245283, 'f1': 0.31802120141342755, 'number': 159}, 'P': {'precision': 0.4745762711864407, 'recall': 0.7, 'f1': 0.5656565656565656, 'number': 280}, 'overall_precision': 0.44878957169459965, 'overall_recall': 0.5489749430523918, 'overall_f1': 0.49385245901639346, 'overall_accuracy': 0.8256396148555708}
			------------EPOCH 9---------------
Loss:  tensor(452.3258, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(247.6309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(287.7289, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.3605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(482.3104, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(321.8062, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(232.9986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(255.4079, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(271.7940, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(223.9023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(331.5124, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(166.7565, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.4840, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(232.5793, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.4465, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.4196, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(222.3878, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.0898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(428.3594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(305.8361, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.6253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(125.7860, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(253.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(183.7147, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(177.9434, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.8991, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(339.9099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(326.6321, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.1898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(773.2170, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(377.8522, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(573.6028, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(184.9728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(402.6405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(109.8220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.6851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(297.9308, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(241.3129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(114.8293, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(242.1786, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(248.0101, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(150.6768, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(139.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(361.3468, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(276.7710, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(430.0719, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(167.6723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(337.6142, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(217.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(506.5304, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(362.6972, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(455.2387, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(154.7459, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4377358490566038, 'recall': 0.42962962962962964, 'f1': 0.43364485981308415, 'number': 270}, 'P': {'precision': 0.5319148936170213, 'recall': 0.7034632034632035, 'f1': 0.6057781919850886, 'number': 462}, 'overall_precision': 0.5034246575342466, 'overall_recall': 0.6024590163934426, 'overall_f1': 0.5485074626865671, 'overall_accuracy': 0.7121870701513068}
				Near DM Metrics: {'C': {'precision': 0.33858267716535434, 'recall': 0.38738738738738737, 'f1': 0.36134453781512604, 'number': 111}, 'P': {'precision': 0.5100401606425703, 'recall': 0.6978021978021978, 'f1': 0.5893271461716938, 'number': 182}, 'overall_precision': 0.4521276595744681, 'overall_recall': 0.5802047781569966, 'overall_f1': 0.508221225710015, 'overall_accuracy': 0.8530398899587345}
				Far DM Metrics: {'C': {'precision': 0.453416149068323, 'recall': 0.4591194968553459, 'f1': 0.45625000000000004, 'number': 159}, 'P': {'precision': 0.5469613259668509, 'recall': 0.7071428571428572, 'f1': 0.616822429906542, 'number': 280}, 'overall_precision': 0.5181644359464627, 'overall_recall': 0.6173120728929385, 'overall_f1': 0.5634095634095634, 'overall_accuracy': 0.8388445667125172}
			------------EPOCH 10---------------
Loss:  tensor(238.7267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(148.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(182.9874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(245.7760, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.9284, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(151.7052, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.9772, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(116.6589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.3342, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(86.7091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(138.3255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.9797, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.6117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.0590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.0591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.0280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(175.5788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(175.4182, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.7135, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(385.7128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.5052, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(184.9913, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.1709, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(233.8633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(295.0340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(284.9934, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(195.4283, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.3259, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.2238, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.2198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(373.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(133.4762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(229.0171, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(209.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(128.3465, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(168.8942, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(551.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(515.9548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.6846, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(722.8523, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(250.0303, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.7253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(270.9851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(351.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(202.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(311.5226, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(153.8937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(344.5613, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(192.0328, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(317.4962, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.1566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(305.7688, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.3979, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.35648148148148145, 'recall': 0.2851851851851852, 'f1': 0.31687242798353915, 'number': 270}, 'P': {'precision': 0.5242165242165242, 'recall': 0.7965367965367965, 'f1': 0.6323024054982819, 'number': 462}, 'overall_precision': 0.48474945533769065, 'overall_recall': 0.6079234972677595, 'overall_f1': 0.5393939393939393, 'overall_accuracy': 0.6997524071526823}
				Near DM Metrics: {'C': {'precision': 0.23809523809523808, 'recall': 0.22522522522522523, 'f1': 0.2314814814814815, 'number': 111}, 'P': {'precision': 0.5179856115107914, 'recall': 0.7912087912087912, 'f1': 0.6260869565217392, 'number': 182}, 'overall_precision': 0.4412532637075718, 'overall_recall': 0.5767918088737202, 'overall_f1': 0.5, 'overall_accuracy': 0.8529298486932599}
				Far DM Metrics: {'C': {'precision': 0.39097744360902253, 'recall': 0.3270440251572327, 'f1': 0.35616438356164387, 'number': 159}, 'P': {'precision': 0.5283018867924528, 'recall': 0.8, 'f1': 0.6363636363636364, 'number': 280}, 'overall_precision': 0.4955116696588869, 'overall_recall': 0.6287015945330297, 'overall_f1': 0.5542168674698795, 'overall_accuracy': 0.8215680880330124}
			------------EPOCH 11---------------
Loss:  tensor(264.8201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(134.7195, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(203.5852, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(239.5602, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(515.3023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(417.0574, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(287.6695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.6204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(572.6726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.5932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(224.4680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.4264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(286.7449, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(127.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(213.4479, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(250.9613, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.7404, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(382.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(324.7904, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(396.4282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.6020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.9551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.6966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(124.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(147.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(155.1866, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.8617, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(196.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(371.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(195.5412, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(307.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(119.1762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(293.5128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(199.9425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(231.8734, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(180.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(136.2190, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(396.1494, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(371.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(145.4512, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.4416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(153.3491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(222.5774, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(213.0694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(448.9603, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(392.9142, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(203.9351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(598.3033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(600.4874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(666.9937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.8268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(358.2489, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(168.7372, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39882697947214074, 'recall': 0.5037037037037037, 'f1': 0.44517184942716853, 'number': 270}, 'P': {'precision': 0.588469184890656, 'recall': 0.6406926406926406, 'f1': 0.6134715025906735, 'number': 462}, 'overall_precision': 0.5118483412322274, 'overall_recall': 0.5901639344262295, 'overall_f1': 0.5482233502538071, 'overall_accuracy': 0.7212654745529573}
				Near DM Metrics: {'C': {'precision': 0.3401360544217687, 'recall': 0.45045045045045046, 'f1': 0.38759689922480617, 'number': 111}, 'P': {'precision': 0.5674418604651162, 'recall': 0.6703296703296703, 'f1': 0.614609571788413, 'number': 182}, 'overall_precision': 0.47513812154696133, 'overall_recall': 0.5870307167235495, 'overall_f1': 0.5251908396946565, 'overall_accuracy': 0.8660247592847318}
				Far DM Metrics: {'C': {'precision': 0.39631336405529954, 'recall': 0.5408805031446541, 'f1': 0.45744680851063835, 'number': 159}, 'P': {'precision': 0.6041666666666666, 'recall': 0.6214285714285714, 'f1': 0.6126760563380282, 'number': 280}, 'overall_precision': 0.5148514851485149, 'overall_recall': 0.592255125284738, 'overall_f1': 0.5508474576271187, 'overall_accuracy': 0.8329023383768913}
			------------EPOCH 12---------------
Loss:  tensor(163.5496, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(181.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.7060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(134.2210, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(139.1475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(126.8953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.1764, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.4500, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.8500, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.2036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.5966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.3787, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.7292, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(95.8167, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(307.3873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(244.6756, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(307.3444, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(807.2998, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(325.2336, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(515.4846, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.1608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(344.8412, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(675.3522, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(301.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(817.9817, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(281.1020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(668.0885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(128.8367, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(532.8542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(256.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(291.9025, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.1915, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(333.4359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.1144, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.0168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.5145, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(166.7230, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.9743, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.0414, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.5711, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.2421, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.7498, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.4437, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(507.8091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(448.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(194.6228, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(454.9604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(659.5455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(576.9718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(378.4181, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(470.6795, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(404.4926, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3435700575815739, 'recall': 0.662962962962963, 'f1': 0.4525916561314791, 'number': 270}, 'P': {'precision': 0.5165876777251185, 'recall': 0.23593073593073594, 'f1': 0.3239227340267459, 'number': 462}, 'overall_precision': 0.39344262295081966, 'overall_recall': 0.39344262295081966, 'overall_f1': 0.3934426229508196, 'overall_accuracy': 0.5911416781292985}
				Near DM Metrics: {'C': {'precision': 0.3056768558951965, 'recall': 0.6306306306306306, 'f1': 0.4117647058823529, 'number': 111}, 'P': {'precision': 0.6323529411764706, 'recall': 0.23626373626373626, 'f1': 0.344, 'number': 182}, 'overall_precision': 0.38047138047138046, 'overall_recall': 0.3856655290102389, 'overall_f1': 0.38305084745762713, 'overall_accuracy': 0.8212379642365887}
				Far DM Metrics: {'C': {'precision': 0.3471337579617834, 'recall': 0.6855345911949685, 'f1': 0.4608879492600423, 'number': 159}, 'P': {'precision': 0.46153846153846156, 'recall': 0.2357142857142857, 'f1': 0.3120567375886525, 'number': 280}, 'overall_precision': 0.38293216630196936, 'overall_recall': 0.39863325740318906, 'overall_f1': 0.390625, 'overall_accuracy': 0.7430536451169188}
			------------EPOCH 13---------------
Loss:  tensor(690.8214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(453.3708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(559.2590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.9425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(323.6483, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(518.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.7774, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(224.0187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.4099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.9731, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(128.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.2527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(108.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.4770, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(193.4959, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(108.9995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(304.8214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(174.8091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(179.3547, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(306.8567, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.1044, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(166.0913, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(112.1454, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(143.1329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(137.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(155.7365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(167.1683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(254.5035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(443.0380, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(519.7698, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1486.4563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(296.9179, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(852.5857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(257.4074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.7131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(175.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(172.9439, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(933.5376, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(482.2401, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.2215, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(393.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(287.2645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.7431, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(266.3936, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.0437, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.7543, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(181.6031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.5094, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(184.6511, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(225.9029, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(126.3169, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.24925373134328357, 'recall': 0.6185185185185185, 'f1': 0.35531914893617017, 'number': 270}, 'P': {'precision': 0.6923076923076923, 'recall': 0.35064935064935066, 'f1': 0.46551724137931033, 'number': 462}, 'overall_precision': 0.3639380530973451, 'overall_recall': 0.4494535519125683, 'overall_f1': 0.402200488997555, 'overall_accuracy': 0.5873452544704264}
				Near DM Metrics: {'C': {'precision': 0.23104693140794225, 'recall': 0.5765765765765766, 'f1': 0.3298969072164948, 'number': 111}, 'P': {'precision': 0.6153846153846154, 'recall': 0.3076923076923077, 'f1': 0.4102564102564103, 'number': 182}, 'overall_precision': 0.32608695652173914, 'overall_recall': 0.40955631399317405, 'overall_f1': 0.3630862329803328, 'overall_accuracy': 0.8162861072902339}
				Far DM Metrics: {'C': {'precision': 0.24641148325358853, 'recall': 0.6477987421383647, 'f1': 0.3570190641247834, 'number': 159}, 'P': {'precision': 0.7412587412587412, 'recall': 0.37857142857142856, 'f1': 0.5011820330969268, 'number': 280}, 'overall_precision': 0.37254901960784315, 'overall_recall': 0.4760820045558087, 'overall_f1': 0.418, 'overall_accuracy': 0.7445942228335626}
			------------EPOCH 14---------------
Loss:  tensor(224.6590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.4220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(234.1828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(306.7364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(401.7478, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(415.6135, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(210.4372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(147.6821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(336.9921, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(112.5985, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(179.2085, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(476.1457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(405.6410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(424.5117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(586.8105, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.4020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(295.5322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.3759, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(519.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(385.6752, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(373.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.6354, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(116.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(101.8451, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(100.6586, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(170.6372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(115.8274, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.0482, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(159.3790, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.6571, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(203.8651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(114.5949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.4703, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.2248, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(156.4517, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.7475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.4865, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.0519, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(310.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(190.1652, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.4925, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.2899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(408.4889, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.0020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(414.8638, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.7997, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(754.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(584.0432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(213.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.9948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(487.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(841.5135, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(383.6434, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(395.7999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(125.8945, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.38235294117647056, 'recall': 0.3851851851851852, 'f1': 0.38376383763837635, 'number': 270}, 'P': {'precision': 0.5795053003533569, 'recall': 0.70995670995671, 'f1': 0.6381322957198443, 'number': 462}, 'overall_precision': 0.5155131264916468, 'overall_recall': 0.5901639344262295, 'overall_f1': 0.5503184713375796, 'overall_accuracy': 0.7346905089408529}
				Near DM Metrics: {'C': {'precision': 0.3, 'recall': 0.35135135135135137, 'f1': 0.3236514522821577, 'number': 111}, 'P': {'precision': 0.5541125541125541, 'recall': 0.7032967032967034, 'f1': 0.6198547215496368, 'number': 182}, 'overall_precision': 0.4626038781163435, 'overall_recall': 0.5699658703071673, 'overall_f1': 0.5107033639143731, 'overall_accuracy': 0.8605777166437414}
				Far DM Metrics: {'C': {'precision': 0.39634146341463417, 'recall': 0.4088050314465409, 'f1': 0.40247678018575855, 'number': 159}, 'P': {'precision': 0.5970149253731343, 'recall': 0.7142857142857143, 'f1': 0.6504065040650405, 'number': 280}, 'overall_precision': 0.531062124248497, 'overall_recall': 0.6036446469248291, 'overall_f1': 0.5650319829424306, 'overall_accuracy': 0.8372489683631362}
			------------EPOCH 15---------------
Loss:  tensor(148.4332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.1306, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.4078, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.3321, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(137.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.9263, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(94.0530, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.4142, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.5525, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.5128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.3341, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.3411, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.7744, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.0202, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.3995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(136.6830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.1138, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(141.8881, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(160.3290, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.0514, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(264.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.6320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(145.2152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(88.8537, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(130.6378, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(425.4853, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(75.0000, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(299.6844, device='cuda:0', grad_fn=<DivBackward0>)
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Loss:  tensor(168.1712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.3252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.7636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.8363, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(184.0967, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.4307, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.6948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.3360, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.5225, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.7333, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39886039886039887, 'recall': 0.5185185185185185, 'f1': 0.45088566827697263, 'number': 270}, 'P': {'precision': 0.5879265091863517, 'recall': 0.48484848484848486, 'f1': 0.5314353499406881, 'number': 462}, 'overall_precision': 0.4972677595628415, 'overall_recall': 0.4972677595628415, 'overall_f1': 0.4972677595628415, 'overall_accuracy': 0.6959559834938102}
				Near DM Metrics: {'C': {'precision': 0.3151515151515151, 'recall': 0.46846846846846846, 'f1': 0.3768115942028985, 'number': 111}, 'P': {'precision': 0.6133333333333333, 'recall': 0.5054945054945055, 'f1': 0.5542168674698795, 'number': 182}, 'overall_precision': 0.45714285714285713, 'overall_recall': 0.49146757679180886, 'overall_f1': 0.4736842105263158, 'overall_accuracy': 0.8538101788170563}
				Far DM Metrics: {'C': {'precision': 0.4230769230769231, 'recall': 0.5534591194968553, 'f1': 0.4795640326975477, 'number': 159}, 'P': {'precision': 0.5714285714285714, 'recall': 0.4714285714285714, 'f1': 0.5166340508806262, 'number': 280}, 'overall_precision': 0.5011389521640092, 'overall_recall': 0.5011389521640092, 'overall_f1': 0.5011389521640092, 'overall_accuracy': 0.8042916093535075}
			------------EPOCH 16---------------
Loss:  tensor(117.7073, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(148.4805, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.8005, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(121.2478, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(135.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.7202, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.2466, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.9940, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.0792, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.2199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.8643, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.2687, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.7100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.6892, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.8243, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(79.3545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.9946, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(152.7948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.8794, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.9783, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.8962, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.3439, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.8654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.9887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.7159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(119.9076, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.0756, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(129.0011, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.7634, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.8559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(94.6136, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.6358, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0481, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.9989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.4754, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.8520, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(96.6502, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.0445, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.2554, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.6568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(95.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.4671, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.9264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(100.6565, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(163.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(79.6130, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.8987, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.5677, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(141.3315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.7003, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.35260115606936415, 'recall': 0.45185185185185184, 'f1': 0.39610389610389607, 'number': 270}, 'P': {'precision': 0.5720338983050848, 'recall': 0.5844155844155844, 'f1': 0.5781584582441114, 'number': 462}, 'overall_precision': 0.4792176039119804, 'overall_recall': 0.5355191256830601, 'overall_f1': 0.5058064516129033, 'overall_accuracy': 0.716808803301238}
				Near DM Metrics: {'C': {'precision': 0.3181818181818182, 'recall': 0.44144144144144143, 'f1': 0.36981132075471695, 'number': 111}, 'P': {'precision': 0.6243093922651933, 'recall': 0.6208791208791209, 'f1': 0.6225895316804407, 'number': 182}, 'overall_precision': 0.4835820895522388, 'overall_recall': 0.552901023890785, 'overall_f1': 0.5159235668789808, 'overall_accuracy': 0.8614580467675378}
				Far DM Metrics: {'C': {'precision': 0.3411214953271028, 'recall': 0.4591194968553459, 'f1': 0.3914209115281501, 'number': 159}, 'P': {'precision': 0.5395189003436426, 'recall': 0.5607142857142857, 'f1': 0.5499124343257442, 'number': 280}, 'overall_precision': 0.45544554455445546, 'overall_recall': 0.5239179954441914, 'overall_f1': 0.4872881355932203, 'overall_accuracy': 0.8204676753782668}
			------------EPOCH 17---------------
Loss:  tensor(84.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.4564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(66.8709, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.9952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.8753, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.1725, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2757, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.7604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.6253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.8201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.6357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.8218, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.7208, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.5125, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(105.1605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.3334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.0746, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.2077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.7912, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.3716, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.9262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.8903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.7701, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.6086, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.8173, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(76.2490, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.4141, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.9557, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.0528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.8853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.9646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.5066, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1569, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(79.2150, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(96.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(76.8033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(95.0620, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.8165, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(109.4442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(86.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(136.6861, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.8064, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(113.2204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.9713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.8743, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0082, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.37305699481865284, 'recall': 0.5333333333333333, 'f1': 0.43902439024390244, 'number': 270}, 'P': {'precision': 0.6148325358851675, 'recall': 0.5562770562770563, 'f1': 0.5840909090909092, 'number': 462}, 'overall_precision': 0.4987562189054726, 'overall_recall': 0.5478142076502732, 'overall_f1': 0.5221354166666666, 'overall_accuracy': 0.7097111416781293}
				Near DM Metrics: {'C': {'precision': 0.3275862068965517, 'recall': 0.5135135135135135, 'f1': 0.4, 'number': 111}, 'P': {'precision': 0.6242424242424243, 'recall': 0.5659340659340659, 'f1': 0.5936599423631124, 'number': 182}, 'overall_precision': 0.471976401179941, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.5063291139240506, 'overall_accuracy': 0.8630536451169188}
				Far DM Metrics: {'C': {'precision': 0.3717948717948718, 'recall': 0.5471698113207547, 'f1': 0.44274809160305345, 'number': 159}, 'P': {'precision': 0.6086956521739131, 'recall': 0.55, 'f1': 0.577861163227017, 'number': 280}, 'overall_precision': 0.4948665297741273, 'overall_recall': 0.5489749430523918, 'overall_f1': 0.5205183585313176, 'overall_accuracy': 0.8245942228335625}
			------------EPOCH 18---------------
Loss:  tensor(60.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.8331, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.1505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.8869, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.9434, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.7244, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.1065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.4610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.7095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5068, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3348, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.3685, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.7120, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.1567, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.0430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.3487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.7286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.6084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.2623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(74.3467, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.3889, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.1512, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.3253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.2920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.9836, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.5262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.1983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.0024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.5288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.0042, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.3713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.6289, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.8599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.5078, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.8830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.6355, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.6114, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.9642, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.1901, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.4262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.4625, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.9052, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.0130, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(79.4398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(124.4801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.3324, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(101.4080, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.6873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.2502, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.2148, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.37922077922077924, 'recall': 0.5407407407407407, 'f1': 0.4458015267175573, 'number': 270}, 'P': {'precision': 0.6155778894472361, 'recall': 0.5303030303030303, 'f1': 0.569767441860465, 'number': 462}, 'overall_precision': 0.49936143039591313, 'overall_recall': 0.5341530054644809, 'overall_f1': 0.5161716171617161, 'overall_accuracy': 0.7048143053645117}
				Near DM Metrics: {'C': {'precision': 0.3393939393939394, 'recall': 0.5045045045045045, 'f1': 0.40579710144927544, 'number': 111}, 'P': {'precision': 0.6125, 'recall': 0.5384615384615384, 'f1': 0.5730994152046783, 'number': 182}, 'overall_precision': 0.47384615384615386, 'overall_recall': 0.5255972696245734, 'overall_f1': 0.4983818770226538, 'overall_accuracy': 0.8620632737276479}
				Far DM Metrics: {'C': {'precision': 0.38961038961038963, 'recall': 0.5660377358490566, 'f1': 0.46153846153846156, 'number': 159}, 'P': {'precision': 0.6176470588235294, 'recall': 0.525, 'f1': 0.5675675675675677, 'number': 280}, 'overall_precision': 0.5053304904051172, 'overall_recall': 0.5398633257403189, 'overall_f1': 0.5220264317180617, 'overall_accuracy': 0.8193672627235213}
			------------EPOCH 19---------------
Loss:  tensor(51.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.4984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.4881, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.1698, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.2060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.4279, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.4075, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.3391, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.8775, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7014, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.4457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.6440, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.5346, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.8099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.8734, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.2841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.7479, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.8664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.5870, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.3178, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.9697, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.2008, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.1476, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.5822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.6324, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(76.9057, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.9051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8740, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.9084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.9591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.3839, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.4844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.0972, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.8572, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.1088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(74.2923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.1549, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(98.1009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.7222, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.4481, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(96.3148, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.8002, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(116.2891, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.2587, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4067796610169492, 'recall': 0.5333333333333333, 'f1': 0.46153846153846156, 'number': 270}, 'P': {'precision': 0.5981087470449172, 'recall': 0.5476190476190477, 'f1': 0.5717514124293785, 'number': 462}, 'overall_precision': 0.510939510939511, 'overall_recall': 0.5423497267759563, 'overall_f1': 0.5261762756792577, 'overall_accuracy': 0.7132874828060523}
				Near DM Metrics: {'C': {'precision': 0.3945578231292517, 'recall': 0.5225225225225225, 'f1': 0.44961240310077516, 'number': 111}, 'P': {'precision': 0.6319018404907976, 'recall': 0.5659340659340659, 'f1': 0.5971014492753622, 'number': 182}, 'overall_precision': 0.5193548387096775, 'overall_recall': 0.5494880546075085, 'overall_f1': 0.5339966832504146, 'overall_accuracy': 0.8678404401650619}
				Far DM Metrics: {'C': {'precision': 0.41545893719806765, 'recall': 0.5408805031446541, 'f1': 0.4699453551912569, 'number': 159}, 'P': {'precision': 0.5769230769230769, 'recall': 0.5357142857142857, 'f1': 0.5555555555555555, 'number': 280}, 'overall_precision': 0.5053533190578159, 'overall_recall': 0.5375854214123007, 'overall_f1': 0.520971302428256, 'overall_accuracy': 0.8282255845942228}
			------------EPOCH 20---------------
Loss:  tensor(48.6363, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.9356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.1070, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.7718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.7033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.9308, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.2443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.9257, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.6786, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.9653, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.0304, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.4545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.3292, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.6220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.7951, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.2184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(66.0811, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.5830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.8319, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.1111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8232, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.9244, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.2010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.2568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(76.9953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.0585, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.1250, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.6140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1606, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.4166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.0863, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.2984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.3172, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.6405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.8347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.4548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.3171, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.7372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(111.2948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.9166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.6637, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(111.5446, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1977, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.37960339943342775, 'recall': 0.4962962962962963, 'f1': 0.4301765650080257, 'number': 270}, 'P': {'precision': 0.6060606060606061, 'recall': 0.5627705627705628, 'f1': 0.5836139169472503, 'number': 462}, 'overall_precision': 0.5038363171355499, 'overall_recall': 0.5382513661202186, 'overall_f1': 0.5204755614266844, 'overall_accuracy': 0.7130123796423659}
				Near DM Metrics: {'C': {'precision': 0.36666666666666664, 'recall': 0.4954954954954955, 'f1': 0.421455938697318, 'number': 111}, 'P': {'precision': 0.6204819277108434, 'recall': 0.5659340659340659, 'f1': 0.5919540229885059, 'number': 182}, 'overall_precision': 0.5, 'overall_recall': 0.5392491467576792, 'overall_f1': 0.5188834154351396, 'overall_accuracy': 0.8633837689133425}
				Far DM Metrics: {'C': {'precision': 0.3891625615763547, 'recall': 0.4968553459119497, 'f1': 0.4364640883977901, 'number': 159}, 'P': {'precision': 0.596958174904943, 'recall': 0.5607142857142857, 'f1': 0.578268876611418, 'number': 280}, 'overall_precision': 0.5064377682403434, 'overall_recall': 0.5375854214123007, 'overall_f1': 0.5215469613259669, 'overall_accuracy': 0.8271801925722145}
			------------EPOCH 21---------------
Loss:  tensor(45.6289, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.8467, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.6713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.8007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.1938, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.7447, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.8544, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.9864, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5299, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.6521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.6949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.4621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2278, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.4868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.0186, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.9769, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(74.7339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.1234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.4008, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.2219, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.0094, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.4031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.0691, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.9906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.6316, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.5264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.9469, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.1396, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(74.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0735, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.1780, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5534, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2600, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.1685, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.9717, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.3514, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.7086, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.1682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.4184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.2526, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.2117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.2822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.3763, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.5124, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.9162, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.6539, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(98.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.9961, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.375, 'recall': 0.5111111111111111, 'f1': 0.43260188087774293, 'number': 270}, 'P': {'precision': 0.5913461538461539, 'recall': 0.5324675324675324, 'f1': 0.5603644646924829, 'number': 462}, 'overall_precision': 0.4897959183673469, 'overall_recall': 0.5245901639344263, 'overall_f1': 0.5065963060686016, 'overall_accuracy': 0.7096011004126548}
				Near DM Metrics: {'C': {'precision': 0.34810126582278483, 'recall': 0.4954954954954955, 'f1': 0.4089219330855019, 'number': 111}, 'P': {'precision': 0.6178343949044586, 'recall': 0.532967032967033, 'f1': 0.5722713864306784, 'number': 182}, 'overall_precision': 0.48253968253968255, 'overall_recall': 0.5187713310580204, 'overall_f1': 0.5, 'overall_accuracy': 0.8581017881705639}
				Far DM Metrics: {'C': {'precision': 0.3952380952380952, 'recall': 0.5220125786163522, 'f1': 0.44986449864498645, 'number': 159}, 'P': {'precision': 0.5752895752895753, 'recall': 0.5321428571428571, 'f1': 0.5528756957328387, 'number': 280}, 'overall_precision': 0.4946695095948827, 'overall_recall': 0.5284738041002278, 'overall_f1': 0.5110132158590309, 'overall_accuracy': 0.8262448418156809}
			------------EPOCH 22---------------
Loss:  tensor(36.0987, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.3185, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.9473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.4580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.3789, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.7632, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.0750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.4246, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.0659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.3277, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.4612, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.4835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.2256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.6252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.5613, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.2405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.8985, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.3539, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.9547, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.9991, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.8422, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.3610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.4542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.1141, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.7746, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.8393, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.0368, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.0170, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2324, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.0624, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.1650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.9703, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1918, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.1714, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.9537, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.2884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.5181, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.7235, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.0862, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.1890, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.7489, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(111.3360, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.6640, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.0712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(66.0727, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.7340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.1103, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4117647058823529, 'recall': 0.5703703703703704, 'f1': 0.4782608695652174, 'number': 270}, 'P': {'precision': 0.5871121718377088, 'recall': 0.5324675324675324, 'f1': 0.5584562996594779, 'number': 462}, 'overall_precision': 0.5044136191677175, 'overall_recall': 0.546448087431694, 'overall_f1': 0.5245901639344261, 'overall_accuracy': 0.7201100412654745}
				Near DM Metrics: {'C': {'precision': 0.3987341772151899, 'recall': 0.5675675675675675, 'f1': 0.4684014869888476, 'number': 111}, 'P': {'precision': 0.6258064516129033, 'recall': 0.532967032967033, 'f1': 0.5756676557863503, 'number': 182}, 'overall_precision': 0.5111821086261981, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.528052805280528, 'overall_accuracy': 0.8681155433287483}
				Far DM Metrics: {'C': {'precision': 0.4212962962962963, 'recall': 0.5723270440251572, 'f1': 0.4853333333333333, 'number': 159}, 'P': {'precision': 0.5643939393939394, 'recall': 0.5321428571428571, 'f1': 0.5477941176470589, 'number': 280}, 'overall_precision': 0.5, 'overall_recall': 0.5466970387243736, 'overall_f1': 0.5223068552774756, 'overall_accuracy': 0.8236588720770289}
			------------EPOCH 23---------------
Loss:  tensor(37.0805, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8913, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.1414, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.6112, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.0907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.8005, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.5432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.5552, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5771, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6653, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0939, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8471, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.5158, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.5606, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.7603, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4229, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.4032, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.8790, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7226, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.3589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4420, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.3002, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.0607, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.5351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.8297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.6671, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.0804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.1461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.8530, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4541, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.9291, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.5899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7681, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.9466, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.4278, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.4765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.8397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.6277, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.8442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.4814, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.5025, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.8188, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.41823056300268097, 'recall': 0.5777777777777777, 'f1': 0.4852255054432348, 'number': 270}, 'P': {'precision': 0.6155717761557178, 'recall': 0.5476190476190477, 'f1': 0.579610538373425, 'number': 462}, 'overall_precision': 0.5216836734693877, 'overall_recall': 0.5587431693989071, 'overall_f1': 0.5395778364116095, 'overall_accuracy': 0.7160385144429161}
				Near DM Metrics: {'C': {'precision': 0.39263803680981596, 'recall': 0.5765765765765766, 'f1': 0.46715328467153283, 'number': 111}, 'P': {'precision': 0.6258064516129033, 'recall': 0.532967032967033, 'f1': 0.5756676557863503, 'number': 182}, 'overall_precision': 0.5062893081761006, 'overall_recall': 0.5494880546075085, 'overall_f1': 0.5270049099836334, 'overall_accuracy': 0.8669601100412655}
				Far DM Metrics: {'C': {'precision': 0.4380952380952381, 'recall': 0.5786163522012578, 'f1': 0.49864498644986444, 'number': 159}, 'P': {'precision': 0.609375, 'recall': 0.5571428571428572, 'f1': 0.582089552238806, 'number': 280}, 'overall_precision': 0.5321888412017167, 'overall_recall': 0.5649202733485194, 'overall_f1': 0.5480662983425415, 'overall_accuracy': 0.8211279229711141}
			------------EPOCH 24---------------
Loss:  tensor(26.9981, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.6737, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8629, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.3316, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.9678, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.7153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.7091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.7705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.1334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2497, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.2376, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.5353, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.1985, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.6310, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.0958, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.7528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.3425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.0276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1847, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.6616, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.8506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2943, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.2712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.8221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.8080, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.4583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8865, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.7587, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2704, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1936, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.7320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.9709, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.1109, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.3156, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.4304, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.7553, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.4364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.4615, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.5520, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.7906, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3963730569948187, 'recall': 0.5666666666666667, 'f1': 0.46646341463414637, 'number': 270}, 'P': {'precision': 0.6136919315403423, 'recall': 0.5432900432900433, 'f1': 0.5763490241102182, 'number': 462}, 'overall_precision': 0.5081761006289308, 'overall_recall': 0.5519125683060109, 'overall_f1': 0.5291421087098888, 'overall_accuracy': 0.7137276478679505}
				Near DM Metrics: {'C': {'precision': 0.38922155688622756, 'recall': 0.5855855855855856, 'f1': 0.4676258992805755, 'number': 111}, 'P': {'precision': 0.6209150326797386, 'recall': 0.521978021978022, 'f1': 0.5671641791044777, 'number': 182}, 'overall_precision': 0.5, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.5220228384991843, 'overall_accuracy': 0.865474552957359}
				Far DM Metrics: {'C': {'precision': 0.4018264840182648, 'recall': 0.5534591194968553, 'f1': 0.4656084656084656, 'number': 159}, 'P': {'precision': 0.609375, 'recall': 0.5571428571428572, 'f1': 0.582089552238806, 'number': 280}, 'overall_precision': 0.5136842105263157, 'overall_recall': 0.5558086560364465, 'overall_f1': 0.5339168490153172, 'overall_accuracy': 0.8194222833562586}
			------------EPOCH 25---------------
Loss:  tensor(30.6074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5344, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.9509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.6068, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.0674, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.4714, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.6238, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.7576, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7092, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.0881, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2107, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5080, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.5955, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.2986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.0559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.5983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7617, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5530, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4494, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.3917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.0845, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5082, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.9362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5724, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.4296, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.5907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7216, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.4071, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.1460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8816, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.1394, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2641, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.0137, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.2134, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.6856, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.7537, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.8025, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.3091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.6191, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.5178, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.3288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.0870, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.0848, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.1555, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7852, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4051948051948052, 'recall': 0.5777777777777777, 'f1': 0.4763358778625954, 'number': 270}, 'P': {'precision': 0.6287878787878788, 'recall': 0.538961038961039, 'f1': 0.5804195804195804, 'number': 462}, 'overall_precision': 0.5185659411011524, 'overall_recall': 0.5532786885245902, 'overall_f1': 0.5353602115003304, 'overall_accuracy': 0.7131774415405777}
				Near DM Metrics: {'C': {'precision': 0.38823529411764707, 'recall': 0.5945945945945946, 'f1': 0.4697508896797153, 'number': 111}, 'P': {'precision': 0.6308724832214765, 'recall': 0.5164835164835165, 'f1': 0.56797583081571, 'number': 182}, 'overall_precision': 0.5015673981191222, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.522875816993464, 'overall_accuracy': 0.8661348005502063}
				Far DM Metrics: {'C': {'precision': 0.4186046511627907, 'recall': 0.5660377358490566, 'f1': 0.4812834224598931, 'number': 159}, 'P': {'precision': 0.6275303643724697, 'recall': 0.5535714285714286, 'f1': 0.5882352941176471, 'number': 280}, 'overall_precision': 0.5303030303030303, 'overall_recall': 0.5580865603644647, 'overall_f1': 0.5438401775804662, 'overall_accuracy': 0.8189821182943604}

	Train size: 80 Test size: 20
Tokenizer: allenai/longformer-base-4096 Model: allenai/longformer-base-4096
Tokenizer: ../home/arg_mining/4epoch_complete/tokenizer/ Model: ../home/arg_mining/4epoch_complete/model/


		-------------RUN 1-----------
			------------EPOCH 1---------------
Loss:  tensor(2577.5806, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1529.7947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1808.3821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1984.5150, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1678.0295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2707.4277, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1355.8979, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2124.5332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2247.8115, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1207.5908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2409.1421, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1804.6750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1822.2332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1417.0195, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2156.5942, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1513.6658, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1316.9399, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2535.7466, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2458.6858, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1897.5610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2521.8682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1559.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1697.5239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(622.2334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1103.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1079.5029, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1555.6648, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1299.0338, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1257.7549, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1899.4633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1497.2898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2055.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2414.2063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3865.4807, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2297.1196, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2784.2209, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1125.3108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1346.3390, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1171.5740, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(767.2462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2601.8774, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2115.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1430.5464, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1822.1147, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1414.0562, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1044.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1759.1384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2418.6877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2196.2910, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2093.4590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1489.2201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2249.1890, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2157.1362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2868.1089, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2181.8101, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2525.3667, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1729.8826, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.023529411764705882, 'recall': 0.007407407407407408, 'f1': 0.011267605633802818, 'number': 270}, 'P': {'precision': 0.1744421906693712, 'recall': 0.18614718614718614, 'f1': 0.1801047120418848, 'number': 462}, 'overall_precision': 0.1522491349480969, 'overall_recall': 0.12021857923497267, 'overall_f1': 0.13435114503816792, 'overall_accuracy': 0.6142503438789546}
				Near DM Metrics: {'C': {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 111}, 'P': {'precision': 0.1377551020408163, 'recall': 0.14835164835164835, 'f1': 0.14285714285714285, 'number': 182}, 'overall_precision': 0.10975609756097561, 'overall_recall': 0.09215017064846416, 'overall_f1': 0.10018552875695733, 'overall_accuracy': 0.7689133425034388}
				Far DM Metrics: {'C': {'precision': 0.02702702702702703, 'recall': 0.012578616352201259, 'f1': 0.01716738197424893, 'number': 159}, 'P': {'precision': 0.19865319865319866, 'recall': 0.21071428571428572, 'f1': 0.2045060658578856, 'number': 280}, 'overall_precision': 0.16442048517520216, 'overall_recall': 0.13895216400911162, 'overall_f1': 0.1506172839506173, 'overall_accuracy': 0.7143878954607978}
			------------EPOCH 2---------------
Loss:  tensor(1888.4009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1110.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1338.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1455.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1264.6992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2009.7831, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(996.9692, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1599.0266, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1684.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(898.6997, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1813.5046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1325.7140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1433.9329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1105.4081, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1671.7561, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1205.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(999.3724, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1781.0908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1996.8403, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1538.1260, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2099.9695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1188.7318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1405.2192, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(920.2737, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(928.0956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1257.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1065.3231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1050.1536, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1601.0771, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1135.8458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1667.9088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2080.2168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3287.0371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1944.3729, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2409.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(903.9261, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1127.3309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1020.5623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(705.7651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2236.9038, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1815.7760, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1168.7330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1581.9623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1255.6016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(891.0157, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1418.9773, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2037.7445, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1885.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1874.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1168.6077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1733.7458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1873.7885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2624.2451, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1842.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2276.8018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1490.8358, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.03908794788273615, 'recall': 0.044444444444444446, 'f1': 0.04159445407279029, 'number': 270}, 'P': {'precision': 0.21380846325167038, 'recall': 0.2077922077922078, 'f1': 0.21075740944017562, 'number': 462}, 'overall_precision': 0.14285714285714285, 'overall_recall': 0.14754098360655737, 'overall_f1': 0.14516129032258066, 'overall_accuracy': 0.6121045392022009}
				Near DM Metrics: {'C': {'precision': 0.017391304347826087, 'recall': 0.018018018018018018, 'f1': 0.017699115044247787, 'number': 111}, 'P': {'precision': 0.1631578947368421, 'recall': 0.17032967032967034, 'f1': 0.16666666666666669, 'number': 182}, 'overall_precision': 0.10819672131147541, 'overall_recall': 0.11262798634812286, 'overall_f1': 0.11036789297658862, 'overall_accuracy': 0.7708940852819808}
				Far DM Metrics: {'C': {'precision': 0.04672897196261682, 'recall': 0.06289308176100629, 'f1': 0.05361930294906166, 'number': 159}, 'P': {'precision': 0.25096525096525096, 'recall': 0.23214285714285715, 'f1': 0.24118738404452691, 'number': 280}, 'overall_precision': 0.15856236786469344, 'overall_recall': 0.17084282460136674, 'overall_f1': 0.16447368421052633, 'overall_accuracy': 0.7474002751031636}
			------------EPOCH 3---------------
Loss:  tensor(1516.8196, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(871.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1134.5914, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1210.1375, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1074.6648, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1639.2261, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(799.2297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1269.8184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1278.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(702.3929, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1419.1696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1029.2948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1135.7339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(858.0748, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1221.9194, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1047.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(792.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1248.9427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1558.5580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1255.3761, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1747.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(957.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1162.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(438.5381, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(752.8398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(787.6200, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(945.4546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(909.3649, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(848.4679, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1348.1257, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(831.9478, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1400.7556, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1751.1642, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2864.6531, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1542.5391, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2007.3208, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(712.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(898.7974, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(842.8591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(569.5826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1852.6409, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1467.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(805.7738, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1184.9281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1123.2673, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(741.3890, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1054.4038, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1584.9739, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1573.9583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1580.8647, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.3943, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1417.0671, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1502.5586, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2038.7238, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1434.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1698.8270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1202.0076, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.10756972111553785, 'recall': 0.1, 'f1': 0.1036468330134357, 'number': 270}, 'P': {'precision': 0.3391472868217054, 'recall': 0.3787878787878788, 'f1': 0.3578732106339468, 'number': 462}, 'overall_precision': 0.2633637548891786, 'overall_recall': 0.27595628415300544, 'overall_f1': 0.2695130086724483, 'overall_accuracy': 0.6514442916093535}
				Near DM Metrics: {'C': {'precision': 0.08536585365853659, 'recall': 0.06306306306306306, 'f1': 0.07253886010362695, 'number': 111}, 'P': {'precision': 0.2731707317073171, 'recall': 0.3076923076923077, 'f1': 0.289405684754522, 'number': 182}, 'overall_precision': 0.21951219512195122, 'overall_recall': 0.2150170648464164, 'overall_f1': 0.21724137931034485, 'overall_accuracy': 0.8024759284731774}
				Far DM Metrics: {'C': {'precision': 0.10638297872340426, 'recall': 0.12578616352201258, 'f1': 0.11527377521613832, 'number': 159}, 'P': {'precision': 0.38263665594855306, 'recall': 0.425, 'f1': 0.4027072758037225, 'number': 280}, 'overall_precision': 0.2785571142284569, 'overall_recall': 0.31662870159453305, 'overall_f1': 0.2963752665245203, 'overall_accuracy': 0.7660522696011004}
			------------EPOCH 4---------------
Loss:  tensor(1289.4893, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(638.4260, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(892.6083, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1018.7942, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(877.5531, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1094.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(582.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(935.9540, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(884.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(488.7568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1025.6072, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(758.2042, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(818.1140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(628.5472, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(870.2356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(841.0410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(656.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(946.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1281.2627, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1063.6443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1358.3993, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(749.8940, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.8042, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(376.6772, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(602.5348, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(662.7654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(667.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(726.8633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(754.3947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1137.7151, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(514.6431, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1110.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1299.8254, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2229.9062, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1052.5035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1490.6627, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(531.3059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(674.1567, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(623.9335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(470.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1458.6790, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1264.5283, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(703.6066, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(972.0742, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(937.6089, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(590.7971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(735.4167, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1231.1783, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1103.3506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1298.6121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(649.7969, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1088.1710, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1088.8683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1600.8414, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(976.3671, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1227.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(887.1890, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.1598360655737705, 'recall': 0.14444444444444443, 'f1': 0.1517509727626459, 'number': 270}, 'P': {'precision': 0.450199203187251, 'recall': 0.48917748917748916, 'f1': 0.4688796680497925, 'number': 462}, 'overall_precision': 0.3552278820375335, 'overall_recall': 0.3620218579234973, 'overall_f1': 0.35859269282814615, 'overall_accuracy': 0.660687757909216}
				Near DM Metrics: {'C': {'precision': 0.15789473684210525, 'recall': 0.13513513513513514, 'f1': 0.14563106796116504, 'number': 111}, 'P': {'precision': 0.39712918660287083, 'recall': 0.45604395604395603, 'f1': 0.42455242966751916, 'number': 182}, 'overall_precision': 0.3223684210526316, 'overall_recall': 0.33447098976109213, 'overall_f1': 0.32830820770519265, 'overall_accuracy': 0.8269050894085282}
				Far DM Metrics: {'C': {'precision': 0.14035087719298245, 'recall': 0.1509433962264151, 'f1': 0.14545454545454545, 'number': 159}, 'P': {'precision': 0.4880546075085324, 'recall': 0.5107142857142857, 'f1': 0.49912739965095987, 'number': 280}, 'overall_precision': 0.3599137931034483, 'overall_recall': 0.3804100227790433, 'overall_f1': 0.3698781838316722, 'overall_accuracy': 0.7838239339752407}
			------------EPOCH 5---------------
Loss:  tensor(917.8815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(452.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(743.5872, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(760.6243, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(808.6507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(778.1674, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(389.2749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(644.6303, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(552.3644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(349.3071, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(716.5588, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(518.8996, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(517.9224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(402.2755, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(629.8102, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(618.5192, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(426.6420, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(565.9075, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1028.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(845.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1021.9617, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(551.0665, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(639.4958, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(273.5373, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(563.7525, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(632.1875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(555.6830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(633.0667, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1006.0312, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1135.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(568.0214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1348.7949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(891.3642, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1798.4386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(799.9519, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(975.5387, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(412.9420, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(535.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(494.9168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(346.9996, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2335.6006, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1570.4126, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(564.3647, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1397.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1352.4982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(713.1964, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(870.9900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1351.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1061.3710, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1291.5470, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(562.6788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(834.4396, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(911.8046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1331.2194, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(928.7480, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1104.6194, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(787.5363, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.14380165289256197, 'recall': 0.32222222222222224, 'f1': 0.19885714285714284, 'number': 270}, 'P': {'precision': 0.34256055363321797, 'recall': 0.21428571428571427, 'f1': 0.2636484687083888, 'number': 462}, 'overall_precision': 0.2080536912751678, 'overall_recall': 0.2540983606557377, 'overall_f1': 0.22878228782287824, 'overall_accuracy': 0.6126547455295736}
				Near DM Metrics: {'C': {'precision': 0.1566265060240964, 'recall': 0.35135135135135137, 'f1': 0.21666666666666667, 'number': 111}, 'P': {'precision': 0.3620689655172414, 'recall': 0.23076923076923078, 'f1': 0.28187919463087246, 'number': 182}, 'overall_precision': 0.2219178082191781, 'overall_recall': 0.2764505119453925, 'overall_f1': 0.2462006079027356, 'overall_accuracy': 0.8019807427785419}
				Far DM Metrics: {'C': {'precision': 0.12698412698412698, 'recall': 0.3018867924528302, 'f1': 0.17877094972067037, 'number': 159}, 'P': {'precision': 0.32947976878612717, 'recall': 0.20357142857142857, 'f1': 0.25165562913907286, 'number': 280}, 'overall_precision': 0.19056261343012704, 'overall_recall': 0.23917995444191345, 'overall_f1': 0.21212121212121215, 'overall_accuracy': 0.7259972489683632}
			------------EPOCH 6---------------
Loss:  tensor(919.4655, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(492.4187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(695.4398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(665.7676, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(767.4757, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(964.3446, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(354.7968, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(583.2733, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(507.8781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(445.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1029.2664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(793.6995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(743.8528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(501.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(686.1589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(645.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(504.6647, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1156.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(978.6365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(845.7262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1019.3813, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(711.2758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(745.5265, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.2440, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(432.4507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(450.2374, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(442.3993, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(548.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(524.1917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(695.3160, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.8906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(816.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(921.6394, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1505.9771, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(621.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1064.7701, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(373.0572, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(430.9551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(378.5891, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(305.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(895.6018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(690.1995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(391.6967, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(701.6990, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(744.8510, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(328.8251, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(424.0661, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(697.8589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(811.4255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(879.6277, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(356.5273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(640.1521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(658.7416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1158.6226, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(664.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(703.9055, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(391.5580, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.33941605839416056, 'recall': 0.34444444444444444, 'f1': 0.34191176470588236, 'number': 270}, 'P': {'precision': 0.48596491228070177, 'recall': 0.5995670995670995, 'f1': 0.5368217054263565, 'number': 462}, 'overall_precision': 0.43838862559241704, 'overall_recall': 0.505464480874317, 'overall_f1': 0.4695431472081218, 'overall_accuracy': 0.7124071526822559}
				Near DM Metrics: {'C': {'precision': 0.26229508196721313, 'recall': 0.2882882882882883, 'f1': 0.27467811158798283, 'number': 111}, 'P': {'precision': 0.46153846153846156, 'recall': 0.5934065934065934, 'f1': 0.5192307692307693, 'number': 182}, 'overall_precision': 0.39325842696629215, 'overall_recall': 0.4778156996587031, 'overall_f1': 0.43143297380585516, 'overall_accuracy': 0.8529298486932599}
				Far DM Metrics: {'C': {'precision': 0.3407821229050279, 'recall': 0.3836477987421384, 'f1': 0.36094674556213013, 'number': 159}, 'P': {'precision': 0.5029761904761905, 'recall': 0.6035714285714285, 'f1': 0.5487012987012988, 'number': 280}, 'overall_precision': 0.44660194174757284, 'overall_recall': 0.5239179954441914, 'overall_f1': 0.48218029350104824, 'overall_accuracy': 0.8167812929848693}
			------------EPOCH 7---------------
Loss:  tensor(764.4604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(370.8896, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(468.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(547.5457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(494.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(404.0132, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.7783, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(308.8237, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(264.6900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.6853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(423.6093, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(302.9018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(207.5664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.2316, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(365.2018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(170.6633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(450.5414, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(386.4356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(509.1025, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(756.5214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(476.2224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(383.4819, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(198.9229, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(281.8329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(357.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(264.0332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(382.4518, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(362.4887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(469.5237, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(162.8905, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(607.8522, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(429.4749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(818.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.4705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.8464, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.9633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(207.0021, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(209.3467, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(657.0458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(471.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(332.8978, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(566.8475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(461.2375, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(591.7134, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(474.4895, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(649.3282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(329.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(525.7282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(473.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(820.3765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(544.2792, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(526.4932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.3887, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.36764705882352944, 'recall': 0.18518518518518517, 'f1': 0.24630541871921183, 'number': 270}, 'P': {'precision': 0.5131375579598145, 'recall': 0.7186147186147186, 'f1': 0.5987376014427411, 'number': 462}, 'overall_precision': 0.4878671775223499, 'overall_recall': 0.5218579234972678, 'overall_f1': 0.5042904290429043, 'overall_accuracy': 0.7093259972489684}
				Near DM Metrics: {'C': {'precision': 0.2571428571428571, 'recall': 0.16216216216216217, 'f1': 0.1988950276243094, 'number': 111}, 'P': {'precision': 0.467680608365019, 'recall': 0.6758241758241759, 'f1': 0.5528089887640449, 'number': 182}, 'overall_precision': 0.42342342342342343, 'overall_recall': 0.4812286689419795, 'overall_f1': 0.4504792332268371, 'overall_accuracy': 0.8599174690508941}
				Far DM Metrics: {'C': {'precision': 0.3516483516483517, 'recall': 0.20125786163522014, 'f1': 0.256, 'number': 159}, 'P': {'precision': 0.5442708333333334, 'recall': 0.7464285714285714, 'f1': 0.6295180722891566, 'number': 280}, 'overall_precision': 0.5073684210526316, 'overall_recall': 0.5489749430523918, 'overall_f1': 0.5273522975929978, 'overall_accuracy': 0.8234387895460797}
			------------EPOCH 8---------------
Loss:  tensor(750.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(361.6165, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(360.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(600.8712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(544.8994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(365.5761, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(181.1017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(286.1856, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(194.6012, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(134.0384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.9399, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(159.6791, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(163.5544, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.5721, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(222.8564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(194.1202, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(131.4211, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(321.2361, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(250.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(335.5211, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(562.7667, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(345.2460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(424.4357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(227.4449, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(385.1502, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(341.7542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(283.3339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(482.8869, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(355.9270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(516.4683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.3617, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(493.7670, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(233.9799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(703.6239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.3937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.3396, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(107.2608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.7407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(126.0678, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.8748, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(404.3788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(286.8799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(148.6366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.9727, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(248.9255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(134.4719, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(183.7004, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.4965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(357.2299, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(474.6782, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.1374, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(379.0357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(361.5822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(849.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.2646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(563.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.6774, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.33707865168539325, 'recall': 0.2222222222222222, 'f1': 0.2678571428571428, 'number': 270}, 'P': {'precision': 0.48468708388814913, 'recall': 0.7878787878787878, 'f1': 0.6001648804616653, 'number': 462}, 'overall_precision': 0.4564047362755651, 'overall_recall': 0.5792349726775956, 'overall_f1': 0.5105358217940998, 'overall_accuracy': 0.6816506189821183}
				Near DM Metrics: {'C': {'precision': 0.2696629213483146, 'recall': 0.21621621621621623, 'f1': 0.24, 'number': 111}, 'P': {'precision': 0.4444444444444444, 'recall': 0.7472527472527473, 'f1': 0.5573770491803278, 'number': 182}, 'overall_precision': 0.4050632911392405, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.46511627906976744, 'overall_accuracy': 0.8340577716643741}
				Far DM Metrics: {'C': {'precision': 0.3157894736842105, 'recall': 0.22641509433962265, 'f1': 0.2637362637362637, 'number': 159}, 'P': {'precision': 0.5123595505617977, 'recall': 0.8142857142857143, 'f1': 0.6289655172413793, 'number': 280}, 'overall_precision': 0.47227191413237923, 'overall_recall': 0.6013667425968109, 'overall_f1': 0.529058116232465, 'overall_accuracy': 0.8171664374140303}
			------------EPOCH 9---------------
Loss:  tensor(449.9644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.7881, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(424.0529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(462.9473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(517.0466, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.4787, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(259.7788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(314.3876, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(268.4517, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(158.3651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(231.5652, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.9830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.8970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(111.7804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(179.0030, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(94.1927, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(155.1391, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(171.3254, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(230.7499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(240.4926, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(156.0902, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(251.7704, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.6929, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.9343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(163.9140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.6173, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(263.1979, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(383.2232, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(414.8180, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(153.6106, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(502.9632, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(905.4368, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1857.4990, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(583.5005, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(822.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(438.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(348.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(190.0007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(254.8952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(635.6229, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(363.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(328.5988, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.3705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.5558, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(125.5026, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.9377, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(152.3745, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(202.1908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(151.8577, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.8519, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(273.0501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(510.5355, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(242.8938, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(219.4581, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.3012, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.33548387096774196, 'recall': 0.1925925925925926, 'f1': 0.24470588235294122, 'number': 270}, 'P': {'precision': 0.3505402160864346, 'recall': 0.6320346320346321, 'f1': 0.45096525096525103, 'number': 462}, 'overall_precision': 0.3481781376518219, 'overall_recall': 0.46994535519125685, 'overall_f1': 0.4, 'overall_accuracy': 0.6426960110041265}
				Near DM Metrics: {'C': {'precision': 0.2054794520547945, 'recall': 0.13513513513513514, 'f1': 0.16304347826086957, 'number': 111}, 'P': {'precision': 0.3516819571865443, 'recall': 0.6318681318681318, 'f1': 0.4518664047151277, 'number': 182}, 'overall_precision': 0.325, 'overall_recall': 0.44368600682593856, 'overall_f1': 0.3751803751803752, 'overall_accuracy': 0.8327372764786795}
				Far DM Metrics: {'C': {'precision': 0.3274336283185841, 'recall': 0.23270440251572327, 'f1': 0.27205882352941174, 'number': 159}, 'P': {'precision': 0.34980237154150196, 'recall': 0.6321428571428571, 'f1': 0.45038167938931295, 'number': 280}, 'overall_precision': 0.345718901453958, 'overall_recall': 0.4874715261958998, 'overall_f1': 0.4045368620037807, 'overall_accuracy': 0.780302613480055}
			------------EPOCH 10---------------
Loss:  tensor(492.7422, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.5658, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(363.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(329.3499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(616.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(525.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.4380, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(409.7341, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(651.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.9902, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(374.8987, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(214.1487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(343.4800, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.1779, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(591.7635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(639.8040, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(418.0424, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(380.3907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(677.1553, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(567.2935, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(843.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(458.0070, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(632.8798, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.8089, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.3347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(343.9540, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(160.4120, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(348.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.5067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(316.7409, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.6343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(314.8849, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(397.4148, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(545.4901, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(181.0599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(419.7703, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.1298, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.1024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.5314, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(192.7816, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(928.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(675.9197, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(592.8245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(831.0941, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(481.5564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(224.3048, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(441.6755, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(874.3544, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(563.7356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(729.9888, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(406.7501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1044.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(447.3276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(793.3256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(524.9343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(551.8702, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(207.0293, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.43790849673202614, 'recall': 0.24814814814814815, 'f1': 0.31678486997635935, 'number': 270}, 'P': {'precision': 0.575503355704698, 'recall': 0.7424242424242424, 'f1': 0.6483931947069943, 'number': 462}, 'overall_precision': 0.5473965287049399, 'overall_recall': 0.5601092896174863, 'overall_f1': 0.5536799459824443, 'overall_accuracy': 0.7252269601100413}
				Near DM Metrics: {'C': {'precision': 0.4225352112676056, 'recall': 0.2702702702702703, 'f1': 0.3296703296703297, 'number': 111}, 'P': {'precision': 0.5630252100840336, 'recall': 0.7362637362637363, 'f1': 0.638095238095238, 'number': 182}, 'overall_precision': 0.5307443365695793, 'overall_recall': 0.5597269624573379, 'overall_f1': 0.5448504983388704, 'overall_accuracy': 0.8761485557083907}
				Far DM Metrics: {'C': {'precision': 0.3854166666666667, 'recall': 0.23270440251572327, 'f1': 0.2901960784313726, 'number': 159}, 'P': {'precision': 0.5837988826815642, 'recall': 0.7464285714285714, 'f1': 0.6551724137931035, 'number': 280}, 'overall_precision': 0.5418502202643172, 'overall_recall': 0.5603644646924829, 'overall_f1': 0.5509518477043673, 'overall_accuracy': 0.8327372764786795}
			------------EPOCH 11---------------
Loss:  tensor(232.4403, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.4023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(282.6682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(211.3931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(321., device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(170.0534, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(124.6544, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.6057, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.4566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.2422, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(126.6723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.1328, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.3801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.4072, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.5075, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.8248, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(388.1928, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(742.6685, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(611.8350, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(429.5900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(561.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.7335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(467.9628, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(101.0949, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(179.4332, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(330.5693, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(229.3527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(357.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(211.1097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(460.2166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(183.1131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(411.1826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(582.6545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(944.8994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(302.5991, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1037.1340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.3238, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(373.5911, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(320.9917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(136.3575, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(323.2861, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(390.9509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(195.1317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(267.3608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(399.6882, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(112.6258, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(356.0950, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.2114, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.4049, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.5723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(377.2509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.1318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(306.6618, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.2026, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.3073, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.7255, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.2033898305084746, 'recall': 0.08888888888888889, 'f1': 0.12371134020618556, 'number': 270}, 'P': {'precision': 0.44536082474226807, 'recall': 0.4675324675324675, 'f1': 0.4561774023231257, 'number': 462}, 'overall_precision': 0.39800995024875624, 'overall_recall': 0.32786885245901637, 'overall_f1': 0.3595505617977528, 'overall_accuracy': 0.6331774415405778}
				Near DM Metrics: {'C': {'precision': 0.2608695652173913, 'recall': 0.10810810810810811, 'f1': 0.15286624203821655, 'number': 111}, 'P': {'precision': 0.4739583333333333, 'recall': 0.5, 'f1': 0.48663101604278075, 'number': 182}, 'overall_precision': 0.4327731092436975, 'overall_recall': 0.3515358361774744, 'overall_f1': 0.38794726930320156, 'overall_accuracy': 0.841980742778542}
				Far DM Metrics: {'C': {'precision': 0.16666666666666666, 'recall': 0.07547169811320754, 'f1': 0.10389610389610389, 'number': 159}, 'P': {'precision': 0.42662116040955633, 'recall': 0.44642857142857145, 'f1': 0.4363001745200698, 'number': 280}, 'overall_precision': 0.37534246575342467, 'overall_recall': 0.3120728929384966, 'overall_f1': 0.3407960199004975, 'overall_accuracy': 0.7637414030261348}
			------------EPOCH 12---------------
Loss:  tensor(358.6944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(243.2347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(399.7046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(322.1957, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.8007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(324.5615, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.5701, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.2331, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(299.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.9048, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(451.9992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(282.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.9297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.4406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(227.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(109.2223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(183.4067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(199.0994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(275.4096, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.5780, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(182.4968, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.9694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(96.9432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.7016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.0313, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(254.5690, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.2659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(308.6069, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(127.4882, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(378.6983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(153.4739, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.1731, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.4905, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.2436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.3416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.6143, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(170.1153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.6884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.9883, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(401.5415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(259.6588, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.8555, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(311.5259, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.2546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(588.6454, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(251.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(643.8356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(348.9846, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(516.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.7837, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(543.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.3309, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.44680851063829785, 'recall': 0.5444444444444444, 'f1': 0.49081803005008345, 'number': 270}, 'P': {'precision': 0.593320235756385, 'recall': 0.6536796536796536, 'f1': 0.6220391349124613, 'number': 462}, 'overall_precision': 0.535799522673031, 'overall_recall': 0.6133879781420765, 'overall_f1': 0.5719745222929935, 'overall_accuracy': 0.7411829436038514}
				Near DM Metrics: {'C': {'precision': 0.38461538461538464, 'recall': 0.4954954954954955, 'f1': 0.43307086614173235, 'number': 111}, 'P': {'precision': 0.5916230366492147, 'recall': 0.6208791208791209, 'f1': 0.6058981233243969, 'number': 182}, 'overall_precision': 0.5029940119760479, 'overall_recall': 0.5733788395904437, 'overall_f1': 0.5358851674641147, 'overall_accuracy': 0.8769188445667125}
				Far DM Metrics: {'C': {'precision': 0.4742268041237113, 'recall': 0.5786163522012578, 'f1': 0.5212464589235127, 'number': 159}, 'P': {'precision': 0.5943396226415094, 'recall': 0.675, 'f1': 0.6321070234113713, 'number': 280}, 'overall_precision': 0.548828125, 'overall_recall': 0.6400911161731208, 'overall_f1': 0.5909568874868559, 'overall_accuracy': 0.8446217331499313}
			------------EPOCH 13---------------
Loss:  tensor(215.2214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.4965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.2353, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(209.7694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(270.9286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.7923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.5243, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.6580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.8439, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.3621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.5103, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(105.5058, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.2494, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.7124, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(225.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(206.1431, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(190.9264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(834.6737, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(412.7601, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(248.4823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(235.6458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(807.4326, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(923.0374, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1234.7722, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1084.9969, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(522.1415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(759.2529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(443.3505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(701.8324, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(207.3631, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1003.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(214.6006, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.1539, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.5263, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.0672, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.6677, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(143.8313, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.4349, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.3910, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.0527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.5986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(126.9163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(230.8114, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(469.9016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(343.3932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(243.8253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(582.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(525.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(830.0723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(638.5054, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(584.9244, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(603.1246, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.2734375, 'recall': 0.7777777777777778, 'f1': 0.4046242774566474, 'number': 270}, 'P': {'precision': 0.7083333333333334, 'recall': 0.33116883116883117, 'f1': 0.4513274336283186, 'number': 462}, 'overall_precision': 0.36890243902439024, 'overall_recall': 0.4959016393442623, 'overall_f1': 0.4230769230769231, 'overall_accuracy': 0.5622008253094911}
				Near DM Metrics: {'C': {'precision': 0.2606060606060606, 'recall': 0.7747747747747747, 'f1': 0.3900226757369615, 'number': 111}, 'P': {'precision': 0.6363636363636364, 'recall': 0.2692307692307692, 'f1': 0.37837837837837834, 'number': 182}, 'overall_precision': 0.3316953316953317, 'overall_recall': 0.46075085324232085, 'overall_f1': 0.3857142857142858, 'overall_accuracy': 0.8040165061898212}
				Far DM Metrics: {'C': {'precision': 0.26956521739130435, 'recall': 0.779874213836478, 'f1': 0.4006462035541195, 'number': 159}, 'P': {'precision': 0.7482014388489209, 'recall': 0.37142857142857144, 'f1': 0.49642004773269693, 'number': 280}, 'overall_precision': 0.3806343906510851, 'overall_recall': 0.5193621867881549, 'overall_f1': 0.4393063583815029, 'overall_accuracy': 0.7358459422283357}
			------------EPOCH 14---------------
Loss:  tensor(680.8282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(518.2867, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(763.1785, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(546.9575, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(598.4373, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(652.1661, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(297.9749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.6156, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.6520, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.5427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(250.7383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.5864, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(221.7965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(349.0616, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(474.0268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(230.9268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(163.8956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(221.4903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.8168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.8372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.0246, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(239.0154, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.2914, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.8193, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(295.7343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.0737, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(265.9221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(210.8665, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(427.3038, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(193.2222, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(294.0568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.9111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(860.9865, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(299.9077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(549.3635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(196.3391, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.7401, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(251.9574, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.3963, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(912.4878, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(622.9260, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(152.2002, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(525.1805, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(520.0497, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(143.0454, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(311.3337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(413.4041, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(431.2292, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(214.9795, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(405.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(293.5681, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.9915, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.6661, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(282.1084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(98.3246, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.37168141592920356, 'recall': 0.6222222222222222, 'f1': 0.4653739612188366, 'number': 270}, 'P': {'precision': 0.611764705882353, 'recall': 0.45021645021645024, 'f1': 0.5187032418952618, 'number': 462}, 'overall_precision': 0.47474747474747475, 'overall_recall': 0.5136612021857924, 'overall_f1': 0.49343832020997375, 'overall_accuracy': 0.6669601100412654}
				Near DM Metrics: {'C': {'precision': 0.328125, 'recall': 0.5675675675675675, 'f1': 0.4158415841584159, 'number': 111}, 'P': {'precision': 0.5939849624060151, 'recall': 0.4340659340659341, 'f1': 0.5015873015873016, 'number': 182}, 'overall_precision': 0.4369230769230769, 'overall_recall': 0.48464163822525597, 'overall_f1': 0.459546925566343, 'overall_accuracy': 0.8394497936726273}
				Far DM Metrics: {'C': {'precision': 0.40384615384615385, 'recall': 0.660377358490566, 'f1': 0.5011933174224343, 'number': 159}, 'P': {'precision': 0.6231884057971014, 'recall': 0.4607142857142857, 'f1': 0.5297741273100616, 'number': 280}, 'overall_precision': 0.5010706638115632, 'overall_recall': 0.5330296127562643, 'overall_f1': 0.5165562913907286, 'overall_accuracy': 0.7898211829436038}
			------------EPOCH 15---------------
Loss:  tensor(116.0984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(94.3273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.4490, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(210.7644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.8202, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.6511, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.6955, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.0612, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.7328, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(105.1824, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(191.0587, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(127.1063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(223.2316, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.1799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.9227, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(311.8601, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.4266, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.1166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(349.8646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(330.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.8580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.3044, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(214.4855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(189.4109, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(221.8708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.5654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(158.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(110.6407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(163.6007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.1152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.8302, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.2028, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.4445, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.7294, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.5448, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.9529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.6458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.1788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.5608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.2286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(79.9256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.6785, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2327, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.7236, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.2726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.4992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.9133, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.0322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(166.6659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(90.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(128.6436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.8956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.8294, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3783783783783784, 'recall': 0.4666666666666667, 'f1': 0.417910447761194, 'number': 270}, 'P': {'precision': 0.6191369606003753, 'recall': 0.7142857142857143, 'f1': 0.6633165829145728, 'number': 462}, 'overall_precision': 0.5265588914549654, 'overall_recall': 0.6229508196721312, 'overall_f1': 0.5707133917396747, 'overall_accuracy': 0.7294085281980742}
				Near DM Metrics: {'C': {'precision': 0.3194444444444444, 'recall': 0.4144144144144144, 'f1': 0.3607843137254902, 'number': 111}, 'P': {'precision': 0.6176470588235294, 'recall': 0.6923076923076923, 'f1': 0.6528497409326426, 'number': 182}, 'overall_precision': 0.4942528735632184, 'overall_recall': 0.5870307167235495, 'overall_f1': 0.5366614664586583, 'overall_accuracy': 0.864484181568088}
				Far DM Metrics: {'C': {'precision': 0.42328042328042326, 'recall': 0.5031446540880503, 'f1': 0.45977011494252873, 'number': 159}, 'P': {'precision': 0.6200607902735562, 'recall': 0.7285714285714285, 'f1': 0.6699507389162562, 'number': 280}, 'overall_precision': 0.5482625482625483, 'overall_recall': 0.6469248291571754, 'overall_f1': 0.593521421107628, 'overall_accuracy': 0.8445116918844566}
			------------EPOCH 16---------------
Loss:  tensor(94.8835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.1877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.5521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.3680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(141.0952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0910, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.9906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.9593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.5509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.8300, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.2980, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.5182, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.4157, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.2359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.1482, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.8826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.6183, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.5548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(73.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.1402, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.4855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.5884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.7373, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.6913, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.1950, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(102.1216, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.6956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.5345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.9383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(143.7825, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.8701, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.2242, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.7022, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.5686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.6543, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.6705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.0123, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.0565, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.9031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(66.2277, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.6902, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4042, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.2082, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.9542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.3933, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.5698, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.0500, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.3471, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.6706, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.7886, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.3584, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5759, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4108761329305136, 'recall': 0.5037037037037037, 'f1': 0.4525790349417637, 'number': 270}, 'P': {'precision': 0.6191536748329621, 'recall': 0.6017316017316018, 'f1': 0.610318331503842, 'number': 462}, 'overall_precision': 0.5307692307692308, 'overall_recall': 0.5655737704918032, 'overall_f1': 0.5476190476190476, 'overall_accuracy': 0.7146629986244842}
				Near DM Metrics: {'C': {'precision': 0.3382352941176471, 'recall': 0.4144144144144144, 'f1': 0.3724696356275303, 'number': 111}, 'P': {'precision': 0.6705882352941176, 'recall': 0.6263736263736264, 'f1': 0.6477272727272727, 'number': 182}, 'overall_precision': 0.5228758169934641, 'overall_recall': 0.5460750853242321, 'overall_f1': 0.5342237061769617, 'overall_accuracy': 0.8572214580467675}
				Far DM Metrics: {'C': {'precision': 0.46153846153846156, 'recall': 0.5660377358490566, 'f1': 0.5084745762711864, 'number': 159}, 'P': {'precision': 0.5878136200716846, 'recall': 0.5857142857142857, 'f1': 0.5867620751341682, 'number': 280}, 'overall_precision': 0.5358649789029536, 'overall_recall': 0.5785876993166287, 'overall_f1': 0.5564074479737131, 'overall_accuracy': 0.8163961485557084}
			------------EPOCH 17---------------
Loss:  tensor(38.4012, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.2668, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.9683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.3908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.8966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.8033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.4777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7625, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.2132, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.4855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5665, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2480, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.0031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.3435, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.4989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.0440, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.2784, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.8067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.4224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.9868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.7204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.2091, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.1278, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.2622, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.2832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.6829, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.2582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(110.3495, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.9857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.6718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5519, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5688, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7237, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.1507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.3264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.3131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8299, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.9020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8338, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.0281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.3026, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.5144, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.0267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.4828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(105.9388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.7184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7168, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40168539325842695, 'recall': 0.5296296296296297, 'f1': 0.4568690095846645, 'number': 270}, 'P': {'precision': 0.6153846153846154, 'recall': 0.5714285714285714, 'f1': 0.5925925925925927, 'number': 462}, 'overall_precision': 0.5184713375796178, 'overall_recall': 0.5560109289617486, 'overall_f1': 0.5365853658536586, 'overall_accuracy': 0.7074552957359009}
				Near DM Metrics: {'C': {'precision': 0.3443708609271523, 'recall': 0.46846846846846846, 'f1': 0.3969465648854962, 'number': 111}, 'P': {'precision': 0.6503067484662577, 'recall': 0.5824175824175825, 'f1': 0.6144927536231884, 'number': 182}, 'overall_precision': 0.5031847133757962, 'overall_recall': 0.5392491467576792, 'overall_f1': 0.5205930807248764, 'overall_accuracy': 0.8529298486932599}
				Far DM Metrics: {'C': {'precision': 0.44390243902439025, 'recall': 0.5723270440251572, 'f1': 0.5, 'number': 159}, 'P': {'precision': 0.5939849624060151, 'recall': 0.5642857142857143, 'f1': 0.5787545787545788, 'number': 280}, 'overall_precision': 0.5286624203821656, 'overall_recall': 0.5671981776765376, 'overall_f1': 0.5472527472527473, 'overall_accuracy': 0.8134250343878955}
			------------EPOCH 18---------------
Loss:  tensor(26.3343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.6663, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.4323, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.1597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.5129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.7559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.6867, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.8735, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.1994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.2626, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.6213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.8971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.3388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.4219, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.8590, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.0317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.4474, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7796, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.6908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4149, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.3527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.7898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.8934, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.3984, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.8381, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.2386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.7461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.1302, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.8347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.4572, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.6097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4048, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.3007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.6106, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4845, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.6153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.9697, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5818, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.7128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.8715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.9821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.0794, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.4430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.9931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.0134, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.0297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.0839, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.5671, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2814, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4139941690962099, 'recall': 0.5259259259259259, 'f1': 0.4632952691680261, 'number': 270}, 'P': {'precision': 0.6333333333333333, 'recall': 0.6168831168831169, 'f1': 0.625, 'number': 462}, 'overall_precision': 0.5384615384615384, 'overall_recall': 0.5833333333333334, 'overall_f1': 0.5599999999999999, 'overall_accuracy': 0.7214855570839065}
				Near DM Metrics: {'C': {'precision': 0.35664335664335667, 'recall': 0.4594594594594595, 'f1': 0.40157480314960636, 'number': 111}, 'P': {'precision': 0.6802325581395349, 'recall': 0.6428571428571429, 'f1': 0.6610169491525424, 'number': 182}, 'overall_precision': 0.5333333333333333, 'overall_recall': 0.5733788395904437, 'overall_f1': 0.5526315789473684, 'overall_accuracy': 0.8581017881705639}
				Far DM Metrics: {'C': {'precision': 0.455, 'recall': 0.5723270440251572, 'f1': 0.5069637883008357, 'number': 159}, 'P': {'precision': 0.60431654676259, 'recall': 0.6, 'f1': 0.6021505376344086, 'number': 280}, 'overall_precision': 0.5418410041841004, 'overall_recall': 0.5899772209567198, 'overall_f1': 0.564885496183206, 'overall_accuracy': 0.8262448418156809}
			------------EPOCH 19---------------
Loss:  tensor(21.4596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.2065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5625, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.6936, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4323, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.9730, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.6798, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.6071, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5465, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.6219, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.1777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.7427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.1905, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3327, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.5087, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.7433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.9804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.6581, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5537, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.0005, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.6011, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.2651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.0853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.0493, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.7823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5019, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9072, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.1435, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9193, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.4837, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.8634, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2083, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.9223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.5218, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.3146, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.6299, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.0121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.1688, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.5365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.3024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.7036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7804, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4139941690962099, 'recall': 0.5259259259259259, 'f1': 0.4632952691680261, 'number': 270}, 'P': {'precision': 0.6393805309734514, 'recall': 0.6255411255411255, 'f1': 0.6323851203501094, 'number': 462}, 'overall_precision': 0.5421383647798742, 'overall_recall': 0.5887978142076503, 'overall_f1': 0.564505566470203, 'overall_accuracy': 0.7209353507565337}
				Near DM Metrics: {'C': {'precision': 0.3424657534246575, 'recall': 0.45045045045045046, 'f1': 0.3891050583657587, 'number': 111}, 'P': {'precision': 0.6781609195402298, 'recall': 0.6483516483516484, 'f1': 0.6629213483146068, 'number': 182}, 'overall_precision': 0.525, 'overall_recall': 0.5733788395904437, 'overall_f1': 0.5481239804241436, 'overall_accuracy': 0.8573865199449794}
				Far DM Metrics: {'C': {'precision': 0.467005076142132, 'recall': 0.5786163522012578, 'f1': 0.5168539325842697, 'number': 159}, 'P': {'precision': 0.6151079136690647, 'recall': 0.6107142857142858, 'f1': 0.6129032258064516, 'number': 280}, 'overall_precision': 0.5536842105263158, 'overall_recall': 0.5990888382687927, 'overall_f1': 0.5754923413566739, 'overall_accuracy': 0.8283906464924347}
			------------EPOCH 20---------------
Loss:  tensor(18.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.5050, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.6567, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3072, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.8215, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.2595, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.8486, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.0986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7889, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.6649, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.5006, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.8266, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.4139, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.4453, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.9442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.7879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.1129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.3289, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.4818, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.4909, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3150, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.4458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.1034, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.6601, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.8578, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.2484, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.9712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0148, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.5966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.6198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2856, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.9355, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7575, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.9295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.5425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.6488, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5182, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.9634, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.1686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.8934, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2138, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.7890, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0940, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.3379, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.6330, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.41569767441860467, 'recall': 0.5296296296296297, 'f1': 0.4657980456026059, 'number': 270}, 'P': {'precision': 0.6385809312638581, 'recall': 0.6233766233766234, 'f1': 0.6308871851040526, 'number': 462}, 'overall_precision': 0.5421383647798742, 'overall_recall': 0.5887978142076503, 'overall_f1': 0.564505566470203, 'overall_accuracy': 0.7204951856946354}
				Near DM Metrics: {'C': {'precision': 0.3469387755102041, 'recall': 0.4594594594594595, 'f1': 0.3953488372093023, 'number': 111}, 'P': {'precision': 0.6763005780346821, 'recall': 0.6428571428571429, 'f1': 0.6591549295774648, 'number': 182}, 'overall_precision': 0.525, 'overall_recall': 0.5733788395904437, 'overall_f1': 0.5481239804241436, 'overall_accuracy': 0.8556258596973865}
				Far DM Metrics: {'C': {'precision': 0.467005076142132, 'recall': 0.5786163522012578, 'f1': 0.5168539325842697, 'number': 159}, 'P': {'precision': 0.6151079136690647, 'recall': 0.6107142857142858, 'f1': 0.6129032258064516, 'number': 280}, 'overall_precision': 0.5536842105263158, 'overall_recall': 0.5990888382687927, 'overall_f1': 0.5754923413566739, 'overall_accuracy': 0.8285557083906465}
			------------EPOCH 21---------------
Loss:  tensor(16.8505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.1007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.7931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.0249, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.9689, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3170, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9421, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1174, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7812, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9616, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.6100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6177, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.6108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.0864, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.5403, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.6075, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.0841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7349, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.8924, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.7501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.8609, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.8637, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.5858, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.8395, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5049, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.2016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.3424, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9391, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.9814, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.9196, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0479, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.6325, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2086, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.0680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.6307, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.3414, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3895, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.7726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.0383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6046, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.41329479768786126, 'recall': 0.5296296296296297, 'f1': 0.46428571428571425, 'number': 270}, 'P': {'precision': 0.6407982261640798, 'recall': 0.6255411255411255, 'f1': 0.633077765607886, 'number': 462}, 'overall_precision': 0.5420326223337516, 'overall_recall': 0.5901639344262295, 'overall_f1': 0.5650752125572269, 'overall_accuracy': 0.7196698762035764}
				Near DM Metrics: {'C': {'precision': 0.3469387755102041, 'recall': 0.4594594594594595, 'f1': 0.3953488372093023, 'number': 111}, 'P': {'precision': 0.68, 'recall': 0.6538461538461539, 'f1': 0.6666666666666666, 'number': 182}, 'overall_precision': 0.5279503105590062, 'overall_recall': 0.5802047781569966, 'overall_f1': 0.5528455284552845, 'overall_accuracy': 0.8595323246217331}
				Far DM Metrics: {'C': {'precision': 0.4623115577889447, 'recall': 0.5786163522012578, 'f1': 0.5139664804469273, 'number': 159}, 'P': {'precision': 0.6159420289855072, 'recall': 0.6071428571428571, 'f1': 0.6115107913669064, 'number': 280}, 'overall_precision': 0.5515789473684211, 'overall_recall': 0.5968109339407744, 'overall_f1': 0.5733041575492341, 'overall_accuracy': 0.8310866574965612}
			------------EPOCH 22---------------
Loss:  tensor(15.3114, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.1871, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7361, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8907, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4658, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2495, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4232, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.2647, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.2555, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.8153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.0261, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.9085, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.1230, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.4362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5120, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.6067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.0551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.4606, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.9920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3081, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.3543, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4775, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.1931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.6115, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.7721, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7264, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5668, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.0813, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.9825, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.4593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.5104, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.7976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.0610, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.0499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2202, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.6926, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.9491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.0664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3395, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7628, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40974212034383956, 'recall': 0.5296296296296297, 'f1': 0.4620355411954766, 'number': 270}, 'P': {'precision': 0.6393805309734514, 'recall': 0.6255411255411255, 'f1': 0.6323851203501094, 'number': 462}, 'overall_precision': 0.5393258426966292, 'overall_recall': 0.5901639344262295, 'overall_f1': 0.563600782778865, 'overall_accuracy': 0.7182943603851444}
				Near DM Metrics: {'C': {'precision': 0.34, 'recall': 0.4594594594594595, 'f1': 0.39080459770114945, 'number': 111}, 'P': {'precision': 0.6761363636363636, 'recall': 0.6538461538461539, 'f1': 0.664804469273743, 'number': 182}, 'overall_precision': 0.5214723926380368, 'overall_recall': 0.5802047781569966, 'overall_f1': 0.5492730210016156, 'overall_accuracy': 0.8570563961485557}
				Far DM Metrics: {'C': {'precision': 0.4623115577889447, 'recall': 0.5786163522012578, 'f1': 0.5139664804469273, 'number': 159}, 'P': {'precision': 0.6159420289855072, 'recall': 0.6071428571428571, 'f1': 0.6115107913669064, 'number': 280}, 'overall_precision': 0.5515789473684211, 'overall_recall': 0.5968109339407744, 'overall_f1': 0.5733041575492341, 'overall_accuracy': 0.8280055020632737}
			------------EPOCH 23---------------
Loss:  tensor(14.0453, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2516, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9373, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9782, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.1045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8183, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5543, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.9427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.4944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.2201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.9682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.8191, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.6211, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3579, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5478, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.6401, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9149, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4146, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.8418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.5029, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.4110, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5115, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8632, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.7521, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.8128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.9629, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.9745, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.1185, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.3423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.5758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.7323, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.2729, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2265, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.4394, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8736, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.4846, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1370, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.9552, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.4024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.5169, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4109195402298851, 'recall': 0.5296296296296297, 'f1': 0.46278317152103565, 'number': 270}, 'P': {'precision': 0.6504424778761062, 'recall': 0.6363636363636364, 'f1': 0.6433260393873086, 'number': 462}, 'overall_precision': 0.54625, 'overall_recall': 0.5969945355191257, 'overall_f1': 0.5704960835509139, 'overall_accuracy': 0.7193397524071526}
				Near DM Metrics: {'C': {'precision': 0.34, 'recall': 0.4594594594594595, 'f1': 0.39080459770114945, 'number': 111}, 'P': {'precision': 0.6761363636363636, 'recall': 0.6538461538461539, 'f1': 0.664804469273743, 'number': 182}, 'overall_precision': 0.5214723926380368, 'overall_recall': 0.5802047781569966, 'overall_f1': 0.5492730210016156, 'overall_accuracy': 0.8579367262723522}
				Far DM Metrics: {'C': {'precision': 0.46464646464646464, 'recall': 0.5786163522012578, 'f1': 0.515406162464986, 'number': 159}, 'P': {'precision': 0.6340579710144928, 'recall': 0.625, 'f1': 0.6294964028776979, 'number': 280}, 'overall_precision': 0.5632911392405063, 'overall_recall': 0.6082004555808656, 'overall_f1': 0.5848849945235488, 'overall_accuracy': 0.8283906464924347}
			------------EPOCH 24---------------
Loss:  tensor(12.9464, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.4885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.0114, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0339, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7725, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6910, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6429, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0629, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.7724, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.9761, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.9706, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.0906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.0791, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.8995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8230, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.0893, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.2765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5575, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.6499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.3426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.6540, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5562, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.5395, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9274, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.7666, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5021, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9053, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.7222, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.7937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0378, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2071, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4079, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.4087, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.5369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.7016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.9275, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.9532, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.8803, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.3488, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.1187, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0812, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.5399, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.5046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.4084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2570, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.6681, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5979, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4085714285714286, 'recall': 0.5296296296296297, 'f1': 0.4612903225806452, 'number': 270}, 'P': {'precision': 0.6511111111111111, 'recall': 0.6341991341991342, 'f1': 0.6425438596491228, 'number': 462}, 'overall_precision': 0.545, 'overall_recall': 0.5956284153005464, 'overall_f1': 0.5691906005221933, 'overall_accuracy': 0.7183493810178817}
				Near DM Metrics: {'C': {'precision': 0.3443708609271523, 'recall': 0.46846846846846846, 'f1': 0.3969465648854962, 'number': 111}, 'P': {'precision': 0.6724137931034483, 'recall': 0.6428571428571429, 'f1': 0.6573033707865169, 'number': 182}, 'overall_precision': 0.52, 'overall_recall': 0.5767918088737202, 'overall_f1': 0.5469255663430421, 'overall_accuracy': 0.8565612104539202}
				Far DM Metrics: {'C': {'precision': 0.457286432160804, 'recall': 0.5723270440251572, 'f1': 0.5083798882681564, 'number': 159}, 'P': {'precision': 0.6376811594202898, 'recall': 0.6285714285714286, 'f1': 0.6330935251798562, 'number': 280}, 'overall_precision': 0.5621052631578948, 'overall_recall': 0.6082004555808656, 'overall_f1': 0.5842450765864332, 'overall_accuracy': 0.828665749656121}
			------------EPOCH 25---------------
Loss:  tensor(11.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7493, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.5869, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.0969, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.1168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.2764, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.5953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.5137, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.6988, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.7751, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.2233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.7227, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.6340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.6957, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7901, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3525, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3102, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2325, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.9444, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.5593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.7623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3070, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.0018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.8145, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.6433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.6785, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.7033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0429, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0743, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.0314, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.4976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.3450, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.5400, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.3227, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3659, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.6400, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.3800, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7908, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.7164, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2573, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.4173, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.9174, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8334, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.8476, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8981, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1157, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.41260744985673353, 'recall': 0.5333333333333333, 'f1': 0.46526655896607433, 'number': 270}, 'P': {'precision': 0.6518847006651884, 'recall': 0.6363636363636364, 'f1': 0.6440306681270537, 'number': 462}, 'overall_precision': 0.5475, 'overall_recall': 0.5983606557377049, 'overall_f1': 0.5718015665796345, 'overall_accuracy': 0.719009628610729}
				Near DM Metrics: {'C': {'precision': 0.35570469798657717, 'recall': 0.4774774774774775, 'f1': 0.4076923076923077, 'number': 111}, 'P': {'precision': 0.6761363636363636, 'recall': 0.6538461538461539, 'f1': 0.664804469273743, 'number': 182}, 'overall_precision': 0.5292307692307693, 'overall_recall': 0.5870307167235495, 'overall_f1': 0.5566343042071197, 'overall_accuracy': 0.8595873452544704}
				Far DM Metrics: {'C': {'precision': 0.455, 'recall': 0.5723270440251572, 'f1': 0.5069637883008357, 'number': 159}, 'P': {'precision': 0.6363636363636364, 'recall': 0.625, 'f1': 0.6306306306306306, 'number': 280}, 'overall_precision': 0.56, 'overall_recall': 0.6059225512528473, 'overall_f1': 0.5820568927789933, 'overall_accuracy': 0.8282255845942228}
	Train size: 50 Test size: 50
Tokenizer: allenai/longformer-base-4096 Model: allenai/longformer-base-4096


		-------------RUN 1-----------
			------------EPOCH 1---------------
Loss:  tensor(2390.0508, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1392.7606, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1734.2773, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1832.4966, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1547.8406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2721.7842, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1262.3867, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1986.7045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2097.8423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1315.1179, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2662.2163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1924.0642, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1771.8472, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1277.1664, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1953.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1423.7120, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1296.5059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2730.4734, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2559.7830, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1863.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2544.6541, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1595.8317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1843.6111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(621.4535, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1101.8564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1017.2723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1514.6854, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1270.7009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1286.3279, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1792.0001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1476.2385, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2198.2112, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2463.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3691.1406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2284.7620, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2571.4683, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.043813192103996146, 'recall': 0.12656467315716272, 'f1': 0.06509298998569385, 'number': 719}, 'P': {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1035}, 'overall_precision': 0.043686989918386945, 'overall_recall': 0.05188141391106044, 'overall_f1': 0.0474328902788637, 'overall_accuracy': 0.3505325650427798}
				Near DM Metrics: {'C': {'precision': 0.03502824858757062, 'recall': 0.11567164179104478, 'f1': 0.05377276669557676, 'number': 268}, 'P': {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 398}, 'overall_precision': 0.03502824858757062, 'overall_recall': 0.046546546546546545, 'overall_f1': 0.039974210186976146, 'overall_accuracy': 0.6727344159245678}
				Far DM Metrics: {'C': {'precision': 0.04357298474945534, 'recall': 0.13303769401330376, 'f1': 0.06564551422319476, 'number': 451}, 'P': {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 637}, 'overall_precision': 0.04338394793926247, 'overall_recall': 0.05514705882352941, 'overall_f1': 0.04856333468231484, 'overall_accuracy': 0.5504627204470054}
			------------EPOCH 2---------------
Loss:  tensor(1620.1462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(952.6643, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1253.5466, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1290.7982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1227.9343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2085.6604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1047.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1609.1023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1810.3973, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(908.9001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1838.9390, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1319.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1288.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(971.7252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1458.4246, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1151.4995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1041.8857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1819.7407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2027.4823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1457.0883, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2046.2318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1153.0609, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1460.6812, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(548.4916, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(908.5624, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(900.2210, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1230.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1030.5679, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1022.0470, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1478.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1141.4446, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1660.9934, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2027.9167, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3079.9333, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1894.1620, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2238.8818, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.1896633475580844, 'recall': 0.5563282336578581, 'f1': 0.2828854314002829, 'number': 719}, 'P': {'precision': 0.31297709923664124, 'recall': 0.03961352657004831, 'f1': 0.07032590051457976, 'number': 1035}, 'overall_precision': 0.196875, 'overall_recall': 0.2514253135689852, 'overall_f1': 0.22083124687030548, 'overall_accuracy': 0.4137419242186136}
				Near DM Metrics: {'C': {'precision': 0.17121046892039257, 'recall': 0.585820895522388, 'f1': 0.26497890295358645, 'number': 268}, 'P': {'precision': 0.4411764705882353, 'recall': 0.03768844221105527, 'f1': 0.06944444444444443, 'number': 398}, 'overall_precision': 0.1808622502628812, 'overall_recall': 0.25825825825825827, 'overall_f1': 0.21273964131106987, 'overall_accuracy': 0.7107997206216169}
				Far DM Metrics: {'C': {'precision': 0.19179163378058406, 'recall': 0.5388026607538803, 'f1': 0.2828870779976717, 'number': 451}, 'P': {'precision': 0.26804123711340205, 'recall': 0.04081632653061224, 'f1': 0.07084468664850135, 'number': 637}, 'overall_precision': 0.1972140762463343, 'overall_recall': 0.24724264705882354, 'overall_f1': 0.21941272430668843, 'overall_accuracy': 0.6265715034049241}
			------------EPOCH 3---------------
Loss:  tensor(1306.4099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(781.1700, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1100.7749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1047.4854, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1007.2662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1675.9475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(783.8606, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1173.8654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1271.7505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(713.7367, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1460.0684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1072.8994, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1075.6477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(779.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1115.0433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(992.4731, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(814.5160, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1360.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1643.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1240.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1733.7955, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(957.1458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1165.7169, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(481.3062, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(789.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(802.6410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1014.0117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(912.5596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(852.4429, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1278.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(842.6758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1329.9722, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1698.1459, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2662.4927, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1493.3333, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1922.6333, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.20491803278688525, 'recall': 0.5563282336578581, 'f1': 0.2995132909022838, 'number': 719}, 'P': {'precision': 0.3442622950819672, 'recall': 0.04057971014492753, 'f1': 0.07260155574762316, 'number': 1035}, 'overall_precision': 0.21311475409836064, 'overall_recall': 0.2519954389965792, 'overall_f1': 0.2309299895506792, 'overall_accuracy': 0.4463506198707875}
				Near DM Metrics: {'C': {'precision': 0.17870257037943696, 'recall': 0.5447761194029851, 'f1': 0.26912442396313363, 'number': 268}, 'P': {'precision': 0.38636363636363635, 'recall': 0.04271356783919598, 'f1': 0.07692307692307691, 'number': 398}, 'overall_precision': 0.18931475029036005, 'overall_recall': 0.24474474474474475, 'overall_f1': 0.21349050425671254, 'overall_accuracy': 0.7288065304697049}
				Far DM Metrics: {'C': {'precision': 0.21326616288832914, 'recall': 0.5631929046563193, 'f1': 0.3093788063337394, 'number': 451}, 'P': {'precision': 0.32051282051282054, 'recall': 0.03924646781789639, 'f1': 0.06993006993006994, 'number': 637}, 'overall_precision': 0.2198581560283688, 'overall_recall': 0.25643382352941174, 'overall_f1': 0.2367416207042851, 'overall_accuracy': 0.662803387462895}
			------------EPOCH 4---------------
Loss:  tensor(1117.0127, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(707.0288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1041.9023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(910.2541, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(849.1582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1483.2379, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(571.8665, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(843.9678, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(878.4280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(562.5286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1169.0728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(874.5176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(919.2812, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(625.0675, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(869.8804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(876.4343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(604.8417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(920.5989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1317.3359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1036.9004, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1460.9421, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(722.4347, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(898.0579, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(400.9473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(705.0250, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(699.5400, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(774.5012, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(776.7231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(695.3978, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1088.9463, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(615.7507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1144.2950, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1392.5913, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2369.6206, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1240.5706, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1563.4321, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.2413184226015303, 'recall': 0.5702364394993046, 'f1': 0.3391232423490488, 'number': 719}, 'P': {'precision': 0.391358024691358, 'recall': 0.30628019323671496, 'f1': 0.34363143631436316, 'number': 1035}, 'overall_precision': 0.2897568752491032, 'overall_recall': 0.4144811858608894, 'overall_f1': 0.34107436077879427, 'overall_accuracy': 0.5758468657237646}
				Near DM Metrics: {'C': {'precision': 0.23661971830985915, 'recall': 0.6268656716417911, 'f1': 0.3435582822085889, 'number': 268}, 'P': {'precision': 0.4166666666666667, 'recall': 0.2889447236180904, 'f1': 0.3412462908011869, 'number': 398}, 'overall_precision': 0.2870182555780933, 'overall_recall': 0.42492492492492495, 'overall_f1': 0.3426150121065375, 'overall_accuracy': 0.7763445084686572}
				Far DM Metrics: {'C': {'precision': 0.23157894736842105, 'recall': 0.5365853658536586, 'f1': 0.32352941176470584, 'number': 451}, 'P': {'precision': 0.3782771535580524, 'recall': 0.31711145996860285, 'f1': 0.34500426985482496, 'number': 637}, 'overall_precision': 0.2811906269791007, 'overall_recall': 0.40808823529411764, 'overall_f1': 0.3329583802024747, 'overall_accuracy': 0.7227824340841628}
			------------EPOCH 5---------------
Loss:  tensor(994.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(523.8559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(820.2892, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(795.5452, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(744.3459, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1064.1221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.0504, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(529.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(624.5022, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(426.9373, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(843.7600, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(631.0657, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(800.8785, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(548.5848, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(741.6230, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(828.5298, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(512.8335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(790.5843, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1049.0400, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1077.4863, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1280.7096, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(691.4364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(789.3970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(337.7692, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(510.8399, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.6490, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.8960, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(566.6715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(569.2803, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(833.9547, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(481.3776, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(918.4583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1288.9253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2179.6946, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.1473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1280.8228, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.27832512315270935, 'recall': 0.1571627260083449, 'f1': 0.20088888888888887, 'number': 719}, 'P': {'precision': 0.4115068493150685, 'recall': 0.7256038647342995, 'f1': 0.5251748251748252, 'number': 1035}, 'overall_precision': 0.3872702823845809, 'overall_recall': 0.4925883694412771, 'overall_f1': 0.43362609786700124, 'overall_accuracy': 0.6536581107036843}
				Near DM Metrics: {'C': {'precision': 0.1793478260869565, 'recall': 0.12313432835820895, 'f1': 0.14601769911504422, 'number': 268}, 'P': {'precision': 0.3945868945868946, 'recall': 0.6959798994974874, 'f1': 0.5036363636363637, 'number': 398}, 'overall_precision': 0.34988713318284426, 'overall_recall': 0.46546546546546547, 'overall_f1': 0.39948453608247425, 'overall_accuracy': 0.8260869565217391}
				Far DM Metrics: {'C': {'precision': 0.29304029304029305, 'recall': 0.17738359201773837, 'f1': 0.22099447513812154, 'number': 451}, 'P': {'precision': 0.42021276595744683, 'recall': 0.7441130298273155, 'f1': 0.5371104815864023, 'number': 637}, 'overall_precision': 0.39543183440399715, 'overall_recall': 0.5091911764705882, 'overall_f1': 0.4451586982723985, 'overall_accuracy': 0.7790073336825563}
			------------EPOCH 6---------------
Loss:  tensor(1282.0999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(559.2118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(807.9039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(943.9668, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(720.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(815.3145, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(377.9405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(590.6062, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(547.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(366.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(704.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(631.9213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(560.2753, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(369.2181, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(597.9785, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(558.6365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(423.2348, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(614.7523, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(746.7051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(793.6145, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1287.3912, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(704.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(847.4174, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(334.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(599.2635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(580.6419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(635.0731, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(641.8834, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(972.4628, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1009.0645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(680.0034, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1338.3074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1277.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1882.4586, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(949.1090, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1153.5806, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.31, 'recall': 0.34492350486787204, 'f1': 0.32653061224489793, 'number': 719}, 'P': {'precision': 0.4658040665434381, 'recall': 0.7304347826086957, 'f1': 0.5688487584650113, 'number': 1035}, 'overall_precision': 0.4143623607098638, 'overall_recall': 0.572405929304447, 'overall_f1': 0.48072779506823077, 'overall_accuracy': 0.6464117338920901}
				Near DM Metrics: {'C': {'precision': 0.2546916890080429, 'recall': 0.35447761194029853, 'f1': 0.29641185647425894, 'number': 268}, 'P': {'precision': 0.4366883116883117, 'recall': 0.6758793969849246, 'f1': 0.5305719921104536, 'number': 398}, 'overall_precision': 0.36804853387259856, 'overall_recall': 0.5465465465465466, 'overall_f1': 0.4398791540785498, 'overall_accuracy': 0.8170726383796054}
				Far DM Metrics: {'C': {'precision': 0.3167701863354037, 'recall': 0.3392461197339246, 'f1': 0.32762312633832974, 'number': 451}, 'P': {'precision': 0.48361469712015887, 'recall': 0.7645211930926217, 'f1': 0.5924574209245742, 'number': 637}, 'overall_precision': 0.42953020134228187, 'overall_recall': 0.5882352941176471, 'overall_f1': 0.49650892164468585, 'overall_accuracy': 0.7761917234154008}
			------------EPOCH 7---------------
Loss:  tensor(933.8608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(340.0963, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(643.2497, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(683.3564, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(859.8878, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(923.5662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.9641, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(591.7233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(902.1859, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(424.3207, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(786.8485, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(698.8840, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(906.6801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(638.7778, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1056.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(803.9998, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.9554, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(628.4417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1113.9204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1044.5179, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1457.7073, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(683.8407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(745.2904, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(284.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(501.3526, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.8841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(548.6442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(578.8259, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(534.2537, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(708.2750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(362.9766, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(805.6831, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(972.1441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1543.5912, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(719.9235, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1021.8777, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.24681753889674682, 'recall': 0.4853963838664812, 'f1': 0.32723863103609935, 'number': 719}, 'P': {'precision': 0.34908136482939633, 'recall': 0.1285024154589372, 'f1': 0.18785310734463276, 'number': 1035}, 'overall_precision': 0.26852367688022283, 'overall_recall': 0.2748004561003421, 'overall_f1': 0.27162581008734854, 'overall_accuracy': 0.5664396717303999}
				Near DM Metrics: {'C': {'precision': 0.19093851132686085, 'recall': 0.44029850746268656, 'f1': 0.2663656884875847, 'number': 268}, 'P': {'precision': 0.3951612903225806, 'recall': 0.12311557788944724, 'f1': 0.18773946360153257, 'number': 398}, 'overall_precision': 0.22506738544474394, 'overall_recall': 0.25075075075075076, 'overall_f1': 0.2372159090909091, 'overall_accuracy': 0.7798585646935569}
				Far DM Metrics: {'C': {'precision': 0.2711267605633803, 'recall': 0.5121951219512195, 'f1': 0.35456638526477363, 'number': 451}, 'P': {'precision': 0.32684824902723736, 'recall': 0.13186813186813187, 'f1': 0.1879194630872483, 'number': 637}, 'overall_precision': 0.2840396753832281, 'overall_recall': 0.28952205882352944, 'overall_f1': 0.2867546654528903, 'overall_accuracy': 0.7259472673301903}
			------------EPOCH 8---------------
Loss:  tensor(939.8740, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(603.3384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(900.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(865.6295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(776.6874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(813.0973, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(339.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(452.8898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(402.9527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(351.0873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(760.5499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(579.7748, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(552.5841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(368.5267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(520.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(531.4689, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(396.4954, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(581.5505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(578.4817, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(654.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(938.7241, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(520.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(609.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(263.3478, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(421.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(493.3239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(511.3875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(502.5329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(484.4301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(810.4899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(325.7100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(740.5748, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1046.3185, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1510.6597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(622.7563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1175.3772, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.36947791164658633, 'recall': 0.38386648122392214, 'f1': 0.3765347885402456, 'number': 719}, 'P': {'precision': 0.5045871559633027, 'recall': 0.7439613526570048, 'f1': 0.6013276064037484, 'number': 1035}, 'overall_precision': 0.4601847778266608, 'overall_recall': 0.5963511972633979, 'overall_f1': 0.5194934194189222, 'overall_accuracy': 0.6673432861882311}
				Near DM Metrics: {'C': {'precision': 0.28688524590163933, 'recall': 0.3917910447761194, 'f1': 0.33123028391167186, 'number': 268}, 'P': {'precision': 0.501779359430605, 'recall': 0.7085427135678392, 'f1': 0.5875, 'number': 398}, 'overall_precision': 0.4170258620689655, 'overall_recall': 0.581081081081081, 'overall_f1': 0.4855708908406524, 'overall_accuracy': 0.8321765322158198}
				Far DM Metrics: {'C': {'precision': 0.3904109589041096, 'recall': 0.37915742793791574, 'f1': 0.38470191226096734, 'number': 451}, 'P': {'precision': 0.5062240663900415, 'recall': 0.7660910518053375, 'f1': 0.6096189881324171, 'number': 637}, 'overall_precision': 0.47004279600570614, 'overall_recall': 0.6056985294117647, 'overall_f1': 0.5293172690763053, 'overall_accuracy': 0.7973197136371574}
			------------EPOCH 9---------------
Loss:  tensor(726.6234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.6122, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(482.7511, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(584.5832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(528.7910, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(493.2038, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(241.1393, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(341.4460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(421.0225, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(233.0480, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(521.5753, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(465.5340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(472.1303, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(312.4384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(524.3475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(429.4703, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(290.1851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(454.5600, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(568.7734, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(674.4998, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(744.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(417.8024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(368.3027, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.9616, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(335.8085, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.2708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(261.4295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(353.0566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(373.5922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(479.9051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(196.9691, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(653.9976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(764.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1060.9064, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(376.0223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(576.1872, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3138020833333333, 'recall': 0.6703755215577191, 'f1': 0.42749445676274944, 'number': 719}, 'P': {'precision': 0.635890767230169, 'recall': 0.47246376811594204, 'f1': 0.5421286031042128, 'number': 1035}, 'overall_precision': 0.42125813449023863, 'overall_recall': 0.5535917901938426, 'overall_f1': 0.4784429662478443, 'overall_accuracy': 0.6157892439322508}
				Near DM Metrics: {'C': {'precision': 0.2782874617737003, 'recall': 0.6791044776119403, 'f1': 0.3947939262472885, 'number': 268}, 'P': {'precision': 0.5890909090909091, 'recall': 0.40703517587939697, 'f1': 0.48142644873699847, 'number': 398}, 'overall_precision': 0.37029063509149623, 'overall_recall': 0.5165165165165165, 'overall_f1': 0.4313479623824452, 'overall_accuracy': 0.8130347476863977}
				Far DM Metrics: {'C': {'precision': 0.3194888178913738, 'recall': 0.6651884700665188, 'f1': 0.43165467625899273, 'number': 451}, 'P': {'precision': 0.6619433198380567, 'recall': 0.5133437990580848, 'f1': 0.5782493368700266, 'number': 637}, 'overall_precision': 0.43754361479413817, 'overall_recall': 0.5762867647058824, 'overall_f1': 0.4974216580721936, 'overall_accuracy': 0.7755151038938363}
			------------EPOCH 10---------------
Loss:  tensor(568.6523, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(298.5222, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(467.3069, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(427.9009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(380.3773, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(412.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(224.0494, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.9944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(189.1000, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(158.8623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(259.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(204.6133, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.4419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.1371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(300.0532, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(283.2369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(147.6989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(180.9559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(239.7368, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(345.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.4470, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(286.0095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(262.0074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.4233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(289.2798, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.9501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(187.2273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(322.7712, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.0560, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(347.9476, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(173.2315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(590.5029, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(383.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(707.7007, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.6175, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(448.3288, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39213806327900286, 'recall': 0.56884561891516, 'f1': 0.4642451759364358, 'number': 719}, 'P': {'precision': 0.6136595310907238, 'recall': 0.5816425120772947, 'f1': 0.5972222222222223, 'number': 1035}, 'overall_precision': 0.49950592885375494, 'overall_recall': 0.5763968072976055, 'overall_f1': 0.5352038115404977, 'overall_accuracy': 0.7082678540247949}
				Near DM Metrics: {'C': {'precision': 0.3217391304347826, 'recall': 0.5522388059701493, 'f1': 0.40659340659340665, 'number': 268}, 'P': {'precision': 0.5659340659340659, 'recall': 0.5175879396984925, 'f1': 0.5406824146981628, 'number': 398}, 'overall_precision': 0.42961165048543687, 'overall_recall': 0.5315315315315315, 'overall_f1': 0.4751677852348993, 'overall_accuracy': 0.85577090972586}
				Far DM Metrics: {'C': {'precision': 0.4078125, 'recall': 0.5787139689578714, 'f1': 0.4784601283226398, 'number': 451}, 'P': {'precision': 0.6418152350081038, 'recall': 0.6216640502354788, 'f1': 0.6315789473684211, 'number': 637}, 'overall_precision': 0.522673031026253, 'overall_recall': 0.6038602941176471, 'overall_f1': 0.5603411513859274, 'overall_accuracy': 0.8155229614108608}
			------------EPOCH 11---------------
Loss:  tensor(367.8666, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.9570, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(267.9345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(245.9369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(290.9562, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(171.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.4208, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.5754, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(135.8745, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.2420, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(176.8094, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(147.1272, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(150.8906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(159.9784, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(217.6159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.2801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(109.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(137.5344, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.2869, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(242.4998, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(306.9559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(219.4066, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(175.6743, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(138.0636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.1633, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.5287, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.0441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(159.3615, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(141.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.6688, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.1646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(411.2070, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(219.4095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(406.1899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.6762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(230.0474, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4125714285714286, 'recall': 0.502086230876217, 'f1': 0.4529485570890841, 'number': 719}, 'P': {'precision': 0.5858034321372855, 'recall': 0.7256038647342995, 'f1': 0.6482520500647388, 'number': 1035}, 'overall_precision': 0.5155308298562818, 'overall_recall': 0.6339794754846066, 'overall_f1': 0.5686525185374585, 'overall_accuracy': 0.7019818404050987}
				Near DM Metrics: {'C': {'precision': 0.33651551312649164, 'recall': 0.5261194029850746, 'f1': 0.4104803493449782, 'number': 268}, 'P': {'precision': 0.5835095137420718, 'recall': 0.6934673366834171, 'f1': 0.6337543053960963, 'number': 398}, 'overall_precision': 0.4674887892376682, 'overall_recall': 0.6261261261261262, 'overall_f1': 0.5353016688061617, 'overall_accuracy': 0.8558363890343985}
				Far DM Metrics: {'C': {'precision': 0.42884990253411304, 'recall': 0.4878048780487805, 'f1': 0.45643153526970953, 'number': 451}, 'P': {'precision': 0.5871446229913473, 'recall': 0.7456828885400314, 'f1': 0.656984785615491, 'number': 637}, 'overall_precision': 0.5257186081694403, 'overall_recall': 0.6387867647058824, 'overall_f1': 0.5767634854771784, 'overall_accuracy': 0.8136458878994238}
			------------EPOCH 12---------------
Loss:  tensor(251.7781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(136.8704, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(204.1149, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(219.8383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(248.9822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.4996, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.6380, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(113.5656, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(108.3856, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(99.9324, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(121.4669, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.7759, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.9412, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.0285, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(129.1892, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(125.0918, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.8280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.2793, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(110.9641, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.6576, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.5122, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(86.0801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(89.4696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(117.9716, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.9686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.2050, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(101.7280, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.2131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(171.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(303.5951, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(147.6209, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(337.3076, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(143.1021, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3764607679465776, 'recall': 0.627260083449235, 'f1': 0.470526864893062, 'number': 719}, 'P': {'precision': 0.6454445664105378, 'recall': 0.5681159420289855, 'f1': 0.60431654676259, 'number': 1035}, 'overall_precision': 0.4926505452821242, 'overall_recall': 0.5923603192702395, 'overall_f1': 0.5379238933471394, 'overall_accuracy': 0.698249519818404}
				Near DM Metrics: {'C': {'precision': 0.3326732673267327, 'recall': 0.6268656716417911, 'f1': 0.4346701164294955, 'number': 268}, 'P': {'precision': 0.6275659824046921, 'recall': 0.5376884422110553, 'f1': 0.5791610284167793, 'number': 398}, 'overall_precision': 0.4515366430260047, 'overall_recall': 0.5735735735735735, 'overall_f1': 0.5052910052910052, 'overall_accuracy': 0.8537410511611664}
				Far DM Metrics: {'C': {'precision': 0.37733333333333335, 'recall': 0.6274944567627494, 'f1': 0.47127393838467946, 'number': 451}, 'P': {'precision': 0.656140350877193, 'recall': 0.5871271585557299, 'f1': 0.619718309859155, 'number': 637}, 'overall_precision': 0.49772727272727274, 'overall_recall': 0.6038602941176471, 'overall_f1': 0.5456810631229236, 'overall_accuracy': 0.8175528199755544}
			------------EPOCH 13---------------
Loss:  tensor(138.9897, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(88.6524, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(106.0545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(122.1060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(98.3254, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.3882, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(81.6814, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.1326, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.8322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.7315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.8675, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.0081, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.6677, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.4108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.1255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.3366, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.9112, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.2193, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.6572, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(145.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.9092, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.7268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.1511, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.5591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.8605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.6164, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.3695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(77.3628, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.6836, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.3213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(193.4048, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.0570, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(215.5047, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.2419, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(112.8566, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.36854646544876885, 'recall': 0.6453407510431154, 'f1': 0.4691607684529828, 'number': 719}, 'P': {'precision': 0.6603351955307263, 'recall': 0.5710144927536231, 'f1': 0.6124352331606218, 'number': 1035}, 'overall_precision': 0.48978644382544106, 'overall_recall': 0.6014823261117446, 'overall_f1': 0.5399181166837257, 'overall_accuracy': 0.6922035969966824}
				Near DM Metrics: {'C': {'precision': 0.3092224231464738, 'recall': 0.6380597014925373, 'f1': 0.41656516443361763, 'number': 268}, 'P': {'precision': 0.6144927536231884, 'recall': 0.5326633165829145, 'f1': 0.5706594885598923, 'number': 398}, 'overall_precision': 0.4265033407572383, 'overall_recall': 0.575075075075075, 'overall_f1': 0.48976982097186694, 'overall_accuracy': 0.8495503754147022}
				Far DM Metrics: {'C': {'precision': 0.36488169364881695, 'recall': 0.6496674057649667, 'f1': 0.46730462519936206, 'number': 451}, 'P': {'precision': 0.6890909090909091, 'recall': 0.5949764521193093, 'f1': 0.6385846672283066, 'number': 637}, 'overall_precision': 0.49667405764966743, 'overall_recall': 0.6176470588235294, 'overall_f1': 0.5505940188447359, 'overall_accuracy': 0.8119434258774227}
			------------EPOCH 14---------------
Loss:  tensor(90.1637, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.5281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.8059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.7711, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.9461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.3925, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.9955, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.3386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.4950, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.1457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.4379, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.4728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.5184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.1999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.2107, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.5939, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1538, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.0452, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.4322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(68.0968, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.9571, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.7388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.1058, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.1991, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.8577, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.3738, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.9397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.0152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.4102, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(95.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.3715, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(146.9406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5500, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.2621, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40807651434643993, 'recall': 0.5340751043115438, 'f1': 0.46265060240963857, 'number': 719}, 'P': {'precision': 0.5806451612903226, 'recall': 0.6782608695652174, 'f1': 0.625668449197861, 'number': 1035}, 'overall_precision': 0.5051162790697674, 'overall_recall': 0.6191562143671607, 'overall_f1': 0.5563524590163934, 'overall_accuracy': 0.7071328793434608}
				Near DM Metrics: {'C': {'precision': 0.35336538461538464, 'recall': 0.5485074626865671, 'f1': 0.42982456140350883, 'number': 268}, 'P': {'precision': 0.5682819383259912, 'recall': 0.6482412060301508, 'f1': 0.6056338028169014, 'number': 398}, 'overall_precision': 0.46551724137931033, 'overall_recall': 0.6081081081081081, 'overall_f1': 0.5273437500000001, 'overall_accuracy': 0.8639994761655317}
				Far DM Metrics: {'C': {'precision': 0.41074523396880414, 'recall': 0.5254988913525499, 'f1': 0.4610894941634241, 'number': 451}, 'P': {'precision': 0.5834428383705651, 'recall': 0.6970172684458399, 'f1': 0.6351931330472104, 'number': 637}, 'overall_precision': 0.5089686098654709, 'overall_recall': 0.6259191176470589, 'overall_f1': 0.5614179719703216, 'overall_accuracy': 0.819975554391479}
			------------EPOCH 15---------------
Loss:  tensor(73.2269, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(58.2250, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.1013, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.5143, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.4804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.5977, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1524, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.0829, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1194, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.2777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.4948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.0582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.5102, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.5201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8641, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3693, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.6184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.3144, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1437, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.2129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.3833, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4382, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.9072, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.7475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.4953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.0668, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.3829, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.8588, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(56.1326, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.386443661971831, 'recall': 0.6105702364394993, 'f1': 0.4733153638814016, 'number': 719}, 'P': {'precision': 0.599591419816139, 'recall': 0.5671497584541063, 'f1': 0.5829195630585899, 'number': 1035}, 'overall_precision': 0.4851063829787234, 'overall_recall': 0.5849486887115165, 'overall_f1': 0.530369604548979, 'overall_accuracy': 0.69449537279553}
				Near DM Metrics: {'C': {'precision': 0.34309623430962344, 'recall': 0.6119402985074627, 'f1': 0.43967828418230565, 'number': 268}, 'P': {'precision': 0.5799457994579946, 'recall': 0.5376884422110553, 'f1': 0.5580182529335073, 'number': 398}, 'overall_precision': 0.4462809917355372, 'overall_recall': 0.5675675675675675, 'overall_f1': 0.4996695307336417, 'overall_accuracy': 0.8567094464815785}
				Far DM Metrics: {'C': {'precision': 0.38787023977433005, 'recall': 0.6097560975609756, 'f1': 0.4741379310344828, 'number': 451}, 'P': {'precision': 0.6065040650406504, 'recall': 0.5855572998430141, 'f1': 0.595846645367412, 'number': 637}, 'overall_precision': 0.48942598187311176, 'overall_recall': 0.5955882352941176, 'overall_f1': 0.5373134328358208, 'overall_accuracy': 0.8138641522612188}
			------------EPOCH 16---------------
Loss:  tensor(39.1935, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.1840, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.1821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.7874, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.0975, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.9529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.1594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2915, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.8081, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.4608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.1035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.9795, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5336, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1929, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.6887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7349, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.8433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.8584, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.1500, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.3397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.4300, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.8484, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8607, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.3554, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.4217, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.5797, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.0705, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7819, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.5597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7554, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.0082, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.394990366088632, 'recall': 0.5702364394993046, 'f1': 0.4667046101309049, 'number': 719}, 'P': {'precision': 0.5931899641577061, 'recall': 0.6396135265700483, 'f1': 0.6155276615527661, 'number': 1035}, 'overall_precision': 0.4976787372330548, 'overall_recall': 0.6111744583808438, 'overall_f1': 0.548618219037871, 'overall_accuracy': 0.6972455037541471}
				Near DM Metrics: {'C': {'precision': 0.3549107142857143, 'recall': 0.5932835820895522, 'f1': 0.4441340782122905, 'number': 268}, 'P': {'precision': 0.5857142857142857, 'recall': 0.6180904522613065, 'f1': 0.6014669926650367, 'number': 398}, 'overall_precision': 0.4665898617511521, 'overall_recall': 0.6081081081081081, 'overall_f1': 0.5280312907431551, 'overall_accuracy': 0.858302776322682}
				Far DM Metrics: {'C': {'precision': 0.3915756630265211, 'recall': 0.5565410199556541, 'f1': 0.4597069597069597, 'number': 451}, 'P': {'precision': 0.5934379457917262, 'recall': 0.6530612244897959, 'f1': 0.6218236173393124, 'number': 637}, 'overall_precision': 0.4970193740685544, 'overall_recall': 0.6130514705882353, 'overall_f1': 0.5489711934156378, 'overall_accuracy': 0.8138641522612188}
			------------EPOCH 17---------------
Loss:  tensor(27.7836, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0954, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.6669, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.0916, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.6762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.1425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.1878, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.9160, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7591, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2268, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.7730, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.4977, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.1711, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.4640, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.0708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8222, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.0892, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.8416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.0090, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.7018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1854, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3233, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.9308, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.5217, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.1885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.0686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.9870, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.2584, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.0230, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5114, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39239332096474955, 'recall': 0.588317107093185, 'f1': 0.4707846410684474, 'number': 719}, 'P': {'precision': 0.5964083175803403, 'recall': 0.6096618357487923, 'f1': 0.6029622551361682, 'number': 1035}, 'overall_precision': 0.4934456928838951, 'overall_recall': 0.6009122006841505, 'overall_f1': 0.5419023136246787, 'overall_accuracy': 0.6982713462545835}
				Near DM Metrics: {'C': {'precision': 0.3466666666666667, 'recall': 0.582089552238806, 'f1': 0.4345403899721449, 'number': 268}, 'P': {'precision': 0.6, 'recall': 0.5804020100502513, 'f1': 0.5900383141762452, 'number': 398}, 'overall_precision': 0.46347305389221555, 'overall_recall': 0.581081081081081, 'overall_f1': 0.5156562291805463, 'overall_accuracy': 0.8618823118561202}
				Far DM Metrics: {'C': {'precision': 0.39322533136966126, 'recall': 0.5920177383592018, 'f1': 0.47256637168141596, 'number': 451}, 'P': {'precision': 0.5899705014749262, 'recall': 0.6279434850863422, 'f1': 0.6083650190114068, 'number': 637}, 'overall_precision': 0.4915254237288136, 'overall_recall': 0.6130514705882353, 'overall_f1': 0.54560327198364, 'overall_accuracy': 0.8139296315697573}
			------------EPOCH 18---------------
Loss:  tensor(21.3158, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2119, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0444, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.4151, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.8801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3028, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6973, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.8163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.4632, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5216, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.8392, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.0099, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.3956, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6619, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.1327, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5488, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5974, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.1937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.8559, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.0558, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.5313, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.8649, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.4267, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.4999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1484, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.1504, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.2660, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2065, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.380352644836272, 'recall': 0.6300417246175244, 'f1': 0.47434554973821985, 'number': 719}, 'P': {'precision': 0.6176470588235294, 'recall': 0.5681159420289855, 'f1': 0.5918470055359838, 'number': 1035}, 'overall_precision': 0.4857676154923005, 'overall_recall': 0.5935005701254276, 'overall_f1': 0.5342571208622016, 'overall_accuracy': 0.6932730923694779}
				Near DM Metrics: {'C': {'precision': 0.3236434108527132, 'recall': 0.6231343283582089, 'f1': 0.4260204081632653, 'number': 268}, 'P': {'precision': 0.5797101449275363, 'recall': 0.5025125628140703, 'f1': 0.5383580080753702, 'number': 398}, 'overall_precision': 0.4262485481997677, 'overall_recall': 0.551051051051051, 'overall_f1': 0.48068107400130977, 'overall_accuracy': 0.8496813340317793}
				Far DM Metrics: {'C': {'precision': 0.3939393939393939, 'recall': 0.6341463414634146, 'f1': 0.48598130841121495, 'number': 451}, 'P': {'precision': 0.6339869281045751, 'recall': 0.609105180533752, 'f1': 0.621297037630104, 'number': 637}, 'overall_precision': 0.5037369207772795, 'overall_recall': 0.6194852941176471, 'overall_f1': 0.5556471558120363, 'overall_accuracy': 0.8174436877946569}
			------------EPOCH 19---------------
Loss:  tensor(18.1587, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1117, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.7270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3183, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.6064, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3702, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.0461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.4919, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.7906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.9599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.7448, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.0835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.4413, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.2842, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1193, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.8498, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.2239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.0077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.7906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.5016, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.1919, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.2976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9226, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.9753, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.9013, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2632, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.5168, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.9788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3482, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39961759082217974, 'recall': 0.5813630041724618, 'f1': 0.4736543909348442, 'number': 719}, 'P': {'precision': 0.5859232175502742, 'recall': 0.6193236714975845, 'f1': 0.6021606387975575, 'number': 1035}, 'overall_precision': 0.49485981308411214, 'overall_recall': 0.6037628278221209, 'overall_f1': 0.5439137134052389, 'overall_accuracy': 0.7009559979046621}
				Near DM Metrics: {'C': {'precision': 0.3443708609271523, 'recall': 0.582089552238806, 'f1': 0.43273231622746183, 'number': 268}, 'P': {'precision': 0.5577395577395577, 'recall': 0.5703517587939698, 'f1': 0.5639751552795031, 'number': 398}, 'overall_precision': 0.44534883720930235, 'overall_recall': 0.575075075075075, 'overall_f1': 0.5019659239842726, 'overall_accuracy': 0.8608346429195041}
				Far DM Metrics: {'C': {'precision': 0.40683229813664595, 'recall': 0.5809312638580931, 'f1': 0.4785388127853881, 'number': 451}, 'P': {'precision': 0.5982658959537572, 'recall': 0.6499215070643642, 'f1': 0.6230248306997742, 'number': 637}, 'overall_precision': 0.5059880239520959, 'overall_recall': 0.6213235294117647, 'overall_f1': 0.5577557755775577, 'overall_accuracy': 0.8193425877422734}
			------------EPOCH 20---------------
Loss:  tensor(15.5431, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.7105, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3699, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.5596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.0777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.0164, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3567, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3113, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.4221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7434, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.9239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4600, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.6317, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.1563, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.2076, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.8911, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.0418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.3342, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.4672, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.9861, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.7483, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.4432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.1027, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9225, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.1445, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.7192, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3975, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0369, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9997, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.1506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1036, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3970037453183521, 'recall': 0.5897079276773296, 'f1': 0.4745383324006715, 'number': 719}, 'P': {'precision': 0.5951492537313433, 'recall': 0.6164251207729469, 'f1': 0.6056003796867584, 'number': 1035}, 'overall_precision': 0.49626168224299066, 'overall_recall': 0.6054732041049031, 'overall_f1': 0.5454545454545455, 'overall_accuracy': 0.7039243932250742}
				Near DM Metrics: {'C': {'precision': 0.3443708609271523, 'recall': 0.582089552238806, 'f1': 0.43273231622746183, 'number': 268}, 'P': {'precision': 0.5757575757575758, 'recall': 0.5728643216080402, 'f1': 0.5743073047858943, 'number': 398}, 'overall_precision': 0.45229681978798586, 'overall_recall': 0.5765765765765766, 'overall_f1': 0.5069306930693069, 'overall_accuracy': 0.8623624934520692}
				Far DM Metrics: {'C': {'precision': 0.4042232277526395, 'recall': 0.5942350332594235, 'f1': 0.48114901256732495, 'number': 451}, 'P': {'precision': 0.6020558002936858, 'recall': 0.6436420722135008, 'f1': 0.622154779969651, 'number': 637}, 'overall_precision': 0.5044642857142857, 'overall_recall': 0.6231617647058824, 'overall_f1': 0.5575657894736842, 'overall_accuracy': 0.8197354635935045}
			------------EPOCH 21---------------
Loss:  tensor(13.8900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.0503, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.4043, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.7686, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.3221, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.4257, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3770, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.2245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.5031, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.3688, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.9359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.6298, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.5077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.2999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.9583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.0821, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.1199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9185, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.1304, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.1760, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.0483, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9428, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.7531, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5714, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1311, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.4470, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3969, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39871086556169427, 'recall': 0.6022253129346314, 'f1': 0.4797783933518005, 'number': 719}, 'P': {'precision': 0.5958254269449715, 'recall': 0.6067632850241546, 'f1': 0.601244614648157, 'number': 1035}, 'overall_precision': 0.4957943925233645, 'overall_recall': 0.604903078677309, 'overall_f1': 0.5449409347714432, 'overall_accuracy': 0.6999301554042257}
				Near DM Metrics: {'C': {'precision': 0.351409978308026, 'recall': 0.6044776119402985, 'f1': 0.4444444444444444, 'number': 268}, 'P': {'precision': 0.5663265306122449, 'recall': 0.5577889447236181, 'f1': 0.5620253164556963, 'number': 398}, 'overall_precision': 0.4501758499413834, 'overall_recall': 0.5765765765765766, 'overall_f1': 0.5055957867017775, 'overall_accuracy': 0.8598524532914266}
				Far DM Metrics: {'C': {'precision': 0.4069069069069069, 'recall': 0.6008869179600886, 'f1': 0.4852282900626678, 'number': 451}, 'P': {'precision': 0.6086956521739131, 'recall': 0.6373626373626373, 'f1': 0.6226993865030676, 'number': 637}, 'overall_precision': 0.5078769692423106, 'overall_recall': 0.6222426470588235, 'overall_f1': 0.5592730276745147, 'overall_accuracy': 0.8179238693906059}
			------------EPOCH 22---------------
Loss:  tensor(12.6275, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.4807, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.6658, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.6174, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.2143, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.9650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.4188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.5786, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.7900, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.1623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.6330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.6262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.8721, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.3342, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.1415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.9749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.4698, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.7351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1593, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.1886, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6467, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.2977, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.5594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.4749, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.1951, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.3561, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.2272, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.1156, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.9312, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.1259, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.2247, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.8621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.0964, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40331491712707185, 'recall': 0.6091794158553546, 'f1': 0.48531855955678666, 'number': 719}, 'P': {'precision': 0.6024904214559387, 'recall': 0.6077294685990338, 'f1': 0.6050986050986051, 'number': 1035}, 'overall_precision': 0.5009389671361503, 'overall_recall': 0.6083238312428735, 'overall_f1': 0.5494335736354274, 'overall_accuracy': 0.7005412956172516}
				Near DM Metrics: {'C': {'precision': 0.3626373626373626, 'recall': 0.6156716417910447, 'f1': 0.45643153526970953, 'number': 268}, 'P': {'precision': 0.5803108808290155, 'recall': 0.5628140703517588, 'f1': 0.5714285714285713, 'number': 398}, 'overall_precision': 0.4625445897740785, 'overall_recall': 0.5840840840840841, 'overall_f1': 0.5162574651625746, 'overall_accuracy': 0.8618168325475817}
				Far DM Metrics: {'C': {'precision': 0.4123867069486405, 'recall': 0.6053215077605322, 'f1': 0.49056603773584906, 'number': 451}, 'P': {'precision': 0.6108597285067874, 'recall': 0.6357927786499215, 'f1': 0.6230769230769232, 'number': 637}, 'overall_precision': 0.5116981132075472, 'overall_recall': 0.6231617647058824, 'overall_f1': 0.5619560712805636, 'overall_accuracy': 0.818011175135324}
			------------EPOCH 23---------------
Loss:  tensor(11.6383, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9929, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.7097, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.7475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.7327, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8880, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.8607, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.0063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.9965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.9972, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.4636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.7954, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.5979, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.4879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.3887, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.0832, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.7460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5774, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.6978, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.0098, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.0426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.6018, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.4395, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6754, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.1274, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8747, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.3306, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.6035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.3253, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.9891, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40730337078651685, 'recall': 0.6050069541029207, 'f1': 0.4868494683827644, 'number': 719}, 'P': {'precision': 0.6040076335877863, 'recall': 0.6115942028985507, 'f1': 0.6077772443590975, 'number': 1035}, 'overall_precision': 0.504725897920605, 'overall_recall': 0.6088939566704675, 'overall_f1': 0.5519379844961241, 'overall_accuracy': 0.7009123450323032}
				Near DM Metrics: {'C': {'precision': 0.3712984054669704, 'recall': 0.6082089552238806, 'f1': 0.4611032531824611, 'number': 268}, 'P': {'precision': 0.5784061696658098, 'recall': 0.5653266331658291, 'f1': 0.5717916137229987, 'number': 398}, 'overall_precision': 0.46859903381642515, 'overall_recall': 0.5825825825825826, 'overall_f1': 0.5194109772423026, 'overall_accuracy': 0.8613584773878121}
				Far DM Metrics: {'C': {'precision': 0.422360248447205, 'recall': 0.6031042128603105, 'f1': 0.4968036529680366, 'number': 451}, 'P': {'precision': 0.6144578313253012, 'recall': 0.640502354788069, 'f1': 0.6272098385857033, 'number': 637}, 'overall_precision': 0.5198776758409785, 'overall_recall': 0.625, 'overall_f1': 0.5676126878130217, 'overall_accuracy': 0.8185568360398114}
			------------EPOCH 24---------------
Loss:  tensor(10.7487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.5171, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.6223, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.9663, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.2886, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6497, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4490, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.4067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.0546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.2653, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.4247, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.2694, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.3596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.7657, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.0459, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.0204, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.4358, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.9149, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.2088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.3371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.6583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3284, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.5100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.6699, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.5707, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9447, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.7216, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.6033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.7474, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.5510, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.5159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.8148, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1635, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4066350710900474, 'recall': 0.5966620305980529, 'f1': 0.4836527621195039, 'number': 719}, 'P': {'precision': 0.6043643263757116, 'recall': 0.6154589371980677, 'f1': 0.6098611775969364, 'number': 1035}, 'overall_precision': 0.505452821242295, 'overall_recall': 0.6077537058152793, 'overall_f1': 0.5519026663215117, 'overall_accuracy': 0.7012179151388162}
				Near DM Metrics: {'C': {'precision': 0.37354988399071926, 'recall': 0.6007462686567164, 'f1': 0.46065808297567956, 'number': 268}, 'P': {'precision': 0.5736040609137056, 'recall': 0.5678391959798995, 'f1': 0.5707070707070707, 'number': 398}, 'overall_precision': 0.4690909090909091, 'overall_recall': 0.581081081081081, 'overall_f1': 0.5191146881287726, 'overall_accuracy': 0.8623843198882486}
				Far DM Metrics: {'C': {'precision': 0.4207221350078493, 'recall': 0.5942350332594235, 'f1': 0.4926470588235293, 'number': 451}, 'P': {'precision': 0.6171171171171171, 'recall': 0.6452119309262166, 'f1': 0.6308518802762856, 'number': 637}, 'overall_precision': 0.5211051419800461, 'overall_recall': 0.6240808823529411, 'overall_f1': 0.5679631953157674, 'overall_accuracy': 0.8192116291251964}
			------------EPOCH 25---------------
Loss:  tensor(9.9683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.1774, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.3351, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.8642, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.7706, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.1106, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.9726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.4201, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.6608, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.1078, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.7625, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.2942, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.7270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(5.8639, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.5696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.5899, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.6645, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(4.6438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5430, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.9903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.8980, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1681, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.1003, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.3781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.0318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.4337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.1387, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8076, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2.9594, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.8159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.9917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.6103, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3.3784, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.6039, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40861244019138754, 'recall': 0.5938803894297635, 'f1': 0.4841269841269841, 'number': 719}, 'P': {'precision': 0.6013257575757576, 'recall': 0.6135265700483091, 'f1': 0.6073648971783836, 'number': 1035}, 'overall_precision': 0.5054735840076154, 'overall_recall': 0.6054732041049031, 'overall_f1': 0.5509727626459144, 'overall_accuracy': 0.7016107909900472}
				Near DM Metrics: {'C': {'precision': 0.37857142857142856, 'recall': 0.5932835820895522, 'f1': 0.4622093023255814, 'number': 268}, 'P': {'precision': 0.5721518987341773, 'recall': 0.5678391959798995, 'f1': 0.5699873896595209, 'number': 398}, 'overall_precision': 0.4723926380368098, 'overall_recall': 0.5780780780780781, 'overall_f1': 0.5199189736664417, 'overall_accuracy': 0.8632792037716082}
				Far DM Metrics: {'C': {'precision': 0.4253968253968254, 'recall': 0.5942350332594235, 'f1': 0.4958371877890842, 'number': 451}, 'P': {'precision': 0.6131934032983508, 'recall': 0.6420722135007849, 'f1': 0.6273006134969324, 'number': 637}, 'overall_precision': 0.5219737856592136, 'overall_recall': 0.6222426470588235, 'overall_f1': 0.5677148846960167, 'overall_accuracy': 0.8194298934869915}
Tokenizer: ../home/arg_mining/4epoch_complete/tokenizer/ Model: ../home/arg_mining/4epoch_complete/model/


		-------------RUN 1-----------
			------------EPOCH 1---------------
Loss:  tensor(2371.1858, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1378.7249, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1701.9084, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1803.6288, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1607.3696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2704.3777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1337.5292, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2054.4480, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2261.4902, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1225.3020, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2496.8088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1792.1758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1723.5198, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1352.3682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2101.4111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1467.6426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1308.8365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2567.3433, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2461.3867, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1890.5024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2585.0933, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1559.8510, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1725.6010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(638.6995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1128.1843, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1105.8372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1612.5621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1342.5781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1307.1206, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1885.4520, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1552.6904, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2142.9531, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2502.2986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3872.9492, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2352.0491, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2836.5916, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.01639344262295082, 'recall': 0.005563282336578581, 'f1': 0.008307372793354102, 'number': 719}, 'P': {'precision': 0.2253269916765755, 'recall': 0.36618357487922704, 'f1': 0.27898417372101586, 'number': 1035}, 'overall_precision': 0.19885773624091382, 'overall_recall': 0.21835803876852908, 'overall_f1': 0.2081521739130435, 'overall_accuracy': 0.5301641348000699}
				Near DM Metrics: {'C': {'precision': 0.010309278350515464, 'recall': 0.0037313432835820895, 'f1': 0.005479452054794521, 'number': 268}, 'P': {'precision': 0.15397350993377484, 'recall': 0.23366834170854273, 'f1': 0.18562874251497008, 'number': 398}, 'overall_precision': 0.1340941512125535, 'overall_recall': 0.14114114114114115, 'overall_f1': 0.13752743233357717, 'overall_accuracy': 0.7219312030731622}
				Far DM Metrics: {'C': {'precision': 0.015, 'recall': 0.0066518847006651885, 'f1': 0.009216589861751152, 'number': 451}, 'P': {'precision': 0.25087719298245614, 'recall': 0.4489795918367347, 'f1': 0.32189082723691614, 'number': 637}, 'overall_precision': 0.21567164179104478, 'overall_recall': 0.265625, 'overall_f1': 0.23805601317957165, 'overall_accuracy': 0.6312860136196962}
			------------EPOCH 2---------------
Loss:  tensor(1767.3442, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1012.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1286.2639, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1369.5349, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1291.8928, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2073.5415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1096.0013, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1680.1580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1868.7085, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(885.2188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1794.3073, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1334.1403, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1356.4644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1064.2576, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1594.8206, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1193.3407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1074.3455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1943.6316, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2103.1599, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1566.7406, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2199.6558, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1247.1423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1533.5410, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(551.0773, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(926.4176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(932.9271, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1275.1965, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1087.8842, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1066.8507, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1559.5868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1219.4308, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1710.3844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2108.4568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(3271.8320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1961.5933, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2506.9172, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.09309623430962342, 'recall': 0.12378303198887343, 'f1': 0.1062686567164179, 'number': 719}, 'P': {'precision': 0.20741758241758243, 'recall': 0.29178743961352654, 'f1': 0.24247290244881575, 'number': 1035}, 'overall_precision': 0.162106135986733, 'overall_recall': 0.22291904218928163, 'overall_f1': 0.18771003360537686, 'overall_accuracy': 0.5918456434433386}
				Near DM Metrics: {'C': {'precision': 0.07239819004524888, 'recall': 0.11940298507462686, 'f1': 0.09014084507042254, 'number': 268}, 'P': {'precision': 0.12477396021699819, 'recall': 0.17336683417085427, 'f1': 0.14511041009463724, 'number': 398}, 'overall_precision': 0.10150753768844221, 'overall_recall': 0.15165165165165165, 'overall_f1': 0.12161348585189645, 'overall_accuracy': 0.748821372446307}
				Far DM Metrics: {'C': {'precision': 0.1, 'recall': 0.12638580931263857, 'f1': 0.11165523996082272, 'number': 451}, 'P': {'precision': 0.25802879291251385, 'recall': 0.36577708006279436, 'f1': 0.30259740259740264, 'number': 637}, 'overall_precision': 0.19687712152070605, 'overall_recall': 0.2665441176470588, 'overall_f1': 0.22647403358063256, 'overall_accuracy': 0.7008250392875851}
			------------EPOCH 3---------------
Loss:  tensor(1464.3777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(821.2258, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1158.2751, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1127.3953, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1098.4319, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1653.0353, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(846.0924, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1290.6370, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1318.5413, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(668.9708, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1404.5605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1064.3232, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1095.4214, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(871.6589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1210.0947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1061.9807, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(904.2756, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1374.5337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1666.3093, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1279.8074, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1806.1726, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(986.1107, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1255.9697, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(458.4443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(772.1079, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(803.1067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1040.2024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(945.1552, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(882.2441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1303.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(889.1358, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1349.5024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1689.4360, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2721.1768, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1566.0784, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2112.2356, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.16969353007945517, 'recall': 0.41585535465924894, 'f1': 0.24103184199919384, 'number': 719}, 'P': {'precision': 0.3627556512378902, 'recall': 0.32560386473429953, 'f1': 0.34317718940936864, 'number': 1035}, 'overall_precision': 0.23634336677814938, 'overall_recall': 0.36259977194982895, 'overall_f1': 0.2861642294713161, 'overall_accuracy': 0.5852322332809499}
				Near DM Metrics: {'C': {'precision': 0.13008130081300814, 'recall': 0.3582089552238806, 'f1': 0.19085487077534793, 'number': 268}, 'P': {'precision': 0.29545454545454547, 'recall': 0.2613065326633166, 'f1': 0.2773333333333334, 'number': 398}, 'overall_precision': 0.1834862385321101, 'overall_recall': 0.3003003003003003, 'overall_f1': 0.22779043280182235, 'overall_accuracy': 0.768617950061114}
				Far DM Metrics: {'C': {'precision': 0.18796296296296297, 'recall': 0.4501108647450111, 'f1': 0.2651861528412802, 'number': 451}, 'P': {'precision': 0.4038128249566724, 'recall': 0.36577708006279436, 'f1': 0.38385502471169686, 'number': 637}, 'overall_precision': 0.2631261315630658, 'overall_recall': 0.4007352941176471, 'overall_f1': 0.3176684881602914, 'overall_accuracy': 0.7220839881264187}
			------------EPOCH 4---------------
Loss:  tensor(1189.3967, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(707.0923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(984.2739, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(922.4860, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(887.2801, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1192.3644, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(539.8958, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(761.2471, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(819.5959, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(527.6802, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1116.7849, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(835.8207, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(854.6503, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(644.9311, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(932.4923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(859.1036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(691.1413, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(896.3051, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1335.5195, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1048.9009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1468.7030, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(759.8573, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(981.5527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(365.0336, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(595.5209, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(663.5155, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(735.9917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(728.6619, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(675.7894, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1024.7800, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(539.0557, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1010.8212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1298.0822, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(2077.2876, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1045.5322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1521.9866, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.2280361757105943, 'recall': 0.4909596662030598, 'f1': 0.3114247904719894, 'number': 719}, 'P': {'precision': 0.4482200647249191, 'recall': 0.26763285024154587, 'f1': 0.3351482153660012, 'number': 1035}, 'overall_precision': 0.29085872576177285, 'overall_recall': 0.35917901938426455, 'overall_f1': 0.32142857142857145, 'overall_accuracy': 0.5979352191374192}
				Near DM Metrics: {'C': {'precision': 0.16422287390029325, 'recall': 0.417910447761194, 'f1': 0.23578947368421055, 'number': 268}, 'P': {'precision': 0.391705069124424, 'recall': 0.2135678391959799, 'f1': 0.2764227642276423, 'number': 398}, 'overall_precision': 0.21913236929922136, 'overall_recall': 0.2957957957957958, 'overall_f1': 0.25175718849840256, 'overall_accuracy': 0.7852933473022525}
				Far DM Metrics: {'C': {'precision': 0.2613882863340564, 'recall': 0.5343680709534369, 'f1': 0.3510560815731974, 'number': 451}, 'P': {'precision': 0.47880299251870323, 'recall': 0.30141287284144425, 'f1': 0.3699421965317919, 'number': 637}, 'overall_precision': 0.327286470143613, 'overall_recall': 0.39797794117647056, 'overall_f1': 0.359187059311489, 'overall_accuracy': 0.7522481229264886}
			------------EPOCH 5---------------
Loss:  tensor(967.6359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(561.6224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(764.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(804.2958, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(758.4650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(792.9879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(365.5375, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(508.7922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(541.6005, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(361.4836, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(724.4417, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(559.7345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(612.2545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(386.0687, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(667.5123, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(682.9824, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(472.4815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(565.1337, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1001.0309, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(794.3971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1025.5886, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(507.4975, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(628.3036, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(285.6962, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(458.3528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(515.1888, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(455.3105, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(574.5680, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(504.6562, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(769.6684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(353.0239, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(845.4713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(867.6448, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1443.2355, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(547.9720, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(900.2101, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.23553719008264462, 'recall': 0.23783031988873435, 'f1': 0.23667820069204148, 'number': 719}, 'P': {'precision': 0.3834106728538283, 'recall': 0.6386473429951691, 'f1': 0.47915911562160207, 'number': 1035}, 'overall_precision': 0.3395918367346939, 'overall_recall': 0.47434435575826683, 'overall_f1': 0.3958135109419601, 'overall_accuracy': 0.5983499214248298}
				Near DM Metrics: {'C': {'precision': 0.14814814814814814, 'recall': 0.19402985074626866, 'f1': 0.16801292407108237, 'number': 268}, 'P': {'precision': 0.3274760383386581, 'recall': 0.5150753768844221, 'f1': 0.400390625, 'number': 398}, 'overall_precision': 0.263050153531218, 'overall_recall': 0.3858858858858859, 'overall_f1': 0.31284236153377964, 'overall_accuracy': 0.8024270997031605}
				Far DM Metrics: {'C': {'precision': 0.27546296296296297, 'recall': 0.2638580931263858, 'f1': 0.26953567383918464, 'number': 451}, 'P': {'precision': 0.41530054644808745, 'recall': 0.7158555729984302, 'f1': 0.5256484149855908, 'number': 637}, 'overall_precision': 0.3758169934640523, 'overall_recall': 0.5284926470588235, 'overall_f1': 0.439266615737204, 'overall_accuracy': 0.7384101623886852}
			------------EPOCH 6---------------
Loss:  tensor(1295.8199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(650.4058, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(962.7970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1089.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(918.5136, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(926.0372, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(366.9176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(383.9463, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(505.8257, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(332.5699, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(637.0450, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(407.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(553.8457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(348.6853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(679.8885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(687.5269, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(345.5473, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(481.5107, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(771.6001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(656.4897, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(729.9100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(385.9747, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(467.2141, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(251.4771, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(411.3692, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.4617, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(388.3300, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(524.2553, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(497.7418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(762.8967, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.6318, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(874.2296, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(645.1320, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1450.3359, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(592.5651, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(799.7133, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.23687089715536105, 'recall': 0.6022253129346314, 'f1': 0.3400078523753436, 'number': 719}, 'P': {'precision': 0.5188679245283019, 'recall': 0.26570048309178745, 'f1': 0.35143769968051114, 'number': 1035}, 'overall_precision': 0.30025445292620867, 'overall_recall': 0.40364880273660203, 'overall_f1': 0.3443579766536965, 'overall_accuracy': 0.5591496420464467}
				Near DM Metrics: {'C': {'precision': 0.18110236220472442, 'recall': 0.5149253731343284, 'f1': 0.26796116504854367, 'number': 268}, 'P': {'precision': 0.4858757062146893, 'recall': 0.21608040201005024, 'f1': 0.2991304347826087, 'number': 398}, 'overall_precision': 0.23855165069222578, 'overall_recall': 0.33633633633633636, 'overall_f1': 0.2791277258566978, 'overall_accuracy': 0.7768028636284268}
				Far DM Metrics: {'C': {'precision': 0.2629233511586453, 'recall': 0.6541019955654102, 'f1': 0.3750794659885569, 'number': 451}, 'P': {'precision': 0.5354107648725213, 'recall': 0.2967032967032967, 'f1': 0.38181818181818183, 'number': 637}, 'overall_precision': 0.328135593220339, 'overall_recall': 0.44485294117647056, 'overall_f1': 0.3776824034334764, 'overall_accuracy': 0.732866247599092}
			------------EPOCH 7---------------
Loss:  tensor(634.7790, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(307.8365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(451.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(491.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(561.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(563.4371, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(262.7039, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.4718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.6217, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(192.3235, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(396.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(280.2863, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(329.5358, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(171.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(393.8575, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(312.6922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.5121, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(368.0932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(737.3782, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(439.0023, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(649.7003, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(264.7394, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(499.1261, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(184.0220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.1959, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(366.6750, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.4626, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(470.2122, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(265.2403, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.1562, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.8568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(623.0231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(417.7411, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(944.4484, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(274.5858, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(623.9496, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.17324561403508773, 'recall': 0.21974965229485396, 'f1': 0.19374616799509503, 'number': 719}, 'P': {'precision': 0.45868465430016864, 'recall': 0.26280193236714977, 'f1': 0.3341523341523342, 'number': 1035}, 'overall_precision': 0.2857142857142857, 'overall_recall': 0.2451539338654504, 'overall_f1': 0.2638846271862535, 'overall_accuracy': 0.5941374192421861}
				Near DM Metrics: {'C': {'precision': 0.13793103448275862, 'recall': 0.208955223880597, 'f1': 0.1661721068249258, 'number': 268}, 'P': {'precision': 0.411214953271028, 'recall': 0.22110552763819097, 'f1': 0.2875816993464052, 'number': 398}, 'overall_precision': 0.23225806451612904, 'overall_recall': 0.21621621621621623, 'overall_f1': 0.223950233281493, 'overall_accuracy': 0.7947878470403352}
				Far DM Metrics: {'C': {'precision': 0.1935483870967742, 'recall': 0.2261640798226164, 'f1': 0.2085889570552147, 'number': 451}, 'P': {'precision': 0.48548812664907653, 'recall': 0.28885400313971743, 'f1': 0.3622047244094488, 'number': 637}, 'overall_precision': 0.31567328918322296, 'overall_recall': 0.26286764705882354, 'overall_f1': 0.2868605817452357, 'overall_accuracy': 0.7379518072289156}
			------------EPOCH 8---------------
Loss:  tensor(849.4597, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(467.2565, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(916.5515, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(697.1108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(627.5489, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(328.4425, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(161.7212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(177.7794, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(148.0793, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(140.1119, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(315.4085, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.1944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(238.3254, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(145.7458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(341.3485, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(222.5654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(245.5452, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(322.8947, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(455.0401, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(461.8298, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(614.2701, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(219.9955, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(303.2389, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(160.9877, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(242.0342, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(325.7656, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(254.5623, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(403.4363, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(247.2522, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(449.2160, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(248.5443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(591.9970, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(858.4285, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1234.0505, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(499.4898, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1010.8920, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.33016877637130804, 'recall': 0.43532684283727396, 'f1': 0.37552489502099584, 'number': 719}, 'P': {'precision': 0.4784910655195235, 'recall': 0.6985507246376812, 'f1': 0.567949725058916, 'number': 1035}, 'overall_precision': 0.42130947539650265, 'overall_recall': 0.5906499429874572, 'overall_f1': 0.49181106100166144, 'overall_accuracy': 0.6735856469355683}
				Near DM Metrics: {'C': {'precision': 0.25727069351230425, 'recall': 0.4291044776119403, 'f1': 0.3216783216783217, 'number': 268}, 'P': {'precision': 0.45454545454545453, 'recall': 0.6532663316582915, 'f1': 0.5360824742268042, 'number': 398}, 'overall_precision': 0.3680078508341511, 'overall_recall': 0.5630630630630631, 'overall_f1': 0.44510385756676557, 'overall_accuracy': 0.8461236249345206}
				Far DM Metrics: {'C': {'precision': 0.3619744058500914, 'recall': 0.43902439024390244, 'f1': 0.3967935871743487, 'number': 451}, 'P': {'precision': 0.49307774227902024, 'recall': 0.7268445839874411, 'f1': 0.5875634517766498, 'number': 637}, 'overall_precision': 0.4448183041722746, 'overall_recall': 0.6075367647058824, 'overall_f1': 0.5135975135975136, 'overall_accuracy': 0.7995023572551074}
			------------EPOCH 9---------------
Loss:  tensor(578.9043, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(284.1621, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(372.7026, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(496.2455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(420.1485, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(220.8716, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(152.5376, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(150.6579, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(179.7533, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(168.5302, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(336.2388, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(260.6920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(354.9605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(312.3463, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(372.9453, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(323.7423, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(382.8152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(941.9088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(634.9325, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(633.6017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(370.8054, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(212.4678, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(234.0516, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.3464, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(180.7506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(202.4871, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(142.8920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.5032, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(138.6487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(222.1077, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.6000, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(365.6152, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(346.5831, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(616.4329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(198.6804, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(395.2830, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.29285714285714287, 'recall': 0.11404728789986092, 'f1': 0.16416416416416418, 'number': 719}, 'P': {'precision': 0.4015748031496063, 'recall': 0.7884057971014493, 'f1': 0.5321160743397457, 'number': 1035}, 'overall_precision': 0.3884083044982699, 'overall_recall': 0.5119726339794755, 'overall_f1': 0.44171175602557794, 'overall_accuracy': 0.6018421512135499}
				Near DM Metrics: {'C': {'precision': 0.1926605504587156, 'recall': 0.07835820895522388, 'f1': 0.1114058355437666, 'number': 268}, 'P': {'precision': 0.3560145808019441, 'recall': 0.7361809045226131, 'f1': 0.47993447993447985, 'number': 398}, 'overall_precision': 0.3369098712446352, 'overall_recall': 0.47147147147147145, 'overall_f1': 0.392991239048811, 'overall_accuracy': 0.820499388859787}
				Far DM Metrics: {'C': {'precision': 0.32105263157894737, 'recall': 0.1352549889135255, 'f1': 0.19032761310452417, 'number': 451}, 'P': {'precision': 0.4325889164598842, 'recall': 0.8210361067503925, 'f1': 0.5666305525460454, 'number': 637}, 'overall_precision': 0.4174410293066476, 'overall_recall': 0.5367647058823529, 'overall_f1': 0.4696421391234419, 'overall_accuracy': 0.7591671031953903}
			------------EPOCH 10---------------
Loss:  tensor(993.3405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(501.7635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(697.3884, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1080.9224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(870.9265, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(768.4825, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(433.4672, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(539.8271, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(307.9713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(297.3060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(568.0676, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(355.8170, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(263.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.4906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(316.2344, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.9589, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(188.1852, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(225.3376, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(522.6195, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(252.7283, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(641.9598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.8434, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(535.5718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(197.9038, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(557.4855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(597.6449, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(640.1868, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(492.8010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(866.9650, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(897.6757, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(445.7630, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1546.1775, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(677.3480, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1180.2732, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(377.7354, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(596.3383, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3383084577114428, 'recall': 0.28372739916550765, 'f1': 0.3086232980332829, 'number': 719}, 'P': {'precision': 0.45987261146496816, 'recall': 0.6975845410628019, 'f1': 0.5543186180422266, 'number': 1035}, 'overall_precision': 0.4261389783709158, 'overall_recall': 0.5279361459521095, 'overall_f1': 0.47160682454800107, 'overall_accuracy': 0.6973764623712241}
				Near DM Metrics: {'C': {'precision': 0.26717557251908397, 'recall': 0.26119402985074625, 'f1': 0.2641509433962264, 'number': 268}, 'P': {'precision': 0.41545893719806765, 'recall': 0.6482412060301508, 'f1': 0.5063788027477919, 'number': 398}, 'overall_precision': 0.3714609286523216, 'overall_recall': 0.4924924924924925, 'overall_f1': 0.4234990316333118, 'overall_accuracy': 0.8512964903090623}
				Far DM Metrics: {'C': {'precision': 0.39296187683284456, 'recall': 0.29711751662971175, 'f1': 0.33838383838383834, 'number': 451}, 'P': {'precision': 0.48893572181243417, 'recall': 0.728414442700157, 'f1': 0.5851197982345523, 'number': 637}, 'overall_precision': 0.4635658914728682, 'overall_recall': 0.5496323529411765, 'overall_f1': 0.5029436501261565, 'overall_accuracy': 0.804064082416623}
			------------EPOCH 11---------------
Loss:  tensor(294.8357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.5315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(244.2685, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(319.3964, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(517.3154, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(393.8829, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(216.7418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(305.7566, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(545.7360, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(263.2872, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(610.0234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(447.1159, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(949.5200, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(643.7986, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1025.0046, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(615.6875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(414.7844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(585.0679, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1039.7281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(929.7163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(1054.8948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(654.6265, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(437.9441, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(198.5853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(368.4140, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(258.2252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(372.2113, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(515.7992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(249.5343, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(339.9818, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(132.2378, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(422.2506, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(349.1733, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(649.0635, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.0335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(294.1353, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.27983777520278097, 'recall': 0.6717663421418637, 'f1': 0.39509202453987724, 'number': 719}, 'P': {'precision': 0.5881458966565349, 'recall': 0.3739130434782609, 'f1': 0.45717660956881273, 'number': 1035}, 'overall_precision': 0.3649328859060403, 'overall_recall': 0.4960091220068415, 'overall_f1': 0.42049299178347027, 'overall_accuracy': 0.6135629474419417}
				Near DM Metrics: {'C': {'precision': 0.2356164383561644, 'recall': 0.6417910447761194, 'f1': 0.344689378757515, 'number': 268}, 'P': {'precision': 0.5596707818930041, 'recall': 0.3417085427135678, 'f1': 0.4243369734789391, 'number': 398}, 'overall_precision': 0.31654676258992803, 'overall_recall': 0.4624624624624625, 'overall_f1': 0.3758389261744966, 'overall_accuracy': 0.8076654443862407}
				Far DM Metrics: {'C': {'precision': 0.29647283126787416, 'recall': 0.6895787139689579, 'f1': 0.41466666666666663, 'number': 451}, 'P': {'precision': 0.6048192771084338, 'recall': 0.3940345368916798, 'f1': 0.47718631178707227, 'number': 637}, 'overall_precision': 0.383879781420765, 'overall_recall': 0.5165441176470589, 'overall_f1': 0.4404388714733542, 'overall_accuracy': 0.7589488388335952}
			------------EPOCH 12---------------
Loss:  tensor(484.9426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(332.7834, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(409.1876, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(350.8954, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(380.5820, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(477.5527, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(182.6017, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.2305, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(141.4847, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(200.8931, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(408.8096, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(322.0302, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(392.6245, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(279.2702, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(346.7398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(458.9911, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(228.0019, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(379.1364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(397.1299, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(370.8964, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(362.5811, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(298.5762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(354.7384, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(164.0240, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(207.4037, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(241.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(199.9952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(214.1158, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(205.9409, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(269.1240, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(109.4350, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(288.9602, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(209.1225, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(446.6249, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(139.7605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(193.3197, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3827893175074184, 'recall': 0.5382475660639777, 'f1': 0.44739884393063584, 'number': 719}, 'P': {'precision': 0.5497835497835498, 'recall': 0.6135265700483091, 'f1': 0.5799086757990867, 'number': 1035}, 'overall_precision': 0.47183748845798706, 'overall_recall': 0.5826681870011402, 'overall_f1': 0.5214285714285714, 'overall_accuracy': 0.7005849484896106}
				Near DM Metrics: {'C': {'precision': 0.2930648769574944, 'recall': 0.48880597014925375, 'f1': 0.3664335664335664, 'number': 268}, 'P': {'precision': 0.5238095238095238, 'recall': 0.5527638190954773, 'f1': 0.5378973105134475, 'number': 398}, 'overall_precision': 0.40484429065743943, 'overall_recall': 0.527027027027027, 'overall_f1': 0.45792563600782776, 'overall_accuracy': 0.8582809498865025}
				Far DM Metrics: {'C': {'precision': 0.43537414965986393, 'recall': 0.5676274944567627, 'f1': 0.492781520692974, 'number': 451}, 'P': {'precision': 0.564625850340136, 'recall': 0.6514913657770801, 'f1': 0.6049562682215743, 'number': 637}, 'overall_precision': 0.5071806500377929, 'overall_recall': 0.6167279411764706, 'overall_f1': 0.5566155122355869, 'overall_accuracy': 0.8136677143356033}
			------------EPOCH 13---------------
Loss:  tensor(200.6605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(121.1592, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(177.2392, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(172.2768, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(270.4482, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(128.4952, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(82.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.6120, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.3110, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(88.8909, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(169.3928, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.9365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(157.7857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(80.3220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(170.2992, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(95.7923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(88.8407, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(133.2990, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(185.8766, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(178.8501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(272.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(111.9581, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(165.0995, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(86.0948, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(155.9486, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(138.1526, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(129.0004, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(226.7815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(108.9920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(183.4834, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(61.2857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(206.7059, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(93.4129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(273.9545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(69.5630, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(144.3599, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.40767634854771784, 'recall': 0.5465924895688457, 'f1': 0.46702317290552586, 'number': 719}, 'P': {'precision': 0.5547703180212014, 'recall': 0.6067632850241546, 'f1': 0.5796031379787725, 'number': 1035}, 'overall_precision': 0.48711832061068705, 'overall_recall': 0.5820980615735462, 'overall_f1': 0.5303896103896104, 'overall_accuracy': 0.7106905884407194}
				Near DM Metrics: {'C': {'precision': 0.3480392156862745, 'recall': 0.5298507462686567, 'f1': 0.42011834319526625, 'number': 268}, 'P': {'precision': 0.5117924528301887, 'recall': 0.5452261306532663, 'f1': 0.5279805352798053, 'number': 398}, 'overall_precision': 0.43149038461538464, 'overall_recall': 0.539039039039039, 'overall_f1': 0.479305740987984, 'overall_accuracy': 0.858346429195041}
				Far DM Metrics: {'C': {'precision': 0.449820788530466, 'recall': 0.5565410199556541, 'f1': 0.49752229930624375, 'number': 451}, 'P': {'precision': 0.5805084745762712, 'recall': 0.6452119309262166, 'f1': 0.6111524163568772, 'number': 637}, 'overall_precision': 0.5229067930489731, 'overall_recall': 0.6084558823529411, 'overall_f1': 0.562446898895497, 'overall_accuracy': 0.8160904487515278}
			------------EPOCH 14---------------
Loss:  tensor(142.7710, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(84.4630, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(130.3461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(120.0857, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(148.6548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(75.5845, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.3548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.2394, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.6550, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.0725, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(76.6743, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(59.8106, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(57.9166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5219, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(74.5404, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.0878, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(51.0238, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(64.9405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(91.6281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(87.4361, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(88.7273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.2438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.8961, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.8215, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(98.4695, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.3585, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.1315, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(104.0305, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.4669, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(92.0634, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.4210, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.5231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.8823, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(212.8386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.8710, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(103.9403, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3442379182156134, 'recall': 0.6439499304589708, 'f1': 0.4486434108527132, 'number': 719}, 'P': {'precision': 0.6092636579572447, 'recall': 0.4956521739130435, 'f1': 0.5466169419286094, 'number': 1035}, 'overall_precision': 0.4462734339277549, 'overall_recall': 0.556442417331813, 'overall_f1': 0.4953057599594011, 'overall_accuracy': 0.6729745067225423}
				Near DM Metrics: {'C': {'precision': 0.30036630036630035, 'recall': 0.6119402985074627, 'f1': 0.4029484029484029, 'number': 268}, 'P': {'precision': 0.565359477124183, 'recall': 0.43467336683417085, 'f1': 0.4914772727272727, 'number': 398}, 'overall_precision': 0.3955399061032864, 'overall_recall': 0.506006006006006, 'overall_f1': 0.4440052700922266, 'overall_accuracy': 0.8377204470054129}
				Far DM Metrics: {'C': {'precision': 0.3742177722152691, 'recall': 0.6629711751662971, 'f1': 0.47840000000000005, 'number': 451}, 'P': {'precision': 0.6343283582089553, 'recall': 0.533751962323391, 'f1': 0.5797101449275363, 'number': 637}, 'overall_precision': 0.4786516853932584, 'overall_recall': 0.5873161764705882, 'overall_f1': 0.5274453157243086, 'overall_accuracy': 0.8001353239043129}
			------------EPOCH 15---------------
Loss:  tensor(108.8578, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.5070, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(116.8153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(85.8287, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(83.6636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(67.5460, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.2374, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.7838, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.8851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7067, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.4042, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.8276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.8330, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.8289, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.6529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.7732, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.8607, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.4611, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.6340, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.8767, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(60.6345, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.4683, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(41.0271, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.9729, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.8224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.5294, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.7199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(71.3835, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.8269, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(72.2848, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.9944, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.2844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.2055, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(123.6451, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.0386, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.0365, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3990654205607477, 'recall': 0.5938803894297635, 'f1': 0.4773616545556177, 'number': 719}, 'P': {'precision': 0.5711678832116789, 'recall': 0.6048309178743961, 'f1': 0.5875175973721257, 'number': 1035}, 'overall_precision': 0.48614958448753465, 'overall_recall': 0.6003420752565565, 'overall_f1': 0.5372448979591838, 'overall_accuracy': 0.6981185612013271}
				Near DM Metrics: {'C': {'precision': 0.35555555555555557, 'recall': 0.5970149253731343, 'f1': 0.4456824512534818, 'number': 268}, 'P': {'precision': 0.538083538083538, 'recall': 0.550251256281407, 'f1': 0.5440993788819876, 'number': 398}, 'overall_precision': 0.44224037339556593, 'overall_recall': 0.5690690690690691, 'overall_f1': 0.4977019041365726, 'overall_accuracy': 0.8531517373843199}
				Far DM Metrics: {'C': {'precision': 0.4306451612903226, 'recall': 0.5920177383592018, 'f1': 0.4985994397759103, 'number': 451}, 'P': {'precision': 0.590711175616836, 'recall': 0.6389324960753532, 'f1': 0.6138763197586725, 'number': 637}, 'overall_precision': 0.5148968678380443, 'overall_recall': 0.6194852941176471, 'overall_f1': 0.5623696287025448, 'overall_accuracy': 0.8118561201327047}
			------------EPOCH 16---------------
Loss:  tensor(75.4920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.3341, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(62.8577, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(70.4252, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(65.9063, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(48.0008, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.9477, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.0697, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.1479, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.9494, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.3444, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.3060, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.7596, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.8875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.8199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.0912, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.9903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(54.8782, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.8200, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(49.4001, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.8982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.7583, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.8231, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.9054, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.2957, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.1547, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(55.4528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2129, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.3227, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.1693, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(50.1356, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.1126, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(97.3363, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.3429, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.6189, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39906976744186046, 'recall': 0.5966620305980529, 'f1': 0.47826086956521735, 'number': 719}, 'P': {'precision': 0.5879494655004859, 'recall': 0.5845410628019324, 'f1': 0.5862403100775194, 'number': 1035}, 'overall_precision': 0.4914448669201521, 'overall_recall': 0.5895096921322691, 'overall_f1': 0.5360290305857958, 'overall_accuracy': 0.7017199231709447}
				Near DM Metrics: {'C': {'precision': 0.3597285067873303, 'recall': 0.5932835820895522, 'f1': 0.447887323943662, 'number': 268}, 'P': {'precision': 0.5647668393782384, 'recall': 0.5477386934673367, 'f1': 0.5561224489795918, 'number': 398}, 'overall_precision': 0.4553140096618358, 'overall_recall': 0.566066066066066, 'overall_f1': 0.5046854082998661, 'overall_accuracy': 0.8555962982364239}
				Far DM Metrics: {'C': {'precision': 0.4265402843601896, 'recall': 0.5986696230598669, 'f1': 0.4981549815498155, 'number': 451}, 'P': {'precision': 0.6018662519440124, 'recall': 0.6075353218210361, 'f1': 0.6046875, 'number': 637}, 'overall_precision': 0.5148902821316614, 'overall_recall': 0.6038602941176471, 'overall_f1': 0.5558375634517766, 'overall_accuracy': 0.8131438798672953}
			------------EPOCH 17---------------
Loss:  tensor(54.1719, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.3493, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(46.7024, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(45.6539, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.1997, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.5987, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.2101, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.7786, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.6572, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2501, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.9718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.9457, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.9405, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.6200, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.9008, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.5937, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4303, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.9716, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(42.5169, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.0260, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.3362, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7939, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7622, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2971, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.0329, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.2890, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.3490, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(53.0989, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.0161, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.8673, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(78.6418, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.4983, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(39.4169, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3823008849557522, 'recall': 0.6008344923504868, 'f1': 0.4672796106003245, 'number': 719}, 'P': {'precision': 0.5792682926829268, 'recall': 0.5507246376811594, 'f1': 0.564635958395245, 'number': 1035}, 'overall_precision': 0.4739829706717124, 'overall_recall': 0.5712656784492588, 'overall_f1': 0.5180972078593589, 'overall_accuracy': 0.6937751004016064}
				Near DM Metrics: {'C': {'precision': 0.34475374732334046, 'recall': 0.6007462686567164, 'f1': 0.4380952380952381, 'number': 268}, 'P': {'precision': 0.5633802816901409, 'recall': 0.5025125628140703, 'f1': 0.5312084993359893, 'number': 398}, 'overall_precision': 0.4391727493917275, 'overall_recall': 0.5420420420420421, 'overall_f1': 0.4852150537634409, 'overall_accuracy': 0.8504889121704208}
				Far DM Metrics: {'C': {'precision': 0.40874811463046756, 'recall': 0.6008869179600886, 'f1': 0.4865350089766606, 'number': 451}, 'P': {'precision': 0.5882352941176471, 'recall': 0.5808477237048666, 'f1': 0.584518167456556, 'number': 637}, 'overall_precision': 0.49613003095975233, 'overall_recall': 0.5891544117647058, 'overall_f1': 0.5386554621848739, 'overall_accuracy': 0.8076654443862407}
			------------EPOCH 18---------------
Loss:  tensor(43.0515, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.2713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.8534, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.7136, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.3546, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.3919, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.9885, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.7095, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.9281, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.2192, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.7820, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.7909, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.5008, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.1195, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.4132, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.9912, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.4851, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.7723, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.4138, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.3622, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.5844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7718, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6841, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.0273, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.7518, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.8461, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.6894, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8169, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(47.4760, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.6769, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(35.7037, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(37.4142, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(63.8498, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2499, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.6458, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3881401617250674, 'recall': 0.6008344923504868, 'f1': 0.47161572052401746, 'number': 719}, 'P': {'precision': 0.588, 'recall': 0.5681159420289855, 'f1': 0.5778869778869778, 'number': 1035}, 'overall_precision': 0.48272598201609085, 'overall_recall': 0.5815279361459521, 'overall_f1': 0.5275407292474786, 'overall_accuracy': 0.6946045049764275}
				Near DM Metrics: {'C': {'precision': 0.3544857768052516, 'recall': 0.6044776119402985, 'f1': 0.44689655172413795, 'number': 268}, 'P': {'precision': 0.5679347826086957, 'recall': 0.5251256281407035, 'f1': 0.5456919060052219, 'number': 398}, 'overall_precision': 0.4496969696969697, 'overall_recall': 0.5570570570570571, 'overall_f1': 0.4976525821596244, 'overall_accuracy': 0.8522786799371399}
				Far DM Metrics: {'C': {'precision': 0.4115853658536585, 'recall': 0.5986696230598669, 'f1': 0.4878048780487805, 'number': 451}, 'P': {'precision': 0.5996835443037974, 'recall': 0.5949764521193093, 'f1': 0.5973207249802994, 'number': 637}, 'overall_precision': 0.5038819875776398, 'overall_recall': 0.5965073529411765, 'overall_f1': 0.5462962962962964, 'overall_accuracy': 0.8072507420988301}
			------------EPOCH 19---------------
Loss:  tensor(35.0082, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7555, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.5855, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.2834, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.0475, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.1212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.9035, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.7065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.8438, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7819, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.7171, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8674, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.7673, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.7875, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.3155, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2382, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.6297, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.4700, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.5033, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.0704, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1010, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.4862, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.2928, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7631, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(32.2752, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.2128, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(43.7183, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.5156, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.1443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.0287, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(52.4270, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.4728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.1041, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3956043956043956, 'recall': 0.6008344923504868, 'f1': 0.4770844837106571, 'number': 719}, 'P': {'precision': 0.5842259006815969, 'recall': 0.5797101449275363, 'f1': 0.5819592628516005, 'number': 1035}, 'overall_precision': 0.487022180273714, 'overall_recall': 0.5883694412770809, 'overall_f1': 0.5329202168861347, 'overall_accuracy': 0.6984896106163786}
				Near DM Metrics: {'C': {'precision': 0.3590308370044053, 'recall': 0.6082089552238806, 'f1': 0.4515235457063712, 'number': 268}, 'P': {'precision': 0.56282722513089, 'recall': 0.5402010050251256, 'f1': 0.5512820512820511, 'number': 398}, 'overall_precision': 0.45215311004784686, 'overall_recall': 0.5675675675675675, 'overall_f1': 0.5033288948069241, 'overall_accuracy': 0.8550942902042954}
				Far DM Metrics: {'C': {'precision': 0.4216300940438871, 'recall': 0.5964523281596452, 'f1': 0.49403122130394855, 'number': 451}, 'P': {'precision': 0.5968992248062015, 'recall': 0.6043956043956044, 'f1': 0.6006240249609984, 'number': 637}, 'overall_precision': 0.509742790335152, 'overall_recall': 0.6011029411764706, 'overall_f1': 0.5516659637283846, 'overall_accuracy': 0.8092369477911646}
			------------EPOCH 20---------------
Loss:  tensor(30.2740, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2262, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.0462, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.9278, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.9234, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(31.2006, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.5313, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1436, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.3799, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.9535, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.5859, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.7346, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.7236, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5906, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5242, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6662, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3762, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.4820, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.8819, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.4335, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.0859, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.4352, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.6896, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.1923, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4980, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8415, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(30.7167, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0736, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(40.2905, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3684, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(27.7828, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.1699, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(44.3161, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4294, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.0790, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3946146703806871, 'recall': 0.5910987482614742, 'f1': 0.4732739420935412, 'number': 719}, 'P': {'precision': 0.5786948176583493, 'recall': 0.5826086956521739, 'f1': 0.5806451612903225, 'number': 1035}, 'overall_precision': 0.48513449740443604, 'overall_recall': 0.5860889395667047, 'overall_f1': 0.5308546346501419, 'overall_accuracy': 0.6985769163610965}
				Near DM Metrics: {'C': {'precision': 0.36343115124153497, 'recall': 0.6007462686567164, 'f1': 0.4528832630098453, 'number': 268}, 'P': {'precision': 0.5578406169665809, 'recall': 0.5452261306532663, 'f1': 0.5514612452350698, 'number': 398}, 'overall_precision': 0.4543269230769231, 'overall_recall': 0.5675675675675675, 'overall_f1': 0.5046728971962617, 'overall_accuracy': 0.8557272568535009}
				Far DM Metrics: {'C': {'precision': 0.416403785488959, 'recall': 0.5853658536585366, 'f1': 0.4866359447004609, 'number': 451}, 'P': {'precision': 0.5911179173047473, 'recall': 0.6059654631083202, 'f1': 0.5984496124031008, 'number': 637}, 'overall_precision': 0.5050505050505051, 'overall_recall': 0.5974264705882353, 'overall_f1': 0.5473684210526316, 'overall_accuracy': 0.8087131133228567}
			------------EPOCH 21---------------
Loss:  tensor(26.7357, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.8807, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0648, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.3236, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.0188, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.4781, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.6544, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.8398, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1224, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.5573, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5879, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.8449, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.8758, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7350, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.2107, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8220, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6212, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7539, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.5256, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.5627, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.1207, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8514, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.2276, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.3999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.8545, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.9151, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(26.7426, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.0844, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(36.8985, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6131, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.8147, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.9513, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(38.5626, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.6780, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.7683, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.396854764107308, 'recall': 0.5966620305980529, 'f1': 0.4766666666666666, 'number': 719}, 'P': {'precision': 0.5827686350435625, 'recall': 0.5816425120772947, 'f1': 0.5822050290135397, 'number': 1035}, 'overall_precision': 0.48770104068117315, 'overall_recall': 0.5877993158494869, 'overall_f1': 0.5330920372285419, 'overall_accuracy': 0.7008468657237646}
				Near DM Metrics: {'C': {'precision': 0.359375, 'recall': 0.6007462686567164, 'f1': 0.44972067039106145, 'number': 268}, 'P': {'precision': 0.561038961038961, 'recall': 0.542713567839196, 'f1': 0.5517241379310346, 'number': 398}, 'overall_precision': 0.4525810324129652, 'overall_recall': 0.566066066066066, 'overall_f1': 0.5030020013342228, 'overall_accuracy': 0.8553998603108085}
				Far DM Metrics: {'C': {'precision': 0.42338072669826227, 'recall': 0.5942350332594235, 'f1': 0.49446494464944646, 'number': 451}, 'P': {'precision': 0.595679012345679, 'recall': 0.6059654631083202, 'f1': 0.6007782101167315, 'number': 637}, 'overall_precision': 0.5105386416861827, 'overall_recall': 0.6011029411764706, 'overall_f1': 0.5521317011397213, 'overall_accuracy': 0.8107647983237297}
			------------EPOCH 22---------------
Loss:  tensor(24.0286, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.0088, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.6734, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.5819, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5800, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(24.7458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.6009, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.3476, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7323, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.9815, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.5856, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.8432, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.2777, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8548, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1321, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1341, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.1295, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2988, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.4605, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.7920, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.2903, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.5130, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.8880, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5728, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5215, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3524, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.6529, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2115, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(33.2873, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.2167, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.3484, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.4534, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(34.0455, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3515, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.7123, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.4001865671641791, 'recall': 0.5966620305980529, 'f1': 0.47906197654941374, 'number': 719}, 'P': {'precision': 0.5771812080536913, 'recall': 0.5816425120772947, 'f1': 0.579403272377286, 'number': 1035}, 'overall_precision': 0.4874704491725768, 'overall_recall': 0.5877993158494869, 'overall_f1': 0.5329542517446367, 'overall_accuracy': 0.7015889645538677}
				Near DM Metrics: {'C': {'precision': 0.36054421768707484, 'recall': 0.5932835820895522, 'f1': 0.44851904090267986, 'number': 268}, 'P': {'precision': 0.5524296675191815, 'recall': 0.542713567839196, 'f1': 0.5475285171102662, 'number': 398}, 'overall_precision': 0.45072115384615385, 'overall_recall': 0.5630630630630631, 'overall_f1': 0.500667556742323, 'overall_accuracy': 0.8557490832896805}
				Far DM Metrics: {'C': {'precision': 0.42789223454833597, 'recall': 0.5986696230598669, 'f1': 0.49907578558225507, 'number': 451}, 'P': {'precision': 0.5920245398773006, 'recall': 0.6059654631083202, 'f1': 0.5989138867339022, 'number': 637}, 'overall_precision': 0.5113016367887763, 'overall_recall': 0.6029411764705882, 'overall_f1': 0.5533530156052299, 'overall_accuracy': 0.8106556661428322}
			------------EPOCH 23---------------
Loss:  tensor(21.4525, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.1938, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.0788, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3654, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.3374, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(22.4580, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.8306, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.2041, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7969, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.9350, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.9163, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.2737, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.9831, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.5108, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.7536, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.2551, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.5528, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.8365, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.1404, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.6932, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.1770, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5065, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.3427, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.6962, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9015, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.4440, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.1040, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0364, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.3509, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(28.6820, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0153, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.1282, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.5921, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(29.9794, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.1184, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.0024, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3996265172735761, 'recall': 0.5952712100139083, 'f1': 0.4782122905027933, 'number': 719}, 'P': {'precision': 0.5756704980842912, 'recall': 0.5806763285024155, 'f1': 0.5781625781625781, 'number': 1035}, 'overall_precision': 0.48652482269503544, 'overall_recall': 0.5866590649942988, 'overall_f1': 0.5319203928663737, 'overall_accuracy': 0.7024183691286887}
				Near DM Metrics: {'C': {'precision': 0.3574660633484163, 'recall': 0.5895522388059702, 'f1': 0.4450704225352113, 'number': 268}, 'P': {'precision': 0.5443037974683544, 'recall': 0.5402010050251256, 'f1': 0.5422446406052964, 'number': 398}, 'overall_precision': 0.44563918757467147, 'overall_recall': 0.56006006006006, 'overall_f1': 0.4963406520292748, 'overall_accuracy': 0.8546795879168849}
				Far DM Metrics: {'C': {'precision': 0.4292527821939587, 'recall': 0.5986696230598669, 'f1': 0.5, 'number': 451}, 'P': {'precision': 0.5947611710323575, 'recall': 0.6059654631083202, 'f1': 0.6003110419906688, 'number': 637}, 'overall_precision': 0.513302034428795, 'overall_recall': 0.6029411764705882, 'overall_f1': 0.5545224006762468, 'overall_accuracy': 0.8112231534834992}
			------------EPOCH 24---------------
Loss:  tensor(18.3582, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.6922, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.7322, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.3216, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.3208, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(21.0487, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.3045, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.8751, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.9976, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.0190, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4203, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.7636, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.8925, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.0111, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.8600, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.5696, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.0397, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7604, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.2826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3087, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.9999, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.7109, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.2996, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.6678, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.6161, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.5646, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.1853, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.8493, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.4713, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.6416, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.0176, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(18.1787, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(20.2810, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(25.9826, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.9568, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.5729, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.3985102420856611, 'recall': 0.5952712100139083, 'f1': 0.4774121583937535, 'number': 719}, 'P': {'precision': 0.5779904306220096, 'recall': 0.5835748792270531, 'f1': 0.5807692307692307, 'number': 1035}, 'overall_precision': 0.487022180273714, 'overall_recall': 0.5883694412770809, 'overall_f1': 0.5329202168861347, 'overall_accuracy': 0.7032041208311507}
				Near DM Metrics: {'C': {'precision': 0.35033259423503327, 'recall': 0.5895522388059702, 'f1': 0.439499304589708, 'number': 268}, 'P': {'precision': 0.5468354430379747, 'recall': 0.542713567839196, 'f1': 0.5447667087011351, 'number': 398}, 'overall_precision': 0.44208037825059104, 'overall_recall': 0.5615615615615616, 'overall_f1': 0.49470899470899476, 'overall_accuracy': 0.8542648856294744}
				Far DM Metrics: {'C': {'precision': 0.4333868378812199, 'recall': 0.5986696230598669, 'f1': 0.5027932960893854, 'number': 451}, 'P': {'precision': 0.5969230769230769, 'recall': 0.609105180533752, 'f1': 0.6029526029526029, 'number': 637}, 'overall_precision': 0.5168892380204242, 'overall_recall': 0.6047794117647058, 'overall_f1': 0.5573909360440491, 'overall_accuracy': 0.8120743844944998}
			------------EPOCH 25---------------
Loss:  tensor(16.6458, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4888, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.5867, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3542, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.4769, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.8751, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9255, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.8556, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.2628, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(7.1702, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.0865, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4179, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.9848, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.5917, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(8.5982, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9240, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.6064, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(14.8512, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(12.6025, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.1213, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0682, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.9676, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.3429, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(9.7443, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(11.4746, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(6.8037, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(13.4598, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(17.0199, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.6166, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.6736, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.2197, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(15.7765, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(19.3118, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(23.2301, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(10.9100, device='cuda:0', grad_fn=<DivBackward0>)
Loss:  tensor(16.3077, device='cuda:0', grad_fn=<DivBackward0>)
				 {'C': {'precision': 0.39776951672862454, 'recall': 0.5952712100139083, 'f1': 0.47688022284122566, 'number': 719}, 'P': {'precision': 0.5795019157088123, 'recall': 0.5845410628019324, 'f1': 0.5820105820105821, 'number': 1035}, 'overall_precision': 0.4872641509433962, 'overall_recall': 0.5889395667046751, 'overall_f1': 0.5332989158492515, 'overall_accuracy': 0.7022001047668937}
				Near DM Metrics: {'C': {'precision': 0.3495575221238938, 'recall': 0.5895522388059702, 'f1': 0.4388888888888889, 'number': 268}, 'P': {'precision': 0.5532994923857868, 'recall': 0.5477386934673367, 'f1': 0.5505050505050505, 'number': 398}, 'overall_precision': 0.4444444444444444, 'overall_recall': 0.5645645645645646, 'overall_f1': 0.49735449735449744, 'overall_accuracy': 0.8553998603108085}
				Far DM Metrics: {'C': {'precision': 0.4326923076923077, 'recall': 0.5986696230598669, 'f1': 0.5023255813953489, 'number': 451}, 'P': {'precision': 0.5953846153846154, 'recall': 0.6075353218210361, 'f1': 0.6013986013986015, 'number': 637}, 'overall_precision': 0.5156985871271585, 'overall_recall': 0.6038602941176471, 'overall_f1': 0.5563082133784928, 'overall_accuracy': 0.8119652523136023}
