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results 1 (epoch=10).txt
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Epoch: [ 1], step: [10], time: [3.1832], loss: [0.00109150]
Epoch: [ 1], step: [20], time: [5.8541], loss: [0.00081011]
Epoch: [ 1], step: [30], time: [8.7592], loss: [0.00075122]
Epoch: [ 1], step: [40], time: [11.4306], loss: [0.00255910]
Epoch: [ 1], step: [50], time: [14.0954], loss: [0.00096062]
Epoch: [ 1], step: [60], time: [16.6944], loss: [0.00033346]
Epoch: [ 1], step: [70], time: [19.3455], loss: [0.00175632]
Epoch: [ 1], step: [80], time: [22.1597], loss: [0.00027418]
Epoch: [ 1], step: [90], time: [24.8420], loss: [0.00422179]
Epoch: [ 1], step: [100], time: [27.4865], loss: [0.00770429]
Epoch: [ 1], step: [110], time: [30.3129], loss: [0.00030762]
Epoch: [ 1], step: [120], time: [32.9799], loss: [0.00147304]
Epoch: [ 1], step: [130], time: [36.4880], loss: [0.00093157]
Epoch: [ 1], step: [140], time: [39.7386], loss: [0.00035775]
Epoch: [ 1], step: [150], time: [42.9301], loss: [0.00089208]
Epoch: [ 1], step: [160], time: [45.5397], loss: [0.00456960]
Epoch: [ 1], step: [170], time: [48.1329], loss: [0.00040236]
Epoch: [ 2], step: [180], time: [50.7297], loss: [0.00109150]
Epoch: [ 2], step: [190], time: [53.3229], loss: [0.00081011]
Epoch: [ 2], step: [200], time: [55.9545], loss: [0.00075122]
Epoch: [ 2], step: [210], time: [58.6344], loss: [0.00255910]
Epoch: [ 2], step: [220], time: [61.2803], loss: [0.00096062]
Epoch: [ 2], step: [230], time: [64.4153], loss: [0.00033346]
Epoch: [ 2], step: [240], time: [67.0607], loss: [0.00175632]
Epoch: [ 2], step: [250], time: [70.0125], loss: [0.00027418]
Epoch: [ 2], step: [260], time: [72.9567], loss: [0.00422179]
Epoch: [ 2], step: [270], time: [75.7136], loss: [0.00770429]
Epoch: [ 2], step: [280], time: [78.7561], loss: [0.00030762]
Epoch: [ 2], step: [290], time: [81.4272], loss: [0.00147304]
Epoch: [ 2], step: [300], time: [84.0620], loss: [0.00093157]
Epoch: [ 2], step: [310], time: [86.7260], loss: [0.00035775]
Epoch: [ 2], step: [320], time: [89.3872], loss: [0.00089208]
Epoch: [ 2], step: [330], time: [92.0224], loss: [0.00456960]
Epoch: [ 2], step: [340], time: [94.6635], loss: [0.00040236]
Epoch: [ 3], step: [350], time: [97.3100], loss: [0.00109150]
Epoch: [ 3], step: [360], time: [99.9411], loss: [0.00081011]
Epoch: [ 3], step: [370], time: [102.5906], loss: [0.00075122]
Epoch: [ 3], step: [380], time: [105.2145], loss: [0.00255910]
Epoch: [ 3], step: [390], time: [107.8313], loss: [0.00096062]
Epoch: [ 3], step: [400], time: [110.5087], loss: [0.00033346]
Epoch: [ 3], step: [410], time: [113.1519], loss: [0.00175632]
Epoch: [ 3], step: [420], time: [115.8120], loss: [0.00027418]
Epoch: [ 3], step: [430], time: [118.5348], loss: [0.00422178]
Epoch: [ 3], step: [440], time: [121.1997], loss: [0.00770429]
Epoch: [ 3], step: [450], time: [123.8174], loss: [0.00030762]
Epoch: [ 3], step: [460], time: [126.4598], loss: [0.00147304]
Epoch: [ 3], step: [470], time: [129.1044], loss: [0.00093157]
Epoch: [ 3], step: [480], time: [131.7415], loss: [0.00035775]
Epoch: [ 3], step: [490], time: [134.3598], loss: [0.00089208]
Epoch: [ 3], step: [500], time: [136.9994], loss: [0.00456959]
Epoch: [ 3], step: [510], time: [140.1085], loss: [0.00040236]
Epoch: [ 4], step: [520], time: [142.7282], loss: [0.00109150]
Epoch: [ 4], step: [530], time: [145.3388], loss: [0.00081011]
Epoch: [ 4], step: [540], time: [147.9507], loss: [0.00075122]
Epoch: [ 4], step: [550], time: [150.5808], loss: [0.00255910]
Epoch: [ 4], step: [560], time: [153.1718], loss: [0.00096062]
Epoch: [ 4], step: [570], time: [155.7998], loss: [0.00033346]
Epoch: [ 4], step: [580], time: [158.4205], loss: [0.00175631]
Epoch: [ 4], step: [590], time: [161.0451], loss: [0.00027418]
Epoch: [ 4], step: [600], time: [163.6830], loss: [0.00422178]
Epoch: [ 4], step: [610], time: [166.3211], loss: [0.00770429]
Epoch: [ 4], step: [620], time: [168.9666], loss: [0.00030762]
Epoch: [ 4], step: [630], time: [171.6331], loss: [0.00147304]
Epoch: [ 4], step: [640], time: [174.2385], loss: [0.00093157]
Epoch: [ 4], step: [650], time: [176.8611], loss: [0.00035775]
Epoch: [ 4], step: [660], time: [179.5627], loss: [0.00089208]
Epoch: [ 4], step: [670], time: [182.2271], loss: [0.00456959]
Epoch: [ 4], step: [680], time: [184.8639], loss: [0.00040236]
Epoch: [ 5], step: [690], time: [187.4930], loss: [0.00109150]
Epoch: [ 5], step: [700], time: [190.1219], loss: [0.00081011]
Epoch: [ 5], step: [710], time: [192.7360], loss: [0.00075122]
Epoch: [ 5], step: [720], time: [195.3569], loss: [0.00255910]
Epoch: [ 5], step: [730], time: [197.9700], loss: [0.00096062]
Epoch: [ 5], step: [740], time: [200.5856], loss: [0.00033346]
Epoch: [ 5], step: [750], time: [203.2062], loss: [0.00175631]
Epoch: [ 5], step: [760], time: [205.8290], loss: [0.00027418]
Epoch: [ 5], step: [770], time: [208.4478], loss: [0.00422178]
Epoch: [ 5], step: [780], time: [211.0528], loss: [0.00770429]
Epoch: [ 5], step: [790], time: [213.7059], loss: [0.00030762]
Epoch: [ 5], step: [800], time: [216.3441], loss: [0.00147304]
Epoch: [ 5], step: [810], time: [218.9727], loss: [0.00093157]
Epoch: [ 5], step: [820], time: [221.6084], loss: [0.00035775]
Epoch: [ 5], step: [830], time: [224.2314], loss: [0.00089208]
Epoch: [ 5], step: [840], time: [226.8510], loss: [0.00456959]
Epoch: [ 5], step: [850], time: [229.4956], loss: [0.00040236]
Epoch: [ 6], step: [860], time: [232.1000], loss: [0.00109150]
Epoch: [ 6], step: [870], time: [234.7331], loss: [0.00081011]
Epoch: [ 6], step: [880], time: [237.3471], loss: [0.00075122]
Epoch: [ 6], step: [890], time: [239.9986], loss: [0.00255910]
Epoch: [ 6], step: [900], time: [242.7012], loss: [0.00096062]
Epoch: [ 6], step: [910], time: [245.3269], loss: [0.00033346]
Epoch: [ 6], step: [920], time: [247.9592], loss: [0.00175631]
Epoch: [ 6], step: [930], time: [250.6044], loss: [0.00027418]
Epoch: [ 6], step: [940], time: [253.2345], loss: [0.00422178]
Epoch: [ 6], step: [950], time: [255.8582], loss: [0.00770428]
Epoch: [ 6], step: [960], time: [258.4867], loss: [0.00030762]
Epoch: [ 6], step: [970], time: [261.1148], loss: [0.00147304]
Epoch: [ 6], step: [980], time: [263.7399], loss: [0.00093157]
Epoch: [ 6], step: [990], time: [266.3944], loss: [0.00035775]
Epoch: [ 6], step: [1000], time: [269.0294], loss: [0.00089208]
Epoch: [ 6], step: [1010], time: [272.0541], loss: [0.00456959]
Epoch: [ 6], step: [1020], time: [274.6842], loss: [0.00040236]
Epoch: [ 7], step: [1030], time: [277.2978], loss: [0.00109150]
Epoch: [ 7], step: [1040], time: [279.9019], loss: [0.00081011]
Epoch: [ 7], step: [1050], time: [282.5234], loss: [0.00075122]
Epoch: [ 7], step: [1060], time: [285.1459], loss: [0.00255910]
Epoch: [ 7], step: [1070], time: [287.7546], loss: [0.00096062]
Epoch: [ 7], step: [1080], time: [290.4108], loss: [0.00033346]
Epoch: [ 7], step: [1090], time: [293.0115], loss: [0.00175631]
Epoch: [ 7], step: [1100], time: [295.6517], loss: [0.00027418]
Epoch: [ 7], step: [1110], time: [298.2687], loss: [0.00422178]
Epoch: [ 7], step: [1120], time: [300.9284], loss: [0.00770428]
Epoch: [ 7], step: [1130], time: [303.6330], loss: [0.00030762]
Epoch: [ 7], step: [1140], time: [306.2410], loss: [0.00147303]
Epoch: [ 7], step: [1150], time: [308.8669], loss: [0.00093157]
Epoch: [ 7], step: [1160], time: [311.4748], loss: [0.00035775]
Epoch: [ 7], step: [1170], time: [314.1127], loss: [0.00089208]
Epoch: [ 7], step: [1180], time: [316.7642], loss: [0.00456959]
Epoch: [ 7], step: [1190], time: [319.4191], loss: [0.00040236]
Epoch: [ 8], step: [1200], time: [322.1789], loss: [0.00109150]
Epoch: [ 8], step: [1210], time: [324.9519], loss: [0.00081011]
Epoch: [ 8], step: [1220], time: [327.7585], loss: [0.00075121]
Epoch: [ 8], step: [1230], time: [330.5776], loss: [0.00255910]
Epoch: [ 8], step: [1240], time: [333.3642], loss: [0.00096062]
Epoch: [ 8], step: [1250], time: [336.0772], loss: [0.00033346]
Epoch: [ 8], step: [1260], time: [338.7242], loss: [0.00175631]
Epoch: [ 8], step: [1270], time: [341.3608], loss: [0.00027418]
Epoch: [ 8], step: [1280], time: [343.9971], loss: [0.00422178]
Epoch: [ 8], step: [1290], time: [346.6338], loss: [0.00770428]
Epoch: [ 8], step: [1300], time: [349.2769], loss: [0.00030762]
Epoch: [ 8], step: [1310], time: [351.9174], loss: [0.00147303]
Epoch: [ 8], step: [1320], time: [354.5407], loss: [0.00093157]
Epoch: [ 8], step: [1330], time: [357.1880], loss: [0.00035775]
Epoch: [ 8], step: [1340], time: [359.8589], loss: [0.00089208]
Epoch: [ 8], step: [1350], time: [362.7084], loss: [0.00456959]
Epoch: [ 8], step: [1360], time: [365.4255], loss: [0.00040236]
Epoch: [ 9], step: [1370], time: [368.1698], loss: [0.00109150]
Epoch: [ 9], step: [1380], time: [370.9029], loss: [0.00081011]
Epoch: [ 9], step: [1390], time: [373.6208], loss: [0.00075121]
Epoch: [ 9], step: [1400], time: [376.3366], loss: [0.00255910]
Epoch: [ 9], step: [1410], time: [378.9805], loss: [0.00096062]
Epoch: [ 9], step: [1420], time: [381.6248], loss: [0.00033346]
Epoch: [ 9], step: [1430], time: [384.2501], loss: [0.00175631]
Epoch: [ 9], step: [1440], time: [386.8889], loss: [0.00027418]
Epoch: [ 9], step: [1450], time: [389.5139], loss: [0.00422178]
Epoch: [ 9], step: [1460], time: [392.3000], loss: [0.00770428]
Epoch: [ 9], step: [1470], time: [395.0201], loss: [0.00030762]
Epoch: [ 9], step: [1480], time: [397.7832], loss: [0.00147303]
Epoch: [ 9], step: [1490], time: [400.5488], loss: [0.00093157]
Epoch: [ 9], step: [1500], time: [403.2317], loss: [0.00035775]
Epoch: [ 9], step: [1510], time: [406.2747], loss: [0.00089208]
Epoch: [ 9], step: [1520], time: [408.9187], loss: [0.00456959]
Epoch: [ 9], step: [1530], time: [411.5343], loss: [0.00040236]
Epoch: [10], step: [1540], time: [414.2177], loss: [0.00109150]
Epoch: [10], step: [1550], time: [416.9087], loss: [0.00081011]
Epoch: [10], step: [1560], time: [419.5357], loss: [0.00075121]
Epoch: [10], step: [1570], time: [422.1796], loss: [0.00255909]
Epoch: [10], step: [1580], time: [424.8800], loss: [0.00096062]
Epoch: [10], step: [1590], time: [427.5076], loss: [0.00033346]
Epoch: [10], step: [1600], time: [430.1426], loss: [0.00175631]
Epoch: [10], step: [1610], time: [432.7727], loss: [0.00027418]
Epoch: [10], step: [1620], time: [435.4287], loss: [0.00422178]
Epoch: [10], step: [1630], time: [438.0733], loss: [0.00770428]
Epoch: [10], step: [1640], time: [440.7108], loss: [0.00030762]
Epoch: [10], step: [1650], time: [443.3302], loss: [0.00147303]
Epoch: [10], step: [1660], time: [445.9489], loss: [0.00093157]
Epoch: [10], step: [1670], time: [448.5874], loss: [0.00035775]
Epoch: [10], step: [1680], time: [451.2095], loss: [0.00089208]
Epoch: [10], step: [1690], time: [453.8219], loss: [0.00456959]
Epoch: [10], step: [1700], time: [456.4605], loss: [0.00040236]
PNSR = 24.040933971512175