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l1evodiff
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1606880 model parameters
138376 training sequences
34323 validation sequences
Training: Epoch 1 of 10 Step 1 ntokens 35400 Example 300 of 138376 loss = 3.5024 nll loss = 2.1794 accu = 0.3541
Training: Epoch 1 of 10 Step 2 ntokens 70800 Example 600 of 138376 loss = 3.4985 nll loss = 2.1663 accu = 0.3582
Training: Epoch 1 of 10 Step 3 ntokens 106200 Example 900 of 138376 loss = 3.4930 nll loss = 2.1655 accu = 0.3574
Training: Epoch 1 of 10 Step 4 ntokens 141600 Example 1200 of 138376 loss = 3.4911 nll loss = 2.1529 accu = 0.3613
Training: Epoch 1 of 10 Step 5 ntokens 177000 Example 1500 of 138376 loss = 3.4935 nll loss = 2.1627 accu = 0.3579
Training: Epoch 1 of 10 Step 6 ntokens 212400 Example 1800 of 138376 loss = 3.4889 nll loss = 2.1669 accu = 0.3568
Training: Epoch 1 of 10 Step 7 ntokens 247800 Example 2100 of 138376 loss = 3.4968 nll loss = 2.1591 accu = 0.3595
Training: Epoch 1 of 10 Step 8 ntokens 283200 Example 2400 of 138376 loss = 3.4918 nll loss = 2.1493 accu = 0.3625
Training: Epoch 1 of 10 Step 9 ntokens 318600 Example 2700 of 138376 loss = 3.4946 nll loss = 2.1501 accu = 0.3625
Training: Epoch 1 of 10 Step 10 ntokens 354000 Example 3000 of 138376 loss = 3.4906 nll loss = 2.1479 accu = 0.3632
Training: Epoch 1 of 10 Step 11 ntokens 389400 Example 3300 of 138376 loss = 3.4935 nll loss = 2.1449 accu = 0.3642
Training: Epoch 1 of 10 Step 12 ntokens 424800 Example 3600 of 138376 loss = 3.5019 nll loss = 2.1398 accu = 0.3661
Training: Epoch 1 of 10 Step 13 ntokens 460200 Example 3900 of 138376 loss = 3.5017 nll loss = 2.1410 accu = 0.3660
Training: Epoch 1 of 10 Step 14 ntokens 495600 Example 4200 of 138376 loss = 3.5037 nll loss = 2.1433 accu = 0.3652
Training: Epoch 1 of 10 Step 15 ntokens 531000 Example 4500 of 138376 loss = 3.4976 nll loss = 2.1423 accu = 0.3654
Training: Epoch 1 of 10 Step 16 ntokens 566400 Example 4800 of 138376 loss = 3.4954 nll loss = 2.1449 accu = 0.3647
Training: Epoch 1 of 10 Step 17 ntokens 601800 Example 5100 of 138376 loss = 3.4893 nll loss = 2.1455 accu = 0.3647
Training: Epoch 1 of 10 Step 18 ntokens 637200 Example 5400 of 138376 loss = 3.4946 nll loss = 2.1474 accu = 0.3641
Training: Epoch 1 of 10 Step 19 ntokens 672600 Example 5700 of 138376 loss = 3.4909 nll loss = 2.1423 accu = 0.3660
Training: Epoch 1 of 10 Step 20 ntokens 708000 Example 6000 of 138376 loss = 3.4874 nll loss = 2.1442 accu = 0.3655
Training: Epoch 1 of 10 Step 21 ntokens 743400 Example 6300 of 138376 loss = 3.4866 nll loss = 2.1433 accu = 0.3658
Training: Epoch 1 of 10 Step 22 ntokens 778800 Example 6600 of 138376 loss = 3.4897 nll loss = 2.1439 accu = 0.3655
Training: Epoch 1 of 10 Step 23 ntokens 814200 Example 6900 of 138376 loss = 3.4885 nll loss = 2.1434 accu = 0.3656
Training: Epoch 1 of 10 Step 24 ntokens 849600 Example 7200 of 138376 loss = 3.4880 nll loss = 2.1419 accu = 0.3662
Training: Epoch 1 of 10 Step 25 ntokens 885000 Example 7500 of 138376 loss = 3.4899 nll loss = 2.1417 accu = 0.3665
Training: Epoch 1 of 10 Step 26 ntokens 920400 Example 7800 of 138376 loss = 3.4924 nll loss = 2.1417 accu = 0.3664
Training: Epoch 1 of 10 Step 27 ntokens 955800 Example 8100 of 138376 loss = 3.4954 nll loss = 2.1420 accu = 0.3663
Training: Epoch 1 of 10 Step 28 ntokens 991200 Example 8400 of 138376 loss = 3.4933 nll loss = 2.1420 accu = 0.3663
Training: Epoch 1 of 10 Step 29 ntokens 1026600 Example 8700 of 138376 loss = 3.4939 nll loss = 2.1417 accu = 0.3665
Training: Epoch 1 of 10 Step 30 ntokens 1062000 Example 9000 of 138376 loss = 3.4916 nll loss = 2.1415 accu = 0.3666
Training: Epoch 1 of 10 Step 31 ntokens 1097400 Example 9300 of 138376 loss = 3.4925 nll loss = 2.1414 accu = 0.3666
Training: Epoch 1 of 10 Step 32 ntokens 1132800 Example 9600 of 138376 loss = 3.4923 nll loss = 2.1430 accu = 0.3661
Training: Epoch 1 of 10 Step 33 ntokens 1168200 Example 9900 of 138376 loss = 3.4963 nll loss = 2.1440 accu = 0.3657
Training: Epoch 1 of 10 Step 34 ntokens 1203600 Example 10200 of 138376 loss = 3.4974 nll loss = 2.1440 accu = 0.3658
Training: Epoch 1 of 10 Step 35 ntokens 1239000 Example 10500 of 138376 loss = 3.5000 nll loss = 2.1404 accu = 0.3670
Training: Epoch 1 of 10 Step 36 ntokens 1274400 Example 10800 of 138376 loss = 3.5012 nll loss = 2.1395 accu = 0.3671
Training: Epoch 1 of 10 Step 37 ntokens 1309800 Example 11100 of 138376 loss = 3.5016 nll loss = 2.1404 accu = 0.3668
Training: Epoch 1 of 10 Step 38 ntokens 1345200 Example 11400 of 138376 loss = 3.5009 nll loss = 2.1398 accu = 0.3670
Training: Epoch 1 of 10 Step 39 ntokens 1380600 Example 11700 of 138376 loss = 3.5005 nll loss = 2.1409 accu = 0.3666
Training: Epoch 1 of 10 Step 40 ntokens 1416000 Example 12000 of 138376 loss = 3.5002 nll loss = 2.1420 accu = 0.3661
Training: Epoch 1 of 10 Step 41 ntokens 1451400 Example 12300 of 138376 loss = 3.5008 nll loss = 2.1429 accu = 0.3658
Training: Epoch 1 of 10 Step 42 ntokens 1486800 Example 12600 of 138376 loss = 3.4974 nll loss = 2.1425 accu = 0.3660
Training: Epoch 1 of 10 Step 43 ntokens 1522200 Example 12900 of 138376 loss = 3.4971 nll loss = 2.1441 accu = 0.3654
Training: Epoch 1 of 10 Step 44 ntokens 1557600 Example 13200 of 138376 loss = 3.4955 nll loss = 2.1439 accu = 0.3654
Training: Epoch 1 of 10 Step 45 ntokens 1593000 Example 13500 of 138376 loss = 3.4962 nll loss = 2.1457 accu = 0.3648
Training: Epoch 1 of 10 Step 46 ntokens 1628400 Example 13800 of 138376 loss = 3.4966 nll loss = 2.1446 accu = 0.3651
Training: Epoch 1 of 10 Step 47 ntokens 1663800 Example 14100 of 138376 loss = 3.4964 nll loss = 2.1448 accu = 0.3650
Training: Epoch 1 of 10 Step 48 ntokens 1699200 Example 14400 of 138376 loss = 3.4983 nll loss = 2.1438 accu = 0.3654
Training: Epoch 1 of 10 Step 49 ntokens 1734600 Example 14700 of 138376 loss = 3.4988 nll loss = 2.1432 accu = 0.3656
Training: Epoch 1 of 10 Step 50 ntokens 1770000 Example 15000 of 138376 loss = 3.5002 nll loss = 2.1434 accu = 0.3655
Training: Epoch 1 of 10 Step 51 ntokens 1805400 Example 15300 of 138376 loss = 3.5016 nll loss = 2.1425 accu = 0.3658
Training: Epoch 1 of 10 Step 52 ntokens 1840800 Example 15600 of 138376 loss = 3.5021 nll loss = 2.1442 accu = 0.3652
Training: Epoch 1 of 10 Step 53 ntokens 1876200 Example 15900 of 138376 loss = 3.5023 nll loss = 2.1430 accu = 0.3656
Training: Epoch 1 of 10 Step 54 ntokens 1911600 Example 16200 of 138376 loss = 3.5025 nll loss = 2.1426 accu = 0.3657
Training: Epoch 1 of 10 Step 55 ntokens 1947000 Example 16500 of 138376 loss = 3.5022 nll loss = 2.1426 accu = 0.3658
Training: Epoch 1 of 10 Step 56 ntokens 1982400 Example 16800 of 138376 loss = 3.5019 nll loss = 2.1413 accu = 0.3663
Training: Epoch 1 of 10 Step 57 ntokens 2017800 Example 17100 of 138376 loss = 3.5015 nll loss = 2.1410 accu = 0.3664
Training: Epoch 1 of 10 Step 58 ntokens 2053200 Example 17400 of 138376 loss = 3.4998 nll loss = 2.1418 accu = 0.3661
Training: Epoch 1 of 10 Step 59 ntokens 2088600 Example 17700 of 138376 loss = 3.5004 nll loss = 2.1434 accu = 0.3656
Training: Epoch 1 of 10 Step 60 ntokens 2124000 Example 18000 of 138376 loss = 3.5003 nll loss = 2.1430 accu = 0.3657
Training: Epoch 1 of 10 Step 61 ntokens 2159400 Example 18300 of 138376 loss = 3.5013 nll loss = 2.1441 accu = 0.3654
Training: Epoch 1 of 10 Step 62 ntokens 2194800 Example 18600 of 138376 loss = 3.5040 nll loss = 2.1444 accu = 0.3653
Training: Epoch 1 of 10 Step 63 ntokens 2230200 Example 18900 of 138376 loss = 3.5042 nll loss = 2.1435 accu = 0.3656
Training: Epoch 1 of 10 Step 64 ntokens 2265600 Example 19200 of 138376 loss = 3.5052 nll loss = 2.1433 accu = 0.3657
Training: Epoch 1 of 10 Step 65 ntokens 2301000 Example 19500 of 138376 loss = 3.5046 nll loss = 2.1433 accu = 0.3657
Training: Epoch 1 of 10 Step 66 ntokens 2336400 Example 19800 of 138376 loss = 3.5036 nll loss = 2.1428 accu = 0.3659
Training: Epoch 1 of 10 Step 67 ntokens 2371800 Example 20100 of 138376 loss = 3.5030 nll loss = 2.1416 accu = 0.3663
Training: Epoch 1 of 10 Step 68 ntokens 2407200 Example 20400 of 138376 loss = 3.5030 nll loss = 2.1413 accu = 0.3665
Training: Epoch 1 of 10 Step 69 ntokens 2442600 Example 20700 of 138376 loss = 3.5023 nll loss = 2.1419 accu = 0.3663
Training: Epoch 1 of 10 Step 70 ntokens 2478000 Example 21000 of 138376 loss = 3.5017 nll loss = 2.1427 accu = 0.3660
Training: Epoch 1 of 10 Step 71 ntokens 2513400 Example 21300 of 138376 loss = 3.5010 nll loss = 2.1429 accu = 0.3660
Training: Epoch 1 of 10 Step 72 ntokens 2548800 Example 21600 of 138376 loss = 3.5019 nll loss = 2.1434 accu = 0.3658
Training: Epoch 1 of 10 Step 73 ntokens 2584200 Example 21900 of 138376 loss = 3.5017 nll loss = 2.1433 accu = 0.3658
Training: Epoch 1 of 10 Step 74 ntokens 2619600 Example 22200 of 138376 loss = 3.5005 nll loss = 2.1425 accu = 0.3661
Training: Epoch 1 of 10 Step 75 ntokens 2655000 Example 22500 of 138376 loss = 3.5017 nll loss = 2.1417 accu = 0.3664
Training: Epoch 1 of 10 Step 76 ntokens 2690400 Example 22800 of 138376 loss = 3.5032 nll loss = 2.1424 accu = 0.3661
Training: Epoch 1 of 10 Step 77 ntokens 2725800 Example 23100 of 138376 loss = 3.5024 nll loss = 2.1415 accu = 0.3664
Training: Epoch 1 of 10 Step 78 ntokens 2761200 Example 23400 of 138376 loss = 3.5025 nll loss = 2.1423 accu = 0.3662
Training: Epoch 1 of 10 Step 79 ntokens 2796600 Example 23700 of 138376 loss = 3.5017 nll loss = 2.1426 accu = 0.3660
Training: Epoch 1 of 10 Step 80 ntokens 2832000 Example 24000 of 138376 loss = 3.5015 nll loss = 2.1424 accu = 0.3661
Training: Epoch 1 of 10 Step 81 ntokens 2867400 Example 24300 of 138376 loss = 3.5024 nll loss = 2.1424 accu = 0.3662
Training: Epoch 1 of 10 Step 82 ntokens 2902800 Example 24600 of 138376 loss = 3.5031 nll loss = 2.1413 accu = 0.3666
Training: Epoch 1 of 10 Step 83 ntokens 2938200 Example 24900 of 138376 loss = 3.5020 nll loss = 2.1412 accu = 0.3666
Training: Epoch 1 of 10 Step 84 ntokens 2973600 Example 25200 of 138376 loss = 3.5009 nll loss = 2.1410 accu = 0.3667
Training: Epoch 1 of 10 Step 85 ntokens 3009000 Example 25500 of 138376 loss = 3.5001 nll loss = 2.1410 accu = 0.3666
Training: Epoch 1 of 10 Step 86 ntokens 3044400 Example 25800 of 138376 loss = 3.5004 nll loss = 2.1415 accu = 0.3665
Training: Epoch 1 of 10 Step 87 ntokens 3079800 Example 26100 of 138376 loss = 3.4998 nll loss = 2.1413 accu = 0.3665
Training: Epoch 1 of 10 Step 88 ntokens 3115200 Example 26400 of 138376 loss = 3.5010 nll loss = 2.1413 accu = 0.3666
Training: Epoch 1 of 10 Step 89 ntokens 3150600 Example 26700 of 138376 loss = 3.5008 nll loss = 2.1408 accu = 0.3667
Training: Epoch 1 of 10 Step 90 ntokens 3186000 Example 27000 of 138376 loss = 3.5006 nll loss = 2.1406 accu = 0.3668
Training: Epoch 1 of 10 Step 91 ntokens 3221400 Example 27300 of 138376 loss = 3.5002 nll loss = 2.1403 accu = 0.3669
Training: Epoch 1 of 10 Step 92 ntokens 3256800 Example 27600 of 138376 loss = 3.5005 nll loss = 2.1403 accu = 0.3669
Training: Epoch 1 of 10 Step 93 ntokens 3292200 Example 27900 of 138376 loss = 3.4993 nll loss = 2.1404 accu = 0.3669
Training: Epoch 1 of 10 Step 94 ntokens 3327600 Example 28200 of 138376 loss = 3.4987 nll loss = 2.1397 accu = 0.3672
Training: Epoch 1 of 10 Step 95 ntokens 3363000 Example 28500 of 138376 loss = 3.4993 nll loss = 2.1393 accu = 0.3674
Training: Epoch 1 of 10 Step 96 ntokens 3398400 Example 28800 of 138376 loss = 3.4995 nll loss = 2.1392 accu = 0.3674
Training: Epoch 1 of 10 Step 97 ntokens 3433800 Example 29100 of 138376 loss = 3.4988 nll loss = 2.1385 accu = 0.3676
Training: Epoch 1 of 10 Step 98 ntokens 3469200 Example 29400 of 138376 loss = 3.4985 nll loss = 2.1376 accu = 0.3679
Training: Epoch 1 of 10 Step 99 ntokens 3504600 Example 29700 of 138376 loss = 3.4978 nll loss = 2.1380 accu = 0.3678
Training: Epoch 1 of 10 Step 100 ntokens 3540000 Example 30000 of 138376 loss = 3.4981 nll loss = 2.1375 accu = 0.3680
Training: Epoch 1 of 10 Step 101 ntokens 3575400 Example 30300 of 138376 loss = 3.4977 nll loss = 2.1374 accu = 0.3680
Training: Epoch 1 of 10 Step 102 ntokens 3610800 Example 30600 of 138376 loss = 3.4976 nll loss = 2.1372 accu = 0.3681
Training: Epoch 1 of 10 Step 103 ntokens 3646200 Example 30900 of 138376 loss = 3.4980 nll loss = 2.1374 accu = 0.3680
Training: Epoch 1 of 10 Step 104 ntokens 3681600 Example 31200 of 138376 loss = 3.4980 nll loss = 2.1368 accu = 0.3682
Training: Epoch 1 of 10 Step 105 ntokens 3717000 Example 31500 of 138376 loss = 3.4979 nll loss = 2.1365 accu = 0.3683
Training: Epoch 1 of 10 Step 106 ntokens 3752400 Example 31800 of 138376 loss = 3.4969 nll loss = 2.1365 accu = 0.3683
Training: Epoch 1 of 10 Step 107 ntokens 3787800 Example 32100 of 138376 loss = 3.4965 nll loss = 2.1357 accu = 0.3686
Training: Epoch 1 of 10 Step 108 ntokens 3823200 Example 32400 of 138376 loss = 3.4971 nll loss = 2.1362 accu = 0.3685
Training: Epoch 1 of 10 Step 109 ntokens 3858600 Example 32700 of 138376 loss = 3.4976 nll loss = 2.1362 accu = 0.3685
Training: Epoch 1 of 10 Step 110 ntokens 3894000 Example 33000 of 138376 loss = 3.4967 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 111 ntokens 3929400 Example 33300 of 138376 loss = 3.4965 nll loss = 2.1351 accu = 0.3688
Training: Epoch 1 of 10 Step 112 ntokens 3964800 Example 33600 of 138376 loss = 3.4960 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 113 ntokens 4000200 Example 33900 of 138376 loss = 3.4959 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 114 ntokens 4035600 Example 34200 of 138376 loss = 3.4968 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 115 ntokens 4071000 Example 34500 of 138376 loss = 3.4959 nll loss = 2.1357 accu = 0.3686
Training: Epoch 1 of 10 Step 116 ntokens 4106400 Example 34800 of 138376 loss = 3.4955 nll loss = 2.1361 accu = 0.3685
Training: Epoch 1 of 10 Step 117 ntokens 4141800 Example 35100 of 138376 loss = 3.4956 nll loss = 2.1360 accu = 0.3686
Training: Epoch 1 of 10 Step 118 ntokens 4177200 Example 35400 of 138376 loss = 3.4949 nll loss = 2.1365 accu = 0.3684
Training: Epoch 1 of 10 Step 119 ntokens 4212600 Example 35700 of 138376 loss = 3.4947 nll loss = 2.1367 accu = 0.3683
Training: Epoch 1 of 10 Step 120 ntokens 4248000 Example 36000 of 138376 loss = 3.4953 nll loss = 2.1368 accu = 0.3683
Training: Epoch 1 of 10 Step 121 ntokens 4283400 Example 36300 of 138376 loss = 3.4959 nll loss = 2.1373 accu = 0.3682
Training: Epoch 1 of 10 Step 122 ntokens 4318800 Example 36600 of 138376 loss = 3.4959 nll loss = 2.1373 accu = 0.3682
Training: Epoch 1 of 10 Step 123 ntokens 4354200 Example 36900 of 138376 loss = 3.4962 nll loss = 2.1372 accu = 0.3682
Training: Epoch 1 of 10 Step 124 ntokens 4389600 Example 37200 of 138376 loss = 3.4963 nll loss = 2.1373 accu = 0.3681
Training: Epoch 1 of 10 Step 125 ntokens 4425000 Example 37500 of 138376 loss = 3.4964 nll loss = 2.1370 accu = 0.3682
Training: Epoch 1 of 10 Step 126 ntokens 4460400 Example 37800 of 138376 loss = 3.4967 nll loss = 2.1373 accu = 0.3681
Training: Epoch 1 of 10 Step 127 ntokens 4495800 Example 38100 of 138376 loss = 3.4962 nll loss = 2.1366 accu = 0.3684
Training: Epoch 1 of 10 Step 128 ntokens 4531200 Example 38400 of 138376 loss = 3.4962 nll loss = 2.1368 accu = 0.3683
Training: Epoch 1 of 10 Step 129 ntokens 4566600 Example 38700 of 138376 loss = 3.4971 nll loss = 2.1369 accu = 0.3683
Training: Epoch 1 of 10 Step 130 ntokens 4602000 Example 39000 of 138376 loss = 3.4966 nll loss = 2.1366 accu = 0.3684
Training: Epoch 1 of 10 Step 131 ntokens 4637400 Example 39300 of 138376 loss = 3.4972 nll loss = 2.1369 accu = 0.3683
Training: Epoch 1 of 10 Step 132 ntokens 4672800 Example 39600 of 138376 loss = 3.4974 nll loss = 2.1373 accu = 0.3681
Training: Epoch 1 of 10 Step 133 ntokens 4708200 Example 39900 of 138376 loss = 3.4976 nll loss = 2.1377 accu = 0.3679
Training: Epoch 1 of 10 Step 134 ntokens 4743600 Example 40200 of 138376 loss = 3.4972 nll loss = 2.1381 accu = 0.3678
Training: Epoch 1 of 10 Step 135 ntokens 4779000 Example 40500 of 138376 loss = 3.4975 nll loss = 2.1375 accu = 0.3680
Training: Epoch 1 of 10 Step 136 ntokens 4814400 Example 40800 of 138376 loss = 3.4972 nll loss = 2.1377 accu = 0.3680
Training: Epoch 1 of 10 Step 137 ntokens 4849800 Example 41100 of 138376 loss = 3.4968 nll loss = 2.1384 accu = 0.3677
Training: Epoch 1 of 10 Step 138 ntokens 4885200 Example 41400 of 138376 loss = 3.4966 nll loss = 2.1385 accu = 0.3677
Training: Epoch 1 of 10 Step 139 ntokens 4920600 Example 41700 of 138376 loss = 3.4970 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 140 ntokens 4956000 Example 42000 of 138376 loss = 3.4975 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 141 ntokens 4991400 Example 42300 of 138376 loss = 3.4983 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 142 ntokens 5026800 Example 42600 of 138376 loss = 3.4986 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 143 ntokens 5062200 Example 42900 of 138376 loss = 3.4981 nll loss = 2.1386 accu = 0.3677
Training: Epoch 1 of 10 Step 144 ntokens 5097600 Example 43200 of 138376 loss = 3.4983 nll loss = 2.1387 accu = 0.3676
Training: Epoch 1 of 10 Step 145 ntokens 5133000 Example 43500 of 138376 loss = 3.4984 nll loss = 2.1385 accu = 0.3677
Training: Epoch 1 of 10 Step 146 ntokens 5168400 Example 43800 of 138376 loss = 3.4989 nll loss = 2.1385 accu = 0.3677
Training: Epoch 1 of 10 Step 147 ntokens 5203800 Example 44100 of 138376 loss = 3.4992 nll loss = 2.1387 accu = 0.3676
Training: Epoch 1 of 10 Step 148 ntokens 5239200 Example 44400 of 138376 loss = 3.4993 nll loss = 2.1390 accu = 0.3675
Training: Epoch 1 of 10 Step 149 ntokens 5274600 Example 44700 of 138376 loss = 3.4988 nll loss = 2.1393 accu = 0.3674
Training: Epoch 1 of 10 Step 150 ntokens 5310000 Example 45000 of 138376 loss = 3.4988 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 151 ntokens 5345400 Example 45300 of 138376 loss = 3.4985 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 152 ntokens 5380800 Example 45600 of 138376 loss = 3.4994 nll loss = 2.1386 accu = 0.3677
Training: Epoch 1 of 10 Step 153 ntokens 5416200 Example 45900 of 138376 loss = 3.5000 nll loss = 2.1388 accu = 0.3676
Training: Epoch 1 of 10 Step 154 ntokens 5451600 Example 46200 of 138376 loss = 3.4998 nll loss = 2.1384 accu = 0.3678
Training: Epoch 1 of 10 Step 155 ntokens 5487000 Example 46500 of 138376 loss = 3.5000 nll loss = 2.1381 accu = 0.3679
Training: Epoch 1 of 10 Step 156 ntokens 5522400 Example 46800 of 138376 loss = 3.5000 nll loss = 2.1374 accu = 0.3681
Training: Epoch 1 of 10 Step 157 ntokens 5557800 Example 47100 of 138376 loss = 3.4997 nll loss = 2.1371 accu = 0.3682
Training: Epoch 1 of 10 Step 158 ntokens 5593200 Example 47400 of 138376 loss = 3.4990 nll loss = 2.1364 accu = 0.3685
Training: Epoch 1 of 10 Step 159 ntokens 5628600 Example 47700 of 138376 loss = 3.4991 nll loss = 2.1361 accu = 0.3686
Training: Epoch 1 of 10 Step 160 ntokens 5664000 Example 48000 of 138376 loss = 3.4992 nll loss = 2.1361 accu = 0.3686
Training: Epoch 1 of 10 Step 161 ntokens 5699400 Example 48300 of 138376 loss = 3.4992 nll loss = 2.1358 accu = 0.3687
Training: Epoch 1 of 10 Step 162 ntokens 5734800 Example 48600 of 138376 loss = 3.4988 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 163 ntokens 5770200 Example 48900 of 138376 loss = 3.4992 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 164 ntokens 5805600 Example 49200 of 138376 loss = 3.4992 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 165 ntokens 5841000 Example 49500 of 138376 loss = 3.4987 nll loss = 2.1359 accu = 0.3686
Training: Epoch 1 of 10 Step 166 ntokens 5876400 Example 49800 of 138376 loss = 3.4989 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 167 ntokens 5911800 Example 50100 of 138376 loss = 3.4986 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 168 ntokens 5947200 Example 50400 of 138376 loss = 3.4984 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 169 ntokens 5982600 Example 50700 of 138376 loss = 3.4981 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 170 ntokens 6018000 Example 51000 of 138376 loss = 3.4981 nll loss = 2.1351 accu = 0.3688
Training: Epoch 1 of 10 Step 171 ntokens 6053400 Example 51300 of 138376 loss = 3.4987 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 172 ntokens 6088800 Example 51600 of 138376 loss = 3.4987 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 173 ntokens 6124200 Example 51900 of 138376 loss = 3.4992 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 174 ntokens 6159600 Example 52200 of 138376 loss = 3.4996 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 175 ntokens 6195000 Example 52500 of 138376 loss = 3.4998 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 176 ntokens 6230400 Example 52800 of 138376 loss = 3.4998 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 177 ntokens 6265800 Example 53100 of 138376 loss = 3.5004 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 178 ntokens 6301200 Example 53400 of 138376 loss = 3.5002 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 179 ntokens 6336600 Example 53700 of 138376 loss = 3.5002 nll loss = 2.1345 accu = 0.3690
Training: Epoch 1 of 10 Step 180 ntokens 6372000 Example 54000 of 138376 loss = 3.4999 nll loss = 2.1348 accu = 0.3689
Training: Epoch 1 of 10 Step 181 ntokens 6407400 Example 54300 of 138376 loss = 3.4995 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 182 ntokens 6442800 Example 54600 of 138376 loss = 3.5000 nll loss = 2.1343 accu = 0.3691
Training: Epoch 1 of 10 Step 183 ntokens 6478200 Example 54900 of 138376 loss = 3.5001 nll loss = 2.1340 accu = 0.3692
Training: Epoch 1 of 10 Step 184 ntokens 6513600 Example 55200 of 138376 loss = 3.4999 nll loss = 2.1343 accu = 0.3691
Training: Epoch 1 of 10 Step 185 ntokens 6549000 Example 55500 of 138376 loss = 3.4997 nll loss = 2.1346 accu = 0.3690
Training: Epoch 1 of 10 Step 186 ntokens 6584400 Example 55800 of 138376 loss = 3.5002 nll loss = 2.1350 accu = 0.3688
Training: Epoch 1 of 10 Step 187 ntokens 6619800 Example 56100 of 138376 loss = 3.5002 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 188 ntokens 6655200 Example 56400 of 138376 loss = 3.4998 nll loss = 2.1350 accu = 0.3688
Training: Epoch 1 of 10 Step 189 ntokens 6690600 Example 56700 of 138376 loss = 3.4998 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 190 ntokens 6726000 Example 57000 of 138376 loss = 3.5000 nll loss = 2.1348 accu = 0.3689
Training: Epoch 1 of 10 Step 191 ntokens 6761400 Example 57300 of 138376 loss = 3.4999 nll loss = 2.1353 accu = 0.3687
Training: Epoch 1 of 10 Step 192 ntokens 6796800 Example 57600 of 138376 loss = 3.5005 nll loss = 2.1351 accu = 0.3688
Training: Epoch 1 of 10 Step 193 ntokens 6832200 Example 57900 of 138376 loss = 3.5009 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 194 ntokens 6867600 Example 58200 of 138376 loss = 3.5004 nll loss = 2.1353 accu = 0.3687
Training: Epoch 1 of 10 Step 195 ntokens 6903000 Example 58500 of 138376 loss = 3.5003 nll loss = 2.1352 accu = 0.3687
Training: Epoch 1 of 10 Step 196 ntokens 6938400 Example 58800 of 138376 loss = 3.5006 nll loss = 2.1353 accu = 0.3687
Training: Epoch 1 of 10 Step 197 ntokens 6973800 Example 59100 of 138376 loss = 3.5004 nll loss = 2.1355 accu = 0.3686
Training: Epoch 1 of 10 Step 198 ntokens 7009200 Example 59400 of 138376 loss = 3.5006 nll loss = 2.1355 accu = 0.3687
Training: Epoch 1 of 10 Step 199 ntokens 7044600 Example 59700 of 138376 loss = 3.5011 nll loss = 2.1356 accu = 0.3686
Training: Epoch 1 of 10 Step 200 ntokens 7080000 Example 60000 of 138376 loss = 3.5014 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 201 ntokens 7115400 Example 60300 of 138376 loss = 3.5019 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 202 ntokens 7150800 Example 60600 of 138376 loss = 3.5023 nll loss = 2.1353 accu = 0.3687
Training: Epoch 1 of 10 Step 203 ntokens 7186200 Example 60900 of 138376 loss = 3.5020 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 204 ntokens 7221600 Example 61200 of 138376 loss = 3.5020 nll loss = 2.1353 accu = 0.3687
Training: Epoch 1 of 10 Step 205 ntokens 7257000 Example 61500 of 138376 loss = 3.5026 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 206 ntokens 7292400 Example 61800 of 138376 loss = 3.5027 nll loss = 2.1355 accu = 0.3687
Training: Epoch 1 of 10 Step 207 ntokens 7327800 Example 62100 of 138376 loss = 3.5027 nll loss = 2.1355 accu = 0.3687
Training: Epoch 1 of 10 Step 208 ntokens 7363200 Example 62400 of 138376 loss = 3.5028 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 209 ntokens 7398600 Example 62700 of 138376 loss = 3.5027 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 210 ntokens 7434000 Example 63000 of 138376 loss = 3.5026 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 211 ntokens 7469400 Example 63300 of 138376 loss = 3.5030 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 212 ntokens 7504800 Example 63600 of 138376 loss = 3.5035 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 213 ntokens 7540200 Example 63900 of 138376 loss = 3.5034 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 214 ntokens 7575600 Example 64200 of 138376 loss = 3.5031 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 215 ntokens 7611000 Example 64500 of 138376 loss = 3.5029 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 216 ntokens 7646400 Example 64800 of 138376 loss = 3.5031 nll loss = 2.1356 accu = 0.3686
Training: Epoch 1 of 10 Step 217 ntokens 7681800 Example 65100 of 138376 loss = 3.5033 nll loss = 2.1352 accu = 0.3688
Training: Epoch 1 of 10 Step 218 ntokens 7717200 Example 65400 of 138376 loss = 3.5036 nll loss = 2.1354 accu = 0.3687
Training: Epoch 1 of 10 Step 219 ntokens 7752600 Example 65700 of 138376 loss = 3.5037 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 220 ntokens 7788000 Example 66000 of 138376 loss = 3.5034 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 221 ntokens 7823400 Example 66300 of 138376 loss = 3.5029 nll loss = 2.1360 accu = 0.3686
Training: Epoch 1 of 10 Step 222 ntokens 7858800 Example 66600 of 138376 loss = 3.5025 nll loss = 2.1359 accu = 0.3686
Training: Epoch 1 of 10 Step 223 ntokens 7894200 Example 66900 of 138376 loss = 3.5025 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 224 ntokens 7929600 Example 67200 of 138376 loss = 3.5026 nll loss = 2.1355 accu = 0.3687
Training: Epoch 1 of 10 Step 225 ntokens 7965000 Example 67500 of 138376 loss = 3.5028 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 226 ntokens 8000400 Example 67800 of 138376 loss = 3.5025 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 227 ntokens 8035800 Example 68100 of 138376 loss = 3.5026 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 228 ntokens 8071200 Example 68400 of 138376 loss = 3.5025 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 229 ntokens 8106600 Example 68700 of 138376 loss = 3.5023 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 230 ntokens 8142000 Example 69000 of 138376 loss = 3.5021 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 231 ntokens 8177400 Example 69300 of 138376 loss = 3.5028 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 232 ntokens 8212800 Example 69600 of 138376 loss = 3.5027 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 233 ntokens 8248200 Example 69900 of 138376 loss = 3.5025 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 234 ntokens 8283600 Example 70200 of 138376 loss = 3.5023 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 235 ntokens 8319000 Example 70500 of 138376 loss = 3.5025 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 236 ntokens 8354400 Example 70800 of 138376 loss = 3.5025 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 237 ntokens 8389800 Example 71100 of 138376 loss = 3.5027 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 238 ntokens 8425200 Example 71400 of 138376 loss = 3.5029 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 239 ntokens 8460600 Example 71700 of 138376 loss = 3.5033 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 240 ntokens 8496000 Example 72000 of 138376 loss = 3.5035 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 241 ntokens 8531400 Example 72300 of 138376 loss = 3.5037 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 242 ntokens 8566800 Example 72600 of 138376 loss = 3.5038 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 243 ntokens 8602200 Example 72900 of 138376 loss = 3.5036 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 244 ntokens 8637600 Example 73200 of 138376 loss = 3.5036 nll loss = 2.1345 accu = 0.3691
Training: Epoch 1 of 10 Step 245 ntokens 8673000 Example 73500 of 138376 loss = 3.5035 nll loss = 2.1345 accu = 0.3691
Training: Epoch 1 of 10 Step 246 ntokens 8708400 Example 73800 of 138376 loss = 3.5039 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 247 ntokens 8743800 Example 74100 of 138376 loss = 3.5043 nll loss = 2.1349 accu = 0.3690
Training: Epoch 1 of 10 Step 248 ntokens 8779200 Example 74400 of 138376 loss = 3.5041 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 249 ntokens 8814600 Example 74700 of 138376 loss = 3.5037 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 250 ntokens 8850000 Example 75000 of 138376 loss = 3.5038 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 251 ntokens 8885400 Example 75300 of 138376 loss = 3.5040 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 252 ntokens 8920800 Example 75600 of 138376 loss = 3.5039 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 253 ntokens 8956200 Example 75900 of 138376 loss = 3.5039 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 254 ntokens 8991600 Example 76200 of 138376 loss = 3.5037 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 255 ntokens 9027000 Example 76500 of 138376 loss = 3.5032 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 256 ntokens 9062400 Example 76800 of 138376 loss = 3.5033 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 257 ntokens 9097800 Example 77100 of 138376 loss = 3.5034 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 258 ntokens 9133200 Example 77400 of 138376 loss = 3.5039 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 259 ntokens 9168600 Example 77700 of 138376 loss = 3.5043 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 260 ntokens 9204000 Example 78000 of 138376 loss = 3.5045 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 261 ntokens 9239400 Example 78300 of 138376 loss = 3.5042 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 262 ntokens 9274800 Example 78600 of 138376 loss = 3.5042 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 263 ntokens 9310200 Example 78900 of 138376 loss = 3.5043 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 264 ntokens 9345600 Example 79200 of 138376 loss = 3.5039 nll loss = 2.1345 accu = 0.3691
Training: Epoch 1 of 10 Step 265 ntokens 9381000 Example 79500 of 138376 loss = 3.5036 nll loss = 2.1346 accu = 0.3690
Training: Epoch 1 of 10 Step 266 ntokens 9416400 Example 79800 of 138376 loss = 3.5033 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 267 ntokens 9451800 Example 80100 of 138376 loss = 3.5036 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 268 ntokens 9487200 Example 80400 of 138376 loss = 3.5034 nll loss = 2.1349 accu = 0.3690
Training: Epoch 1 of 10 Step 269 ntokens 9522600 Example 80700 of 138376 loss = 3.5039 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 270 ntokens 9558000 Example 81000 of 138376 loss = 3.5037 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 271 ntokens 9593400 Example 81300 of 138376 loss = 3.5038 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 272 ntokens 9628800 Example 81600 of 138376 loss = 3.5040 nll loss = 2.1349 accu = 0.3690
Training: Epoch 1 of 10 Step 273 ntokens 9664200 Example 81900 of 138376 loss = 3.5040 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 274 ntokens 9699600 Example 82200 of 138376 loss = 3.5037 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 275 ntokens 9735000 Example 82500 of 138376 loss = 3.5034 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 276 ntokens 9770400 Example 82800 of 138376 loss = 3.5039 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 277 ntokens 9805800 Example 83100 of 138376 loss = 3.5042 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 278 ntokens 9841200 Example 83400 of 138376 loss = 3.5045 nll loss = 2.1349 accu = 0.3689
Training: Epoch 1 of 10 Step 279 ntokens 9876600 Example 83700 of 138376 loss = 3.5044 nll loss = 2.1350 accu = 0.3689
Training: Epoch 1 of 10 Step 280 ntokens 9912000 Example 84000 of 138376 loss = 3.5043 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 281 ntokens 9947400 Example 84300 of 138376 loss = 3.5042 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 282 ntokens 9982800 Example 84600 of 138376 loss = 3.5036 nll loss = 2.1347 accu = 0.3690
Training: Epoch 1 of 10 Step 283 ntokens 10018200 Example 84900 of 138376 loss = 3.5038 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 284 ntokens 10053600 Example 85200 of 138376 loss = 3.5038 nll loss = 2.1349 accu = 0.3690
Training: Epoch 1 of 10 Step 285 ntokens 10089000 Example 85500 of 138376 loss = 3.5037 nll loss = 2.1351 accu = 0.3689
Training: Epoch 1 of 10 Step 286 ntokens 10124400 Example 85800 of 138376 loss = 3.5037 nll loss = 2.1356 accu = 0.3687
Training: Epoch 1 of 10 Step 287 ntokens 10159800 Example 86100 of 138376 loss = 3.5037 nll loss = 2.1356 accu = 0.3688
Training: Epoch 1 of 10 Step 288 ntokens 10195200 Example 86400 of 138376 loss = 3.5032 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 289 ntokens 10230600 Example 86700 of 138376 loss = 3.5033 nll loss = 2.1358 accu = 0.3687
Training: Epoch 1 of 10 Step 290 ntokens 10266000 Example 87000 of 138376 loss = 3.5031 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 291 ntokens 10301400 Example 87300 of 138376 loss = 3.5031 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 292 ntokens 10336800 Example 87600 of 138376 loss = 3.5030 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 293 ntokens 10372200 Example 87900 of 138376 loss = 3.5033 nll loss = 2.1353 accu = 0.3688
Training: Epoch 1 of 10 Step 294 ntokens 10407600 Example 88200 of 138376 loss = 3.5034 nll loss = 2.1354 accu = 0.3688
Training: Epoch 1 of 10 Step 295 ntokens 10443000 Example 88500 of 138376 loss = 3.5035 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 296 ntokens 10478400 Example 88800 of 138376 loss = 3.5035 nll loss = 2.1353 accu = 0.3689
Training: Epoch 1 of 10 Step 297 ntokens 10513800 Example 89100 of 138376 loss = 3.5035 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 298 ntokens 10549200 Example 89400 of 138376 loss = 3.5036 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 299 ntokens 10584600 Example 89700 of 138376 loss = 3.5035 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 300 ntokens 10620000 Example 90000 of 138376 loss = 3.5035 nll loss = 2.1356 accu = 0.3688
Training: Epoch 1 of 10 Step 301 ntokens 10655400 Example 90300 of 138376 loss = 3.5034 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 302 ntokens 10690800 Example 90600 of 138376 loss = 3.5031 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 303 ntokens 10726200 Example 90900 of 138376 loss = 3.5034 nll loss = 2.1356 accu = 0.3688
Training: Epoch 1 of 10 Step 304 ntokens 10761600 Example 91200 of 138376 loss = 3.5038 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 305 ntokens 10797000 Example 91500 of 138376 loss = 3.5035 nll loss = 2.1357 accu = 0.3687
Training: Epoch 1 of 10 Step 306 ntokens 10832400 Example 91800 of 138376 loss = 3.5036 nll loss = 2.1355 accu = 0.3688
Training: Epoch 1 of 10 Step 307 ntokens 10867800 Example 92100 of 138376 loss = 3.5037 nll loss = 2.1356 accu = 0.3688
Training: Epoch 1 of 10 Step 308 ntokens 10903200 Example 92400 of 138376 loss = 3.5037 nll loss = 2.1354 accu = 0.3689
Training: Epoch 1 of 10 Step 309 ntokens 10938600 Example 92700 of 138376 loss = 3.5038 nll loss = 2.1353 accu = 0.3689
Training: Epoch 1 of 10 Step 310 ntokens 10974000 Example 93000 of 138376 loss = 3.5039 nll loss = 2.1353 accu = 0.3689
Training: Epoch 1 of 10 Step 311 ntokens 11009400 Example 93300 of 138376 loss = 3.5036 nll loss = 2.1350 accu = 0.3690
Training: Epoch 1 of 10 Step 312 ntokens 11044800 Example 93600 of 138376 loss = 3.5038 nll loss = 2.1349 accu = 0.3691
Training: Epoch 1 of 10 Step 313 ntokens 11080200 Example 93900 of 138376 loss = 3.5040 nll loss = 2.1351 accu = 0.3690
Training: Epoch 1 of 10 Step 314 ntokens 11115600 Example 94200 of 138376 loss = 3.5041 nll loss = 2.1352 accu = 0.3689
Training: Epoch 1 of 10 Step 315 ntokens 11151000 Example 94500 of 138376 loss = 3.5040 nll loss = 2.1351 accu = 0.3690
Training: Epoch 1 of 10 Step 316 ntokens 11186400 Example 94800 of 138376 loss = 3.5040 nll loss = 2.1352 accu = 0.3689
Training: Epoch 1 of 10 Step 317 ntokens 11221800 Example 95100 of 138376 loss = 3.5041 nll loss = 2.1354 accu = 0.3689
Training: Epoch 1 of 10 Step 318 ntokens 11257200 Example 95400 of 138376 loss = 3.5043 nll loss = 2.1353 accu = 0.3689
Training: Epoch 1 of 10 Step 319 ntokens 11292600 Example 95700 of 138376 loss = 3.5041 nll loss = 2.1352 accu = 0.3689
Training: Epoch 1 of 10 Step 320 ntokens 11328000 Example 96000 of 138376 loss = 3.5042 nll loss = 2.1352 accu = 0.3689
Training: Epoch 1 of 10 Step 321 ntokens 11363400 Example 96300 of 138376 loss = 3.5040 nll loss = 2.1350 accu = 0.3690
Training: Epoch 1 of 10 Step 322 ntokens 11398800 Example 96600 of 138376 loss = 3.5038 nll loss = 2.1350 accu = 0.3690
Training: Epoch 1 of 10 Step 323 ntokens 11434200 Example 96900 of 138376 loss = 3.5038 nll loss = 2.1348 accu = 0.3690
Training: Epoch 1 of 10 Step 324 ntokens 11469600 Example 97200 of 138376 loss = 3.5039 nll loss = 2.1349 accu = 0.3690
Training: Epoch 1 of 10 Step 325 ntokens 11505000 Example 97500 of 138376 loss = 3.5038 nll loss = 2.1351 accu = 0.3690
Training: Epoch 1 of 10 Step 326 ntokens 11540400 Example 97800 of 138376 loss = 3.5040 nll loss = 2.1350 accu = 0.3690
Training: Epoch 1 of 10 Step 327 ntokens 11575800 Example 98100 of 138376 loss = 3.5042 nll loss = 2.1347 accu = 0.3691
Training: Epoch 1 of 10 Step 328 ntokens 11611200 Example 98400 of 138376 loss = 3.5042 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 329 ntokens 11646600 Example 98700 of 138376 loss = 3.5044 nll loss = 2.1347 accu = 0.3691
Training: Epoch 1 of 10 Step 330 ntokens 11682000 Example 99000 of 138376 loss = 3.5046 nll loss = 2.1347 accu = 0.3691
Training: Epoch 1 of 10 Step 331 ntokens 11717400 Example 99300 of 138376 loss = 3.5042 nll loss = 2.1346 accu = 0.3691
Training: Epoch 1 of 10 Step 332 ntokens 11752800 Example 99600 of 138376 loss = 3.5042 nll loss = 2.1343 accu = 0.3692
Training: Epoch 1 of 10 Step 333 ntokens 11788200 Example 99900 of 138376 loss = 3.5042 nll loss = 2.1341 accu = 0.3693
Training: Epoch 1 of 10 Step 334 ntokens 11823600 Example 100200 of 138376 loss = 3.5042 nll loss = 2.1340 accu = 0.3693
Training: Epoch 1 of 10 Step 335 ntokens 11859000 Example 100500 of 138376 loss = 3.5044 nll loss = 2.1341 accu = 0.3693
Training: Epoch 1 of 10 Step 336 ntokens 11894400 Example 100800 of 138376 loss = 3.5044 nll loss = 2.1341 accu = 0.3693
Training: Epoch 1 of 10 Step 337 ntokens 11929800 Example 101100 of 138376 loss = 3.5045 nll loss = 2.1341 accu = 0.3693
Training: Epoch 1 of 10 Step 338 ntokens 11965200 Example 101400 of 138376 loss = 3.5047 nll loss = 2.1339 accu = 0.3694
Training: Epoch 1 of 10 Step 339 ntokens 12000600 Example 101700 of 138376 loss = 3.5049 nll loss = 2.1335 accu = 0.3695
Training: Epoch 1 of 10 Step 340 ntokens 12036000 Example 102000 of 138376 loss = 3.5047 nll loss = 2.1337 accu = 0.3695
Training: Epoch 1 of 10 Step 341 ntokens 12071400 Example 102300 of 138376 loss = 3.5046 nll loss = 2.1335 accu = 0.3695
Training: Epoch 1 of 10 Step 342 ntokens 12106800 Example 102600 of 138376 loss = 3.5041 nll loss = 2.1335 accu = 0.3695
Training: Epoch 1 of 10 Step 343 ntokens 12142200 Example 102900 of 138376 loss = 3.5043 nll loss = 2.1337 accu = 0.3695
Training: Epoch 1 of 10 Step 344 ntokens 12177600 Example 103200 of 138376 loss = 3.5043 nll loss = 2.1336 accu = 0.3695
Training: Epoch 1 of 10 Step 345 ntokens 12213000 Example 103500 of 138376 loss = 3.5045 nll loss = 2.1336 accu = 0.3695
Training: Epoch 1 of 10 Step 346 ntokens 12248400 Example 103800 of 138376 loss = 3.5044 nll loss = 2.1332 accu = 0.3696
Training: Epoch 1 of 10 Step 347 ntokens 12283800 Example 104100 of 138376 loss = 3.5046 nll loss = 2.1333 accu = 0.3696
Training: Epoch 1 of 10 Step 348 ntokens 12319200 Example 104400 of 138376 loss = 3.5046 nll loss = 2.1332 accu = 0.3697
Training: Epoch 1 of 10 Step 349 ntokens 12354600 Example 104700 of 138376 loss = 3.5047 nll loss = 2.1329 accu = 0.3697
Training: Epoch 1 of 10 Step 350 ntokens 12390000 Example 105000 of 138376 loss = 3.5045 nll loss = 2.1326 accu = 0.3698
Training: Epoch 1 of 10 Step 351 ntokens 12425400 Example 105300 of 138376 loss = 3.5048 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 352 ntokens 12460800 Example 105600 of 138376 loss = 3.5051 nll loss = 2.1325 accu = 0.3699
Training: Epoch 1 of 10 Step 353 ntokens 12496200 Example 105900 of 138376 loss = 3.5050 nll loss = 2.1324 accu = 0.3699
Training: Epoch 1 of 10 Step 354 ntokens 12531600 Example 106200 of 138376 loss = 3.5049 nll loss = 2.1322 accu = 0.3700
Training: Epoch 1 of 10 Step 355 ntokens 12567000 Example 106500 of 138376 loss = 3.5048 nll loss = 2.1322 accu = 0.3700
Training: Epoch 1 of 10 Step 356 ntokens 12602400 Example 106800 of 138376 loss = 3.5047 nll loss = 2.1322 accu = 0.3700
Training: Epoch 1 of 10 Step 357 ntokens 12637800 Example 107100 of 138376 loss = 3.5048 nll loss = 2.1323 accu = 0.3700
Training: Epoch 1 of 10 Step 358 ntokens 12673200 Example 107400 of 138376 loss = 3.5049 nll loss = 2.1324 accu = 0.3700
Training: Epoch 1 of 10 Step 359 ntokens 12708600 Example 107700 of 138376 loss = 3.5048 nll loss = 2.1323 accu = 0.3700
Training: Epoch 1 of 10 Step 360 ntokens 12744000 Example 108000 of 138376 loss = 3.5050 nll loss = 2.1324 accu = 0.3699
Training: Epoch 1 of 10 Step 361 ntokens 12779400 Example 108300 of 138376 loss = 3.5051 nll loss = 2.1325 accu = 0.3699
Training: Epoch 1 of 10 Step 362 ntokens 12814800 Example 108600 of 138376 loss = 3.5051 nll loss = 2.1324 accu = 0.3699
Training: Epoch 1 of 10 Step 363 ntokens 12850200 Example 108900 of 138376 loss = 3.5051 nll loss = 2.1324 accu = 0.3699
Training: Epoch 1 of 10 Step 364 ntokens 12885600 Example 109200 of 138376 loss = 3.5049 nll loss = 2.1324 accu = 0.3699
Training: Epoch 1 of 10 Step 365 ntokens 12921000 Example 109500 of 138376 loss = 3.5051 nll loss = 2.1322 accu = 0.3700
Training: Epoch 1 of 10 Step 366 ntokens 12956400 Example 109800 of 138376 loss = 3.5050 nll loss = 2.1321 accu = 0.3701
Training: Epoch 1 of 10 Step 367 ntokens 12991800 Example 110100 of 138376 loss = 3.5051 nll loss = 2.1321 accu = 0.3701
Training: Epoch 1 of 10 Step 368 ntokens 13027200 Example 110400 of 138376 loss = 3.5050 nll loss = 2.1321 accu = 0.3701
Training: Epoch 1 of 10 Step 369 ntokens 13062600 Example 110700 of 138376 loss = 3.5052 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 370 ntokens 13098000 Example 111000 of 138376 loss = 3.5051 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 371 ntokens 13133400 Example 111300 of 138376 loss = 3.5051 nll loss = 2.1319 accu = 0.3702
Training: Epoch 1 of 10 Step 372 ntokens 13168800 Example 111600 of 138376 loss = 3.5049 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 373 ntokens 13204200 Example 111900 of 138376 loss = 3.5047 nll loss = 2.1316 accu = 0.3703
Training: Epoch 1 of 10 Step 374 ntokens 13239600 Example 112200 of 138376 loss = 3.5044 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 375 ntokens 13275000 Example 112500 of 138376 loss = 3.5043 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 376 ntokens 13310400 Example 112800 of 138376 loss = 3.5042 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 377 ntokens 13345800 Example 113100 of 138376 loss = 3.5042 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 378 ntokens 13381200 Example 113400 of 138376 loss = 3.5042 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 379 ntokens 13416600 Example 113700 of 138376 loss = 3.5039 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 380 ntokens 13452000 Example 114000 of 138376 loss = 3.5038 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 381 ntokens 13487400 Example 114300 of 138376 loss = 3.5039 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 382 ntokens 13522800 Example 114600 of 138376 loss = 3.5037 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 383 ntokens 13558200 Example 114900 of 138376 loss = 3.5038 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 384 ntokens 13593600 Example 115200 of 138376 loss = 3.5038 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 385 ntokens 13629000 Example 115500 of 138376 loss = 3.5036 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 386 ntokens 13664400 Example 115800 of 138376 loss = 3.5033 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 387 ntokens 13699800 Example 116100 of 138376 loss = 3.5033 nll loss = 2.1319 accu = 0.3702
Training: Epoch 1 of 10 Step 388 ntokens 13735200 Example 116400 of 138376 loss = 3.5034 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 389 ntokens 13770600 Example 116700 of 138376 loss = 3.5034 nll loss = 2.1316 accu = 0.3703
Training: Epoch 1 of 10 Step 390 ntokens 13806000 Example 117000 of 138376 loss = 3.5033 nll loss = 2.1316 accu = 0.3703
Training: Epoch 1 of 10 Step 391 ntokens 13841400 Example 117300 of 138376 loss = 3.5031 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 392 ntokens 13876800 Example 117600 of 138376 loss = 3.5029 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 393 ntokens 13912200 Example 117900 of 138376 loss = 3.5028 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 394 ntokens 13947600 Example 118200 of 138376 loss = 3.5028 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 395 ntokens 13983000 Example 118500 of 138376 loss = 3.5028 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 396 ntokens 14018400 Example 118800 of 138376 loss = 3.5028 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 397 ntokens 14053800 Example 119100 of 138376 loss = 3.5027 nll loss = 2.1314 accu = 0.3703
Training: Epoch 1 of 10 Step 398 ntokens 14089200 Example 119400 of 138376 loss = 3.5025 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 399 ntokens 14124600 Example 119700 of 138376 loss = 3.5027 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 400 ntokens 14160000 Example 120000 of 138376 loss = 3.5027 nll loss = 2.1315 accu = 0.3703
Training: Epoch 1 of 10 Step 401 ntokens 14195400 Example 120300 of 138376 loss = 3.5028 nll loss = 2.1315 accu = 0.3703
Training: Epoch 1 of 10 Step 402 ntokens 14230800 Example 120600 of 138376 loss = 3.5028 nll loss = 2.1315 accu = 0.3703
Training: Epoch 1 of 10 Step 403 ntokens 14266200 Example 120900 of 138376 loss = 3.5031 nll loss = 2.1315 accu = 0.3703
Training: Epoch 1 of 10 Step 404 ntokens 14301600 Example 121200 of 138376 loss = 3.5030 nll loss = 2.1315 accu = 0.3703
Training: Epoch 1 of 10 Step 405 ntokens 14337000 Example 121500 of 138376 loss = 3.5030 nll loss = 2.1316 accu = 0.3702
Training: Epoch 1 of 10 Step 406 ntokens 14372400 Example 121800 of 138376 loss = 3.5033 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 407 ntokens 14407800 Example 122100 of 138376 loss = 3.5032 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 408 ntokens 14443200 Example 122400 of 138376 loss = 3.5032 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 409 ntokens 14478600 Example 122700 of 138376 loss = 3.5034 nll loss = 2.1320 accu = 0.3701
Training: Epoch 1 of 10 Step 410 ntokens 14514000 Example 123000 of 138376 loss = 3.5035 nll loss = 2.1320 accu = 0.3701
Training: Epoch 1 of 10 Step 411 ntokens 14549400 Example 123300 of 138376 loss = 3.5038 nll loss = 2.1319 accu = 0.3702
Training: Epoch 1 of 10 Step 412 ntokens 14584800 Example 123600 of 138376 loss = 3.5037 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 413 ntokens 14620200 Example 123900 of 138376 loss = 3.5035 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 414 ntokens 14655600 Example 124200 of 138376 loss = 3.5033 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 415 ntokens 14691000 Example 124500 of 138376 loss = 3.5031 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 416 ntokens 14726400 Example 124800 of 138376 loss = 3.5035 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 417 ntokens 14761800 Example 125100 of 138376 loss = 3.5034 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 418 ntokens 14797200 Example 125400 of 138376 loss = 3.5034 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 419 ntokens 14832600 Example 125700 of 138376 loss = 3.5032 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 420 ntokens 14868000 Example 126000 of 138376 loss = 3.5032 nll loss = 2.1317 accu = 0.3702
Training: Epoch 1 of 10 Step 421 ntokens 14903400 Example 126300 of 138376 loss = 3.5031 nll loss = 2.1318 accu = 0.3702
Training: Epoch 1 of 10 Step 422 ntokens 14938800 Example 126600 of 138376 loss = 3.5031 nll loss = 2.1318 accu = 0.3701
Training: Epoch 1 of 10 Step 423 ntokens 14974200 Example 126900 of 138376 loss = 3.5030 nll loss = 2.1320 accu = 0.3701
Training: Epoch 1 of 10 Step 424 ntokens 15009600 Example 127200 of 138376 loss = 3.5029 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 425 ntokens 15045000 Example 127500 of 138376 loss = 3.5031 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 426 ntokens 15080400 Example 127800 of 138376 loss = 3.5032 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 427 ntokens 15115800 Example 128100 of 138376 loss = 3.5031 nll loss = 2.1319 accu = 0.3701
Training: Epoch 1 of 10 Step 428 ntokens 15151200 Example 128400 of 138376 loss = 3.5030 nll loss = 2.1320 accu = 0.3701
Training: Epoch 1 of 10 Step 429 ntokens 15186600 Example 128700 of 138376 loss = 3.5029 nll loss = 2.1321 accu = 0.3700
Training: Epoch 1 of 10 Step 430 ntokens 15222000 Example 129000 of 138376 loss = 3.5028 nll loss = 2.1323 accu = 0.3700
Training: Epoch 1 of 10 Step 431 ntokens 15257400 Example 129300 of 138376 loss = 3.5029 nll loss = 2.1325 accu = 0.3699
Training: Epoch 1 of 10 Step 432 ntokens 15292800 Example 129600 of 138376 loss = 3.5027 nll loss = 2.1325 accu = 0.3699
Training: Epoch 1 of 10 Step 433 ntokens 15328200 Example 129900 of 138376 loss = 3.5026 nll loss = 2.1323 accu = 0.3700
Training: Epoch 1 of 10 Step 434 ntokens 15363600 Example 130200 of 138376 loss = 3.5025 nll loss = 2.1324 accu = 0.3700
Training: Epoch 1 of 10 Step 435 ntokens 15399000 Example 130500 of 138376 loss = 3.5026 nll loss = 2.1325 accu = 0.3699
Training: Epoch 1 of 10 Step 436 ntokens 15434400 Example 130800 of 138376 loss = 3.5026 nll loss = 2.1326 accu = 0.3699
Training: Epoch 1 of 10 Step 437 ntokens 15469800 Example 131100 of 138376 loss = 3.5028 nll loss = 2.1326 accu = 0.3699
Training: Epoch 1 of 10 Step 438 ntokens 15505200 Example 131400 of 138376 loss = 3.5030 nll loss = 2.1326 accu = 0.3699
Training: Epoch 1 of 10 Step 439 ntokens 15540600 Example 131700 of 138376 loss = 3.5031 nll loss = 2.1326 accu = 0.3699
Training: Epoch 1 of 10 Step 440 ntokens 15576000 Example 132000 of 138376 loss = 3.5030 nll loss = 2.1327 accu = 0.3699
Training: Epoch 1 of 10 Step 441 ntokens 15611400 Example 132300 of 138376 loss = 3.5026 nll loss = 2.1327 accu = 0.3699
Training: Epoch 1 of 10 Step 442 ntokens 15646800 Example 132600 of 138376 loss = 3.5026 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 443 ntokens 15682200 Example 132900 of 138376 loss = 3.5026 nll loss = 2.1328 accu = 0.3699
Training: Epoch 1 of 10 Step 444 ntokens 15717600 Example 133200 of 138376 loss = 3.5022 nll loss = 2.1327 accu = 0.3699
Training: Epoch 1 of 10 Step 445 ntokens 15753000 Example 133500 of 138376 loss = 3.5022 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 446 ntokens 15788400 Example 133800 of 138376 loss = 3.5019 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 447 ntokens 15823800 Example 134100 of 138376 loss = 3.5019 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 448 ntokens 15859200 Example 134400 of 138376 loss = 3.5020 nll loss = 2.1329 accu = 0.3698
Training: Epoch 1 of 10 Step 449 ntokens 15894600 Example 134700 of 138376 loss = 3.5019 nll loss = 2.1331 accu = 0.3697
Training: Epoch 1 of 10 Step 450 ntokens 15930000 Example 135000 of 138376 loss = 3.5020 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 451 ntokens 15965400 Example 135300 of 138376 loss = 3.5019 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 452 ntokens 16000800 Example 135600 of 138376 loss = 3.5019 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 453 ntokens 16036200 Example 135900 of 138376 loss = 3.5022 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 454 ntokens 16071600 Example 136200 of 138376 loss = 3.5023 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 455 ntokens 16107000 Example 136500 of 138376 loss = 3.5022 nll loss = 2.1328 accu = 0.3699
Training: Epoch 1 of 10 Step 456 ntokens 16142400 Example 136800 of 138376 loss = 3.5024 nll loss = 2.1327 accu = 0.3699
Training: Epoch 1 of 10 Step 457 ntokens 16177800 Example 137100 of 138376 loss = 3.5024 nll loss = 2.1328 accu = 0.3699
Training: Epoch 1 of 10 Step 458 ntokens 16213200 Example 137400 of 138376 loss = 3.5022 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 459 ntokens 16248600 Example 137700 of 138376 loss = 3.5023 nll loss = 2.1328 accu = 0.3698
Training: Epoch 1 of 10 Step 460 ntokens 16284000 Example 138000 of 138376 loss = 3.5024 nll loss = 2.1329 accu = 0.3698
Training: Epoch 1 of 10 Step 461 ntokens 16319400 Example 138300 of 138376 loss = 3.5023 nll loss = 2.1330 accu = 0.3698
Training: Epoch 1 of 10 Step 462 ntokens 16328368 Example 138376 of 138376 loss = 3.5021 nll loss = 2.1329 accu = 0.3698
Writing to checkpoint at 2024-05-28 16:50:31.521877
Validating: Epoch 1 of 10 Step 0 ntokens 16328368 Example 300 of 34323 loss = 3.4225 nll loss = 2.0832 accu = 0.3899
Validating: Epoch 1 of 10 Step 1 ntokens 16328368 Example 600 of 34323 loss = 3.4240 nll loss = 2.1183 accu = 0.3777
Validating: Epoch 1 of 10 Step 2 ntokens 16328368 Example 900 of 34323 loss = 3.4277 nll loss = 2.1264 accu = 0.3735
Validating: Epoch 1 of 10 Step 3 ntokens 16328368 Example 1200 of 34323 loss = 3.4502 nll loss = 2.1243 accu = 0.3741
Validating: Epoch 1 of 10 Step 4 ntokens 16328368 Example 1500 of 34323 loss = 3.4590 nll loss = 2.1217 accu = 0.3743
Validating: Epoch 1 of 10 Step 5 ntokens 16328368 Example 1800 of 34323 loss = 3.4658 nll loss = 2.1244 accu = 0.3723
Validating: Epoch 1 of 10 Step 6 ntokens 16328368 Example 2100 of 34323 loss = 3.4646 nll loss = 2.1264 accu = 0.3711
Validating: Epoch 1 of 10 Step 7 ntokens 16328368 Example 2400 of 34323 loss = 3.4694 nll loss = 2.1339 accu = 0.3684
Validating: Epoch 1 of 10 Step 8 ntokens 16328368 Example 2700 of 34323 loss = 3.4664 nll loss = 2.1437 accu = 0.3653
Validating: Epoch 1 of 10 Step 9 ntokens 16328368 Example 3000 of 34323 loss = 3.4669 nll loss = 2.1347 accu = 0.3687
Validating: Epoch 1 of 10 Step 10 ntokens 16328368 Example 3300 of 34323 loss = 3.4772 nll loss = 2.1392 accu = 0.3672
Validating: Epoch 1 of 10 Step 11 ntokens 16328368 Example 3600 of 34323 loss = 3.4858 nll loss = 2.1386 accu = 0.3673
Validating: Epoch 1 of 10 Step 12 ntokens 16328368 Example 3900 of 34323 loss = 3.4907 nll loss = 2.1433 accu = 0.3658
Validating: Epoch 1 of 10 Step 13 ntokens 16328368 Example 4200 of 34323 loss = 3.4795 nll loss = 2.1398 accu = 0.3670
Validating: Epoch 1 of 10 Step 14 ntokens 16328368 Example 4500 of 34323 loss = 3.4754 nll loss = 2.1342 accu = 0.3686
Validating: Epoch 1 of 10 Step 15 ntokens 16328368 Example 4800 of 34323 loss = 3.4804 nll loss = 2.1342 accu = 0.3685
Validating: Epoch 1 of 10 Step 16 ntokens 16328368 Example 5100 of 34323 loss = 3.4824 nll loss = 2.1339 accu = 0.3687
Validating: Epoch 1 of 10 Step 17 ntokens 16328368 Example 5400 of 34323 loss = 3.4846 nll loss = 2.1353 accu = 0.3682
Validating: Epoch 1 of 10 Step 18 ntokens 16328368 Example 5700 of 34323 loss = 3.4850 nll loss = 2.1315 accu = 0.3696
Validating: Epoch 1 of 10 Step 19 ntokens 16328368 Example 6000 of 34323 loss = 3.4898 nll loss = 2.1272 accu = 0.3712
Validating: Epoch 1 of 10 Step 20 ntokens 16328368 Example 6300 of 34323 loss = 3.4883 nll loss = 2.1265 accu = 0.3715
Validating: Epoch 1 of 10 Step 21 ntokens 16328368 Example 6600 of 34323 loss = 3.4859 nll loss = 2.1229 accu = 0.3726
Validating: Epoch 1 of 10 Step 22 ntokens 16328368 Example 6900 of 34323 loss = 3.4819 nll loss = 2.1227 accu = 0.3725
Validating: Epoch 1 of 10 Step 23 ntokens 16328368 Example 7200 of 34323 loss = 3.4820 nll loss = 2.1226 accu = 0.3725
Validating: Epoch 1 of 10 Step 24 ntokens 16328368 Example 7500 of 34323 loss = 3.4822 nll loss = 2.1257 accu = 0.3713
Validating: Epoch 1 of 10 Step 25 ntokens 16328368 Example 7800 of 34323 loss = 3.4822 nll loss = 2.1290 accu = 0.3703
Validating: Epoch 1 of 10 Step 26 ntokens 16328368 Example 8100 of 34323 loss = 3.4840 nll loss = 2.1267 accu = 0.3710
Validating: Epoch 1 of 10 Step 27 ntokens 16328368 Example 8400 of 34323 loss = 3.4852 nll loss = 2.1273 accu = 0.3708
Validating: Epoch 1 of 10 Step 28 ntokens 16328368 Example 8700 of 34323 loss = 3.4857 nll loss = 2.1272 accu = 0.3707
Validating: Epoch 1 of 10 Step 29 ntokens 16328368 Example 9000 of 34323 loss = 3.4873 nll loss = 2.1276 accu = 0.3705
Validating: Epoch 1 of 10 Step 30 ntokens 16328368 Example 9300 of 34323 loss = 3.4884 nll loss = 2.1276 accu = 0.3705
Validating: Epoch 1 of 10 Step 31 ntokens 16328368 Example 9600 of 34323 loss = 3.4872 nll loss = 2.1261 accu = 0.3710
Validating: Epoch 1 of 10 Step 32 ntokens 16328368 Example 9900 of 34323 loss = 3.4907 nll loss = 2.1263 accu = 0.3708
Validating: Epoch 1 of 10 Step 33 ntokens 16328368 Example 10200 of 34323 loss = 3.4918 nll loss = 2.1272 accu = 0.3705
Validating: Epoch 1 of 10 Step 34 ntokens 16328368 Example 10500 of 34323 loss = 3.4880 nll loss = 2.1256 accu = 0.3711
Validating: Epoch 1 of 10 Step 35 ntokens 16328368 Example 10800 of 34323 loss = 3.4883 nll loss = 2.1264 accu = 0.3708