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epoch:1390 | train loss: 0.201862| val loss:0.193363
epoch:1391 | train loss: 0.203910| val loss:0.194211
epoch:1392 | train loss: 0.203959| val loss:0.194609
epoch:1393 | train loss: 0.203588| val loss:0.192591
epoch:1394 | train loss: 0.203608| val loss:0.196056
epoch:1395 | train loss: 0.201736| val loss:0.195963
epoch:1396 | train loss: 0.203398| val loss:0.198730
epoch:1397 | train loss: 0.203348| val loss:0.197731
epoch:1398 | train loss: 0.201597| val loss:0.193376
epoch:1399 | train loss: 0.201475| val loss:0.194192
epoch:1400 | train loss: 0.201015| val loss:0.194817
epoch:1401 | train loss: 0.203192| val loss:0.196605
epoch:1402 | train loss: 0.201734| val loss:0.194924
epoch:1403 | train loss: 0.203154| val loss:0.199293
epoch:1404 | train loss: 0.203765| val loss:0.190797
epoch:1405 | train loss: 0.201737| val loss:0.194512
epoch:1406 | train loss: 0.202420| val loss:0.193439
epoch:1407 | train loss: 0.200567| val loss:0.194076
epoch:1408 | train loss: 0.201970| val loss:0.190695
epoch:1409 | train loss: 0.201829| val loss:0.195664
epoch:1410 | train loss: 0.202615| val loss:0.198055
epoch:1411 | train loss: 0.204476| val loss:0.195215
epoch:1412 | train loss: 0.203077| val loss:0.199454
epoch:1413 | train loss: 0.202578| val loss:0.191927
epoch:1414 | train loss: 0.201459| val loss:0.189983
epoch:1415 | train loss: 0.203292| val loss:0.191874
epoch:1416 | train loss: 0.200841| val loss:0.192877
epoch:1417 | train loss: 0.203184| val loss:0.190841
epoch:1418 | train loss: 0.205106| val loss:0.201426
epoch:1419 | train loss: 0.200670| val loss:0.197777
epoch:1420 | train loss: 0.201639| val loss:0.192157
epoch:1421 | train loss: 0.201607| val loss:0.196955
epoch:1422 | train loss: 0.202532| val loss:0.186668
epoch:1423 | train loss: 0.201964| val loss:0.198640
epoch:1424 | train loss: 0.201833| val loss:0.194243
epoch:1425 | train loss: 0.201158| val loss:0.195694
epoch:1426 | train loss: 0.204001| val loss:0.192618
epoch:1427 | train loss: 0.204263| val loss:0.199572
epoch:1428 | train loss: 0.203521| val loss:0.193107
epoch:1429 | train loss: 0.203972| val loss:0.199244
epoch:1430 | train loss: 0.202293| val loss:0.207017
epoch:1431 | train loss: 0.201722| val loss:0.196753
epoch:1432 | train loss: 0.202746| val loss:0.196763
epoch:1433 | train loss: 0.201965| val loss:0.195234
epoch:1434 | train loss: 0.202482| val loss:0.201148
epoch:1435 | train loss: 0.201740| val loss:0.190007
epoch:1436 | train loss: 0.202695| val loss:0.195059
epoch:1437 | train loss: 0.202983| val loss:0.189806
epoch:1438 | train loss: 0.204399| val loss:0.195561
epoch:1439 | train loss: 0.203092| val loss:0.196085
epoch:1440 | train loss: 0.201413| val loss:0.192365
epoch:1441 | train loss: 0.202460| val loss:0.193892
epoch:1442 | train loss: 0.202569| val loss:0.198467
epoch:1443 | train loss: 0.201168| val loss:0.201115
epoch:1444 | train loss: 0.203003| val loss:0.202918
epoch:1445 | train loss: 0.200936| val loss:0.193298
epoch:1446 | train loss: 0.201428| val loss:0.193871
epoch:1447 | train loss: 0.200742| val loss:0.193456
epoch:1448 | train loss: 0.202471| val loss:0.191137
epoch:1449 | train loss: 0.202115| val loss:0.199204
epoch:1450 | train loss: 0.200694| val loss:0.191933
epoch:1451 | train loss: 0.200832| val loss:0.199775
epoch:1452 | train loss: 0.202911| val loss:0.197485
epoch:1453 | train loss: 0.200883| val loss:0.195984
epoch:1454 | train loss: 0.202338| val loss:0.186704
epoch:1455 | train loss: 0.200935| val loss:0.195417
epoch:1456 | train loss: 0.202451| val loss:0.193369
epoch:1457 | train loss: 0.200738| val loss:0.192176
epoch:1458 | train loss: 0.202083| val loss:0.190694
epoch:1459 | train loss: 0.202260| val loss:0.196842
epoch:1460 | train loss: 0.200077| val loss:0.193048
epoch:1461 | train loss: 0.201689| val loss:0.200758
epoch:1462 | train loss: 0.201651| val loss:0.193701
epoch:1463 | train loss: 0.203024| val loss:0.200105
epoch:1464 | train loss: 0.200325| val loss:0.197712
epoch:1465 | train loss: 0.202845| val loss:0.196690
epoch:1466 | train loss: 0.201437| val loss:0.193635
epoch:1467 | train loss: 0.204094| val loss:0.199249
epoch:1468 | train loss: 0.201572| val loss:0.196302
epoch:1469 | train loss: 0.201392| val loss:0.195769
epoch:1470 | train loss: 0.201976| val loss:0.196009
epoch:1471 | train loss: 0.202823| val loss:0.198577
epoch:1472 | train loss: 0.201936| val loss:0.195261
epoch:1473 | train loss: 0.202408| val loss:0.193830
epoch:1474 | train loss: 0.200924| val loss:0.188498
epoch:1475 | train loss: 0.203428| val loss:0.194304
epoch:1476 | train loss: 0.200365| val loss:0.189317
epoch:1477 | train loss: 0.200788| val loss:0.198411
epoch:1478 | train loss: 0.200592| val loss:0.189944
epoch:1479 | train loss: 0.201318| val loss:0.192853
epoch:1480 | train loss: 0.200361| val loss:0.194768
epoch:1481 | train loss: 0.199744| val loss:0.194018
epoch:1482 | train loss: 0.202325| val loss:0.192354
epoch:1483 | train loss: 0.200784| val loss:0.194814
epoch:1484 | train loss: 0.202391| val loss:0.188862
epoch:1485 | train loss: 0.200507| val loss:0.191395
epoch:1486 | train loss: 0.200529| val loss:0.189926
epoch:1487 | train loss: 0.201278| val loss:0.186882
epoch:1488 | train loss: 0.203681| val loss:0.196815
epoch:1489 | train loss: 0.201108| val loss:0.190628
epoch:1490 | train loss: 0.200866| val loss:0.197889
epoch:1491 | train loss: 0.202496| val loss:0.195811
epoch:1492 | train loss: 0.199772| val loss:0.194443
epoch:1493 | train loss: 0.200500| val loss:0.186901
epoch:1494 | train loss: 0.202155| val loss:0.195334
epoch:1495 | train loss: 0.200612| val loss:0.193344
epoch:1496 | train loss: 0.201328| val loss:0.191139
epoch:1497 | train loss: 0.200899| val loss:0.187703
epoch:1498 | train loss: 0.199624| val loss:0.188716
epoch:1499 | train loss: 0.201218| val loss:0.197366
epoch:1500 | train loss: 0.202339| val loss:0.196045
epoch:1501 | train loss: 0.200984| val loss:0.191744
epoch:1502 | train loss: 0.200818| val loss:0.198461
epoch:1503 | train loss: 0.200576| val loss:0.202795
epoch:1504 | train loss: 0.200961| val loss:0.195557
epoch:1505 | train loss: 0.201137| val loss:0.191369
epoch:1506 | train loss: 0.202448| val loss:0.190703
epoch:1507 | train loss: 0.202645| val loss:0.196590
epoch:1508 | train loss: 0.200880| val loss:0.189077
epoch:1509 | train loss: 0.201376| val loss:0.197178
epoch:1510 | train loss: 0.200546| val loss:0.197578
epoch:1511 | train loss: 0.202449| val loss:0.195886
epoch:1512 | train loss: 0.203513| val loss:0.188580
epoch:1513 | train loss: 0.198864| val loss:0.192616
epoch:1514 | train loss: 0.200593| val loss:0.190274
epoch:1515 | train loss: 0.200203| val loss:0.191756
epoch:1516 | train loss: 0.200600| val loss:0.192984
epoch:1517 | train loss: 0.200211| val loss:0.193409
epoch:1518 | train loss: 0.202796| val loss:0.193335
epoch:1519 | train loss: 0.201613| val loss:0.190893
epoch:1520 | train loss: 0.202058| val loss:0.195610
epoch:1521 | train loss: 0.199559| val loss:0.197628
epoch:1522 | train loss: 0.200310| val loss:0.195887
epoch:1523 | train loss: 0.202061| val loss:0.193052
epoch:1524 | train loss: 0.201922| val loss:0.195381
epoch:1525 | train loss: 0.200070| val loss:0.194405
epoch:1526 | train loss: 0.200320| val loss:0.194586
epoch:1527 | train loss: 0.200766| val loss:0.191434
epoch:1528 | train loss: 0.201247| val loss:0.193195
epoch:1529 | train loss: 0.202030| val loss:0.195198
epoch:1530 | train loss: 0.200040| val loss:0.193340
epoch:1531 | train loss: 0.198750| val loss:0.190741
epoch:1532 | train loss: 0.201438| val loss:0.192671
epoch:1533 | train loss: 0.200065| val loss:0.192637
epoch:1534 | train loss: 0.198941| val loss:0.198190
epoch:1535 | train loss: 0.202309| val loss:0.191691
epoch:1536 | train loss: 0.200160| val loss:0.190169
epoch:1537 | train loss: 0.200883| val loss:0.193292
epoch:1538 | train loss: 0.200664| val loss:0.190362
epoch:1539 | train loss: 0.199261| val loss:0.194202
epoch:1540 | train loss: 0.199599| val loss:0.195828
epoch:1541 | train loss: 0.199770| val loss:0.191859
epoch:1542 | train loss: 0.200639| val loss:0.199260
epoch:1543 | train loss: 0.199924| val loss:0.196921
epoch:1544 | train loss: 0.202155| val loss:0.194221
epoch:1545 | train loss: 0.199705| val loss:0.195627
epoch:1546 | train loss: 0.200467| val loss:0.199901
epoch:1547 | train loss: 0.201356| val loss:0.192366
epoch:1548 | train loss: 0.200617| val loss:0.189801
epoch:1549 | train loss: 0.201330| val loss:0.195190
epoch:1550 | train loss: 0.199819| val loss:0.196333
epoch:1551 | train loss: 0.201218| val loss:0.196204
epoch:1552 | train loss: 0.200105| val loss:0.199086
epoch:1553 | train loss: 0.200053| val loss:0.189636
epoch:1554 | train loss: 0.199931| val loss:0.183812
epoch:1555 | train loss: 0.199304| val loss:0.192308
epoch:1556 | train loss: 0.200223| val loss:0.195970
epoch:1557 | train loss: 0.201489| val loss:0.188374
epoch:1558 | train loss: 0.199793| val loss:0.193833
epoch:1559 | train loss: 0.199701| val loss:0.193561
epoch:1560 | train loss: 0.198899| val loss:0.188953
epoch:1561 | train loss: 0.199639| val loss:0.186627
epoch:1562 | train loss: 0.201592| val loss:0.192096
epoch:1563 | train loss: 0.199323| val loss:0.193749
epoch:1564 | train loss: 0.198408| val loss:0.193490
epoch:1565 | train loss: 0.198681| val loss:0.190408
epoch:1566 | train loss: 0.202638| val loss:0.192632
epoch:1567 | train loss: 0.199932| val loss:0.194809
epoch:1568 | train loss: 0.199603| val loss:0.190711
epoch:1569 | train loss: 0.198981| val loss:0.198489
epoch:1570 | train loss: 0.198634| val loss:0.193805
epoch:1571 | train loss: 0.200580| val loss:0.197112
epoch:1572 | train loss: 0.200135| val loss:0.187298
epoch:1573 | train loss: 0.199523| val loss:0.198394
epoch:1574 | train loss: 0.199697| val loss:0.189719
epoch:1575 | train loss: 0.199473| val loss:0.199311
epoch:1576 | train loss: 0.200723| val loss:0.187605
epoch:1577 | train loss: 0.200951| val loss:0.195884
epoch:1578 | train loss: 0.199139| val loss:0.194248
epoch:1579 | train loss: 0.200227| val loss:0.196468
epoch:1580 | train loss: 0.199862| val loss:0.196978
epoch:1581 | train loss: 0.198803| val loss:0.192217
epoch:1582 | train loss: 0.200718| val loss:0.189446
epoch:1583 | train loss: 0.199295| val loss:0.193346
epoch:1584 | train loss: 0.198920| val loss:0.196411
epoch:1585 | train loss: 0.200621| val loss:0.190045
epoch:1586 | train loss: 0.200290| val loss:0.191686
epoch:1587 | train loss: 0.200102| val loss:0.193830
epoch:1588 | train loss: 0.199902| val loss:0.193982
epoch:1589 | train loss: 0.200781| val loss:0.196982
epoch:1590 | train loss: 0.199002| val loss:0.193058