{ "complete": true, "config": { "teacher_width": 64, "student_width": 16, "epochs": 80, "qat_epochs": 20, "batch_size": 64, "lr": 0.003, "qat_lr": 0.0003, "weight_decay": 0.0001, "temperature": 2.0, "alpha": 0.7, "teacher_seed": 2038, "student_seed": 2039, "order_seed": 2040, "max_accuracy_drop": 0.01, "max_state_bytes": 6000 }, "selected": "qat4", "data_sha256": "bf15541d2af22ec89e24e7e7f0ecb2d6c31c7e56ce48a47152000df20b73a4b5", "environment": { "python": "3.12.12", "torch": "2.14.1", "device": "cpu", "dtype": "float32", "threads": 1 }, "split_ids": [ [ 1104, 1792, 234, 206, 633, 1748, 931, 330, 954, 1556, 168, 1740, 793, 854, 630, 1575, 956, 201, 1004, 419, 1745, 560, 1541, 149, 915, 1451, 1221, 637, 1249, 1651, 1284, 1638, 1787, 1654, 669, 621, 921, 1607, 858, 1713, 1048, 214, 814, 7, 156, 159, 50, 1059, 1566, 68, 375, 1645, 548, 1507, 1248, 573, 1064, 695, 892, 1256, 674, 147, 745, 1120, 1074, 1715, 1243, 86, 1258, 568, 624, 369, 1622, 1610, 1140, 804, 866, 485, 1635, 913, 606, 97, 664, 861, 601, 358, 597, 338, 1518, 487, 1735, 1358, 1219, 212, 928, 1112, 481, 1049, 500, 1423, 1138, 1135, 571, 6, 489, 1382, 1475, 1643, 1163, 1617, 1410, 976, 1017, 247, 1371, 329, 301, 1009, 562, 1229, 982, 961, 1754, 1355, 64, 1591, 192, 17, 1483, 590, 917, 806, 1776, 83, 1024, 1716, 1567, 1141, 1038, 869, 270, 1599, 1664, 1396, 31, 1292, 1671, 805, 566, 172, 474, 703, 1565, 999, 1499, 1559, 137, 872, 484, 1090, 828, 1021, 775, 1746, 553, 1198, 1712, 1470, 1524, 1444, 337, 1437, 1427, 1168, 1693, 938, 912, 559, 1342, 70, 1770, 668, 1164, 1729, 1132, 1357, 496, 352, 42, 1578, 655, 865, 835, 924, 488, 776, 1511, 222, 625, 1287, 1611, 1190, 813, 1794, 21, 1691, 1502, 1482, 1694, 1325, 966, 255, 230, 1459, 1055, 1598, 1328, 188, 174, 838, 891, 1121, 1231, 110, 1222, 1774, 992, 950, 1460, 1200, 1585, 971, 455, 1299, 945, 56, 180, 475, 1530, 983, 1405, 1529, 288, 1731, 272, 719, 88, 71, 1500, 529, 831, 1372, 381, 1572, 1453, 1044, 133, 452, 659, 1329, 1438, 729, 1088, 1111, 1481, 1717, 1692, 996, 43, 932, 215, 351, 616, 1257, 177, 357, 1620, 1764, 118, 94, 1554, 203, 92, 943, 403, 1478, 1684, 1561, 1790, 1535, 447, 641, 697, 673, 534, 1136, 434, 788, 1706, 1702, 125, 885, 285, 654, 428, 1107, 985, 994, 291, 1099, 1711, 1010, 1796, 1113, 649, 1084, 421, 240, 1710, 1193, 1095, 841, 1781, 1399, 1759, 1143, 1494, 605, 51, 783, 1208, 1788, 348, 536, 1726, 714, 1686, 1236, 102, 502, 1250, 1644, 173, 900, 946, 1557, 130, 389, 18, 870, 705, 1564, 984, 1110, 1323, 218, 1052, 1264, 561, 802, 207, 210, 67, 934, 1277, 380, 1131, 851, 1158, 187, 1089, 734, 1425, 208, 1397, 1224, 595, 910, 1011, 1156, 919, 1283, 202, 299, 622, 795, 1191, 300, 1626, 563, 1351, 433, 600, 109, 1416, 1709, 798, 1239, 1057, 1527, 516, 739, 1269, 1388, 642, 52, 557, 825, 1474, 1047, 1050, 298, 191, 1028, 165, 1653, 1484, 304, 274, 362, 1226, 618, 1741, 1450, 1751, 927, 1560, 10, 721, 476, 718, 850, 1237, 483, 1253, 978, 1102, 1232, 1187, 747, 1032, 1373, 977, 1006, 750, 227, 1493, 209, 1498, 261, 503, 1162, 844, 167, 656, 378, 1312, 1571, 1278, 1689, 1094, 530, 1091, 401, 268, 1302, 1661, 1350, 853, 513, 449, 1526, 1001, 13, 453, 1521, 661, 760, 634, 1144, 1061, 584, 1340, 758, 221, 834, 1288, 393, 1435, 716, 411, 933, 416, 923, 1586, 492, 63, 1015, 254, 238, 1725, 1154, 242, 650, 713, 583, 1063, 878, 823, 150, 444, 1363, 450, 1642, 1555, 607, 62, 1142, 1779, 0, 1040, 140, 1147, 100, 1202, 1536, 906, 1331, 1457, 953, 171, 1462, 371, 576, 318, 1497, 670, 738, 2, 1262, 472, 229, 326, 1668, 751, 1749, 528, 1786, 1060, 522, 1641, 1296, 1720, 808, 611, 1274, 189, 1167, 185, 855, 678, 742, 567, 647, 876, 628, 638, 322, 1392, 1659, 479, 594, 244, 308, 1464, 1096, 1238, 1762, 836, 644, 569, 1469, 592, 158, 682, 236, 1492, 217, 1618, 1767, 1429, 599, 1783, 1352, 1036, 204, 14, 725, 1196, 1356, 72, 1756, 1002, 1267, 832, 581, 402, 914, 565, 260, 1204, 467, 1308, 34, 417, 144, 69, 136, 687, 1777, 1093, 448, 871, 555, 965, 1293, 1380, 1189, 1181, 816, 1532, 163, 1337, 1072, 894, 1037, 1031, 47, 897, 1000, 1075, 1268, 1489, 904, 699, 1606, 1108, 1247, 28, 459, 1721, 1244, 394, 223, 1744, 1385, 1784, 1343, 918, 947, 65, 1648, 376, 1649, 95, 1235, 1752, 478, 539, 1003, 615, 1631, 677, 152, 1332, 164, 1508, 22, 1761, 1680, 1330, 681, 612, 1227, 48, 762, 1673, 671, 1125, 1588, 959, 1531, 104, 617, 1379, 598, 847, 525, 653, 1690, 1076, 1412, 413, 741, 748, 1467, 1100, 497, 309, 1422, 1753, 225, 754, 538, 547, 1681, 620, 942, 292, 1628, 1519, 1574, 941, 1406, 1210, 663, 848, 367, 888, 930, 312, 343, 264, 142, 1655, 1161, 639, 1773, 54, 643, 672, 800, 363, 319, 126, 410, 248, 720, 1501, 929, 691, 344, 1201, 377, 373, 1369, 1334, 980, 1608, 4, 879, 1719, 1115, 460, 768, 1772, 131, 689, 138, 87, 784, 969, 119, 186, 970, 1176, 756, 1433, 129, 1056, 1677, 176, 8, 1025, 199, 1270, 830, 1707, 135, 1313, 1265, 1596, 1348, 257, 1637, 1793, 662, 646, 414, 265, 1367, 1400, 524, 1546, 160, 80, 1012, 328, 1544, 438, 224, 220, 1699, 1443, 445, 1150, 1584, 29, 442, 686, 1517, 432, 570, 40, 979, 311, 1632, 494, 1589, 1086, 1480, 114, 1318, 101, 1454, 626, 1327, 1217, 178, 395, 59, 353, 736, 77, 989, 572, 477, 1393, 1246, 744, 1528, 1069, 936, 1282, 1538, 908, 1646, 593, 1534, 1298, 157, 1577, 952, 1146, 1522, 794, 1071, 1696, 461, 39, 1660, 1346, 128, 635, 1211, 1562, 405, 757, 1291, 127, 60, 1439, 604, 1157, 294, 239, 314, 1234, 368, 454, 1126, 1374, 629, 211, 1722, 1194, 84, 812, 446, 843, 1442, 495, 1403, 991, 430, 527, 1727, 925, 916, 1216, 237, 1117, 1503, 837, 1085, 602, 1595, 1349, 1700, 1704, 134, 245, 1309, 778, 993, 512, 619, 1408, 1134, 340, 542, 1297, 259, 1341, 1698, 422, 520, 1286, 1609, 1245, 113, 509, 404, 1421, 1547, 23, 1306, 860, 169, 1718, 958, 1067, 1081, 574, 366, 271, 614, 898, 792, 990, 273, 1192, 1007, 1634, 773, 585, 1062, 1675, 1579, 1636, 175, 1042, 412, 342, 1409, 1733, 154, 196, 1018, 767, 355, 507, 441, 1563, 1738, 683, 1466, 1082, 937, 316, 1625, 1205, 1378, 1552, 1449, 1708, 1697, 1116, 1463, 415, 1223, 1630, 603, 688, 1280, 951, 1119, 1206, 20, 556, 1290, 246, 1173, 652, 551, 162, 179, 1486, 589, 1760, 1361, 700, 608, 1447, 93, 852, 385, 36, 243, 723, 1456, 1430, 1629, 1365, 645, 1130, 263, 1153, 397, 1623, 1551, 1022, 1303, 336, 107, 331, 1160, 1791, 429, 425, 648, 875, 1782, 1364, 732, 526, 307, 1184, 667, 1336, 1276, 1027, 881, 829, 153, 1172, 1587, 940, 651, 45, 1310, 1326, 1669, 1041, 944, 1730, 346 ], [ 182, 11, 1225, 74, 1633, 289, 1446, 1414, 815, 1029, 544, 431, 877, 108, 1077, 1188, 480, 883, 1370, 1384, 1505, 1775, 1165, 106, 170, 518, 435, 1019, 541, 408, 789, 103, 1148, 1213, 269, 302, 785, 552, 939, 1070, 786, 327, 5, 1737, 1621, 810, 297, 1046, 262, 73, 998, 724, 1640, 1261, 1241, 1420, 596, 25, 1542, 1593, 727, 1263, 809, 1133, 801, 1472, 1516, 1127, 1073, 1581, 1755, 1473, 1582, 1525, 824, 99, 701, 1026, 1285, 1419, 1182, 587, 1600, 370, 690, 1207, 1765, 770, 1307, 1687, 49, 706, 26, 360, 964, 198, 586, 1228, 275, 702, 631, 317, 1391, 1242, 1766, 406, 1568, 1214, 1496, 1514, 1387, 241, 627, 613, 1688, 1354, 1259, 715, 1685, 981, 1728, 143, 935, 98, 1345, 660, 1488, 580, 1033, 803, 78, 577, 728, 451, 388, 769, 821, 354, 564, 313, 161, 845, 1445, 1742, 1254, 1212, 409, 41, 386, 1105, 733, 287, 12, 712, 1539, 1627, 1658, 1537, 219, 731, 1603, 679, 506, 439, 1703, 391, 873, 752, 231, 1013, 1540, 356, 1390, 1043, 1186, 666, 591, 1428, 1662, 515, 907, 886, 1695, 693, 1035, 462, 9, 58, 1724, 575, 874, 1185, 1145, 1338, 905, 558, 233, 623, 1305, 1509, 1426, 839, 1411, 315, 1294, 407, 1315, 501, 726, 1657, 797, 66, 1434, 1418, 1398, 968, 1592, 1413, 740, 79, 1180, 1320, 1368, 658, 1452, 213, 717, 609, 281, 761, 1171, 973, 1590, 972, 722, 339, 1137, 737, 249, 1209, 746, 466, 1159, 1347, 657, 1335, 868, 183, 1714, 817, 1054, 1319, 283, 920, 826, 1785, 1360, 902, 796, 1005, 519, 1789, 1674, 842, 15, 181, 228, 399, 1758, 35, 38, 468, 764, 1197, 955, 44, 75, 1078, 1175, 818, 278, 1665, 578, 1271, 16, 535, 1383, 1045, 833, 267, 880, 491, 1701, 1174, 440, 457, 124, 684, 1139, 303, 1676, 437, 1431, 759, 1613, 1576, 636, 1169, 1604, 1252, 1614, 323, 1491, 1039, 1769, 306, 890, 1058, 310, 277, 846, 730, 901, 1670, 549, 975, 1092, 531, 1020, 423, 3, 582, 704, 859, 1415, 194, 190, 1795, 987, 1569, 400, 1362, 1101, 279, 76, 374, 1682, 1123, 1512, 305, 895, 1381, 922, 1016, 1079, 1667, 893, 1230, 610, 296 ], [ 1471, 1166, 1023, 1732, 1424, 1476, 1215, 116, 766, 1375, 1739, 1647, 1506, 200, 1401, 145, 957, 1179, 1612, 82, 889, 30, 743, 1240, 284, 390, 1523, 765, 365, 1233, 286, 787, 710, 53, 333, 85, 324, 1376, 141, 290, 1723, 250, 867, 1487, 1051, 1359, 123, 1666, 1407, 1034, 1663, 1543, 1118, 1601, 121, 1763, 1504, 819, 490, 1106, 694, 379, 89, 579, 735, 711, 1404, 707, 427, 545, 443, 111, 1757, 349, 1080, 1458, 469, 967, 1479, 1705, 856, 486, 882, 482, 514, 471, 1300, 258, 1771, 1177, 665, 232, 1220, 1624, 1436, 1616, 1780, 554, 1281, 1432, 1639, 1468, 1515, 1311, 1266, 1124, 105, 546, 253, 1339, 1679, 266, 117, 777, 997, 19, 372, 1322, 424, 709, 896, 790, 521, 1736, 91, 226, 166, 1652, 146, 464, 588, 799, 676, 1550, 1734, 1114, 359, 1149, 148, 1353, 383, 387, 780, 1594, 781, 132, 384, 508, 863, 1395, 1768, 827, 963, 1448, 1683, 1097, 235, 1750, 350, 1087, 533, 347, 857, 325, 948, 820, 470, 498, 465, 960, 1580, 1014, 1583, 55, 1441, 543, 986, 782, 1389, 1129, 1440, 364, 1377, 988, 974, 1650, 1333, 692, 195, 1314, 120, 251, 1545, 510, 122, 193, 753, 458, 540, 1461, 252, 332, 320, 139, 499, 1255, 1066, 909, 1324, 1558, 216, 57, 1304, 1008, 1317, 1, 1155, 90, 27, 61, 1128, 1152, 115, 504, 911, 899, 420, 926, 1170, 1510, 1273, 1199, 1195, 1490, 1743, 1495, 811, 46, 1065, 903, 1122, 1321, 1260, 1615, 197, 675, 436, 1103, 1553, 1386, 1203, 335, 1098, 640, 763, 1455, 276, 155, 382, 517, 463, 1747, 24, 1573, 1178, 840, 456, 1301, 334, 1605, 392, 345, 1402, 1656, 887, 1053, 398, 1485, 1344, 771, 550, 295, 511, 995, 473, 282, 1394, 1295, 426, 1513, 849, 1068, 1083, 772, 1548, 1275, 96, 696, 1151, 396, 779, 1279, 1272, 807, 1619, 1183, 532, 523, 418, 1549, 632, 1477, 256, 361, 151, 749, 321, 774, 280, 1316, 493, 1533, 32, 205, 1520, 822, 112, 184, 1465, 1602, 884, 791, 1778, 33, 505, 698, 708, 1366, 755, 81, 37, 1570, 864, 1678, 1109, 1597, 685, 962, 1672, 862, 341, 1289, 680, 293, 1251, 949, 1030, 1417, 537, 1218 ] ], "test_targets": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 8, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 7, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 5, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 1, 5, 5, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 8, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 1, 4, 0, 1, 4, 1, 4, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 2, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 9, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ], "class_counts": [ 36, 37, 35, 37, 36, 36, 36, 36, 35, 36 ], "epochs": { "teacher": 58, "hard16": 76, "distill16": 77, "qat4": 8 }, "history": { "teacher": [ { "epoch": 1, "loss": 1.8739676475524902, "accuracy": 0.7111111283302307 }, { "epoch": 2, "loss": 1.2790734767913818, "accuracy": 0.8527777791023254 }, { "epoch": 3, "loss": 0.7964198589324951, "accuracy": 0.8694444298744202 }, { "epoch": 4, "loss": 0.5305414199829102, "accuracy": 0.8972222208976746 }, { "epoch": 5, "loss": 0.4134185314178467, "accuracy": 0.9138888716697693 }, { "epoch": 6, "loss": 0.33107948303222656, "accuracy": 0.9222221970558167 }, { "epoch": 7, "loss": 0.2846846580505371, "accuracy": 0.9222221970558167 }, { "epoch": 8, "loss": 0.25202080607414246, "accuracy": 0.9333333373069763 }, { "epoch": 9, "loss": 0.23190738260746002, "accuracy": 0.9333333373069763 }, { "epoch": 10, "loss": 0.20849458873271942, "accuracy": 0.9416666626930237 }, { "epoch": 11, "loss": 0.20237590372562408, "accuracy": 0.9444444179534912 }, { "epoch": 12, "loss": 0.19011518359184265, "accuracy": 0.9333333373069763 }, { "epoch": 13, "loss": 0.18203972280025482, "accuracy": 0.9416666626930237 }, { "epoch": 14, "loss": 0.1692340224981308, "accuracy": 0.9472222328186035 }, { "epoch": 15, "loss": 0.16444890201091766, "accuracy": 0.9472222328186035 }, { "epoch": 16, "loss": 0.1618989259004593, "accuracy": 0.9583333134651184 }, { "epoch": 17, "loss": 0.15203087031841278, "accuracy": 0.9583333134651184 }, { "epoch": 18, "loss": 0.16525372862815857, "accuracy": 0.9361110925674438 }, { "epoch": 19, "loss": 0.14768092334270477, "accuracy": 0.9527778029441833 }, { "epoch": 20, "loss": 0.14679008722305298, "accuracy": 0.9611111283302307 }, { "epoch": 21, "loss": 0.14101596176624298, "accuracy": 0.9583333134651184 }, { "epoch": 22, "loss": 0.14368084073066711, "accuracy": 0.9583333134651184 }, { "epoch": 23, "loss": 0.13758356869220734, "accuracy": 0.9555555582046509 }, { "epoch": 24, "loss": 0.13651883602142334, "accuracy": 0.9666666388511658 }, { "epoch": 25, "loss": 0.13663774728775024, "accuracy": 0.9611111283302307 }, { "epoch": 26, "loss": 0.13506804406642914, "accuracy": 0.9638888835906982 }, { "epoch": 27, "loss": 0.12883655726909637, "accuracy": 0.9638888835906982 }, { "epoch": 28, "loss": 0.12608875334262848, "accuracy": 0.9694444537162781 }, { "epoch": 29, "loss": 0.1266893446445465, "accuracy": 0.9638888835906982 }, { "epoch": 30, "loss": 0.13129538297653198, "accuracy": 0.9611111283302307 }, { "epoch": 31, "loss": 0.1272449940443039, "accuracy": 0.9722222089767456 }, { "epoch": 32, "loss": 0.12323173880577087, "accuracy": 0.9694444537162781 }, { "epoch": 33, "loss": 0.12452961504459381, "accuracy": 0.9666666388511658 }, { "epoch": 34, "loss": 0.12339086830615997, "accuracy": 0.9638888835906982 }, { "epoch": 35, "loss": 0.12351217120885849, "accuracy": 0.9694444537162781 }, { "epoch": 36, "loss": 0.11759059876203537, "accuracy": 0.9694444537162781 }, { "epoch": 37, "loss": 0.12487843632698059, "accuracy": 0.9694444537162781 }, { "epoch": 38, "loss": 0.11821666359901428, "accuracy": 0.9638888835906982 }, { "epoch": 39, "loss": 0.11614196747541428, "accuracy": 0.9694444537162781 }, { "epoch": 40, "loss": 0.12194177508354187, "accuracy": 0.9694444537162781 }, { "epoch": 41, "loss": 0.11527026444673538, "accuracy": 0.9666666388511658 }, { "epoch": 42, "loss": 0.11978959292173386, "accuracy": 0.9694444537162781 }, { "epoch": 43, "loss": 0.12428915500640869, "accuracy": 0.9666666388511658 }, { "epoch": 44, "loss": 0.11507850140333176, "accuracy": 0.9666666388511658 }, { "epoch": 45, "loss": 0.11431312561035156, "accuracy": 0.9694444537162781 }, { "epoch": 46, "loss": 0.1121913343667984, "accuracy": 0.9722222089767456 }, { "epoch": 47, "loss": 0.1177009865641594, "accuracy": 0.9666666388511658 }, { "epoch": 48, "loss": 0.12216860800981522, "accuracy": 0.9666666388511658 }, { "epoch": 49, "loss": 0.11270265281200409, "accuracy": 0.9666666388511658 }, { "epoch": 50, "loss": 0.11157990247011185, "accuracy": 0.9694444537162781 }, { "epoch": 51, "loss": 0.11431355029344559, "accuracy": 0.9666666388511658 }, { "epoch": 52, "loss": 0.11288170516490936, "accuracy": 0.9666666388511658 }, { "epoch": 53, "loss": 0.11174730956554413, "accuracy": 0.9694444537162781 }, { "epoch": 54, "loss": 0.11505576223134995, "accuracy": 0.9666666388511658 }, { "epoch": 55, "loss": 0.11189351975917816, "accuracy": 0.9694444537162781 }, { "epoch": 56, "loss": 0.11224675923585892, "accuracy": 0.9666666388511658 }, { "epoch": 57, "loss": 0.11316855996847153, "accuracy": 0.9694444537162781 }, { "epoch": 58, "loss": 0.11019589006900787, "accuracy": 0.9694444537162781 }, { "epoch": 59, "loss": 0.11650238186120987, "accuracy": 0.9638888835906982 }, { "epoch": 60, "loss": 0.11778856813907623, "accuracy": 0.9666666388511658 }, { "epoch": 61, "loss": 0.11341765522956848, "accuracy": 0.9638888835906982 }, { "epoch": 62, "loss": 0.1118597537279129, "accuracy": 0.9722222089767456 }, { "epoch": 63, "loss": 0.11751148104667664, "accuracy": 0.9666666388511658 }, { "epoch": 64, "loss": 0.11418251693248749, "accuracy": 0.9666666388511658 }, { "epoch": 65, "loss": 0.11278067529201508, "accuracy": 0.9666666388511658 }, { "epoch": 66, "loss": 0.11337926983833313, "accuracy": 0.9666666388511658 }, { "epoch": 67, "loss": 0.11503859609365463, "accuracy": 0.9638888835906982 }, { "epoch": 68, "loss": 0.11389311403036118, "accuracy": 0.9666666388511658 }, { "epoch": 69, "loss": 0.11284451186656952, "accuracy": 0.9666666388511658 }, { "epoch": 70, "loss": 0.12230516970157623, "accuracy": 0.9666666388511658 }, { "epoch": 71, "loss": 0.11941596120595932, "accuracy": 0.9638888835906982 }, { "epoch": 72, "loss": 0.11417490988969803, "accuracy": 0.9638888835906982 }, { "epoch": 73, "loss": 0.11285591870546341, "accuracy": 0.9638888835906982 }, { "epoch": 74, "loss": 0.11651032418012619, "accuracy": 0.9638888835906982 }, { "epoch": 75, "loss": 0.11897869408130646, "accuracy": 0.9666666388511658 }, { "epoch": 76, "loss": 0.11473532766103745, "accuracy": 0.9611111283302307 }, { "epoch": 77, "loss": 0.1155553087592125, "accuracy": 0.9666666388511658 }, { "epoch": 78, "loss": 0.11710136383771896, "accuracy": 0.9638888835906982 }, { "epoch": 79, "loss": 0.1150234118103981, "accuracy": 0.9666666388511658 }, { "epoch": 80, "loss": 0.11543728411197662, "accuracy": 0.9666666388511658 } ], "hard16": [ { "epoch": 1, "loss": 2.127906560897827, "accuracy": 0.36666667461395264 }, { "epoch": 2, "loss": 1.885056734085083, "accuracy": 0.5555555820465088 }, { "epoch": 3, "loss": 1.5945037603378296, "accuracy": 0.6777777671813965 }, { "epoch": 4, "loss": 1.2790566682815552, "accuracy": 0.7805555462837219 }, { "epoch": 5, "loss": 1.007583498954773, "accuracy": 0.8500000238418579 }, { "epoch": 6, "loss": 0.7926695942878723, "accuracy": 0.8638888597488403 }, { "epoch": 7, "loss": 0.6459652185440063, "accuracy": 0.8861111402511597 }, { "epoch": 8, "loss": 0.5455840229988098, "accuracy": 0.8999999761581421 }, { "epoch": 9, "loss": 0.47470080852508545, "accuracy": 0.9027777910232544 }, { "epoch": 10, "loss": 0.41772642731666565, "accuracy": 0.9138888716697693 }, { "epoch": 11, "loss": 0.37861335277557373, "accuracy": 0.9138888716697693 }, { "epoch": 12, "loss": 0.345044881105423, "accuracy": 0.9138888716697693 }, { "epoch": 13, "loss": 0.3174137473106384, "accuracy": 0.9194444417953491 }, { "epoch": 14, "loss": 0.2957287132740021, "accuracy": 0.9166666865348816 }, { "epoch": 15, "loss": 0.27548685669898987, "accuracy": 0.9222221970558167 }, { "epoch": 16, "loss": 0.26194366812705994, "accuracy": 0.9333333373069763 }, { "epoch": 17, "loss": 0.24770978093147278, "accuracy": 0.9333333373069763 }, { "epoch": 18, "loss": 0.23872144520282745, "accuracy": 0.9361110925674438 }, { "epoch": 19, "loss": 0.22837583720684052, "accuracy": 0.9361110925674438 }, { "epoch": 20, "loss": 0.22420147061347961, "accuracy": 0.9388889074325562 }, { "epoch": 21, "loss": 0.2092818170785904, "accuracy": 0.9416666626930237 }, { "epoch": 22, "loss": 0.20812220871448517, "accuracy": 0.9388889074325562 }, { "epoch": 23, "loss": 0.19781990349292755, "accuracy": 0.9388889074325562 }, { "epoch": 24, "loss": 0.19444720447063446, "accuracy": 0.9361110925674438 }, { "epoch": 25, "loss": 0.1925537884235382, "accuracy": 0.9333333373069763 }, { "epoch": 26, "loss": 0.18449059128761292, "accuracy": 0.9416666626930237 }, { "epoch": 27, "loss": 0.18124684691429138, "accuracy": 0.9416666626930237 }, { "epoch": 28, "loss": 0.17470058798789978, "accuracy": 0.949999988079071 }, { "epoch": 29, "loss": 0.1740119457244873, "accuracy": 0.9416666626930237 }, { "epoch": 30, "loss": 0.17057432234287262, "accuracy": 0.9416666626930237 }, { "epoch": 31, "loss": 0.1700948029756546, "accuracy": 0.949999988079071 }, { "epoch": 32, "loss": 0.16492363810539246, "accuracy": 0.9444444179534912 }, { "epoch": 33, "loss": 0.16300466656684875, "accuracy": 0.9472222328186035 }, { "epoch": 34, "loss": 0.15949176251888275, "accuracy": 0.949999988079071 }, { "epoch": 35, "loss": 0.158262699842453, "accuracy": 0.9444444179534912 }, { "epoch": 36, "loss": 0.15685845911502838, "accuracy": 0.9527778029441833 }, { "epoch": 37, "loss": 0.15697158873081207, "accuracy": 0.9472222328186035 }, { "epoch": 38, "loss": 0.15365418791770935, "accuracy": 0.9555555582046509 }, { "epoch": 39, "loss": 0.15195715427398682, "accuracy": 0.9527778029441833 }, { "epoch": 40, "loss": 0.15162107348442078, "accuracy": 0.9527778029441833 }, { "epoch": 41, "loss": 0.14671385288238525, "accuracy": 0.9527778029441833 }, { "epoch": 42, "loss": 0.151567280292511, "accuracy": 0.9472222328186035 }, { "epoch": 43, "loss": 0.14555181562900543, "accuracy": 0.9555555582046509 }, { "epoch": 44, "loss": 0.14843465387821198, "accuracy": 0.9555555582046509 }, { "epoch": 45, "loss": 0.14109301567077637, "accuracy": 0.9638888835906982 }, { "epoch": 46, "loss": 0.14528559148311615, "accuracy": 0.9527778029441833 }, { "epoch": 47, "loss": 0.1422794908285141, "accuracy": 0.9555555582046509 }, { "epoch": 48, "loss": 0.1439291536808014, "accuracy": 0.9611111283302307 }, { "epoch": 49, "loss": 0.13798566162586212, "accuracy": 0.9583333134651184 }, { "epoch": 50, "loss": 0.14202961325645447, "accuracy": 0.9555555582046509 }, { "epoch": 51, "loss": 0.13939079642295837, "accuracy": 0.9611111283302307 }, { "epoch": 52, "loss": 0.13845737278461456, "accuracy": 0.9555555582046509 }, { "epoch": 53, "loss": 0.13674426078796387, "accuracy": 0.9611111283302307 }, { "epoch": 54, "loss": 0.13746176660060883, "accuracy": 0.9583333134651184 }, { "epoch": 55, "loss": 0.13617178797721863, "accuracy": 0.9638888835906982 }, { "epoch": 56, "loss": 0.13582566380500793, "accuracy": 0.9611111283302307 }, { "epoch": 57, "loss": 0.13470013439655304, "accuracy": 0.9611111283302307 }, { "epoch": 58, "loss": 0.13549624383449554, "accuracy": 0.9638888835906982 }, { "epoch": 59, "loss": 0.13447187840938568, "accuracy": 0.9611111283302307 }, { "epoch": 60, "loss": 0.13758693635463715, "accuracy": 0.9583333134651184 }, { "epoch": 61, "loss": 0.13340690732002258, "accuracy": 0.9611111283302307 }, { "epoch": 62, "loss": 0.13416454195976257, "accuracy": 0.9638888835906982 }, { "epoch": 63, "loss": 0.13230857253074646, "accuracy": 0.9611111283302307 }, { "epoch": 64, "loss": 0.13384728133678436, "accuracy": 0.9611111283302307 }, { "epoch": 65, "loss": 0.1305433064699173, "accuracy": 0.9583333134651184 }, { "epoch": 66, "loss": 0.1310647577047348, "accuracy": 0.9611111283302307 }, { "epoch": 67, "loss": 0.13344816863536835, "accuracy": 0.9611111283302307 }, { "epoch": 68, "loss": 0.12961432337760925, "accuracy": 0.9638888835906982 }, { "epoch": 69, "loss": 0.132083922624588, "accuracy": 0.9583333134651184 }, { "epoch": 70, "loss": 0.13334611058235168, "accuracy": 0.9611111283302307 }, { "epoch": 71, "loss": 0.13393960893154144, "accuracy": 0.9583333134651184 }, { "epoch": 72, "loss": 0.12997126579284668, "accuracy": 0.9611111283302307 }, { "epoch": 73, "loss": 0.1305612176656723, "accuracy": 0.9611111283302307 }, { "epoch": 74, "loss": 0.1282341480255127, "accuracy": 0.9611111283302307 }, { "epoch": 75, "loss": 0.13271157443523407, "accuracy": 0.9611111283302307 }, { "epoch": 76, "loss": 0.1267658919095993, "accuracy": 0.9638888835906982 }, { "epoch": 77, "loss": 0.1302664577960968, "accuracy": 0.9638888835906982 }, { "epoch": 78, "loss": 0.1285991668701172, "accuracy": 0.9555555582046509 }, { "epoch": 79, "loss": 0.12882478535175323, "accuracy": 0.9611111283302307 }, { "epoch": 80, "loss": 0.12933789193630219, "accuracy": 0.9583333134651184 } ], "distill16": [ { "epoch": 1, "loss": 2.124706506729126, "accuracy": 0.3611111044883728 }, { "epoch": 2, "loss": 1.8770266771316528, "accuracy": 0.4888888895511627 }, { "epoch": 3, "loss": 1.5788791179656982, "accuracy": 0.5944444537162781 }, { "epoch": 4, "loss": 1.25468909740448, "accuracy": 0.6805555820465088 }, { "epoch": 5, "loss": 0.9643459916114807, "accuracy": 0.7611111402511597 }, { "epoch": 6, "loss": 0.7283616065979004, "accuracy": 0.8416666388511658 }, { "epoch": 7, "loss": 0.5745234489440918, "accuracy": 0.8666666746139526 }, { "epoch": 8, "loss": 0.4748650789260864, "accuracy": 0.8805555701255798 }, { "epoch": 9, "loss": 0.4092780351638794, "accuracy": 0.8888888955116272 }, { "epoch": 10, "loss": 0.36218392848968506, "accuracy": 0.8999999761581421 }, { "epoch": 11, "loss": 0.3289952278137207, "accuracy": 0.9055555462837219 }, { "epoch": 12, "loss": 0.302968829870224, "accuracy": 0.9138888716697693 }, { "epoch": 13, "loss": 0.2831057608127594, "accuracy": 0.9166666865348816 }, { "epoch": 14, "loss": 0.2667596638202667, "accuracy": 0.9194444417953491 }, { "epoch": 15, "loss": 0.2513592839241028, "accuracy": 0.9194444417953491 }, { "epoch": 16, "loss": 0.24145302176475525, "accuracy": 0.9194444417953491 }, { "epoch": 17, "loss": 0.22936880588531494, "accuracy": 0.9222221970558167 }, { "epoch": 18, "loss": 0.22502341866493225, "accuracy": 0.9166666865348816 }, { "epoch": 19, "loss": 0.21779488027095795, "accuracy": 0.925000011920929 }, { "epoch": 20, "loss": 0.21356266736984253, "accuracy": 0.9277777671813965 }, { "epoch": 21, "loss": 0.2037157267332077, "accuracy": 0.9305555820465088 }, { "epoch": 22, "loss": 0.201813742518425, "accuracy": 0.9333333373069763 }, { "epoch": 23, "loss": 0.19477975368499756, "accuracy": 0.9361110925674438 }, { "epoch": 24, "loss": 0.19200293719768524, "accuracy": 0.9361110925674438 }, { "epoch": 25, "loss": 0.19062800705432892, "accuracy": 0.9305555820465088 }, { "epoch": 26, "loss": 0.18476782739162445, "accuracy": 0.9388889074325562 }, { "epoch": 27, "loss": 0.18152481317520142, "accuracy": 0.9444444179534912 }, { "epoch": 28, "loss": 0.17568178474903107, "accuracy": 0.9361110925674438 }, { "epoch": 29, "loss": 0.17643436789512634, "accuracy": 0.9444444179534912 }, { "epoch": 30, "loss": 0.17238853871822357, "accuracy": 0.9444444179534912 }, { "epoch": 31, "loss": 0.17228345572948456, "accuracy": 0.9388889074325562 }, { "epoch": 32, "loss": 0.16752557456493378, "accuracy": 0.9416666626930237 }, { "epoch": 33, "loss": 0.16779860854148865, "accuracy": 0.9472222328186035 }, { "epoch": 34, "loss": 0.1629677712917328, "accuracy": 0.9472222328186035 }, { "epoch": 35, "loss": 0.16368097066879272, "accuracy": 0.9472222328186035 }, { "epoch": 36, "loss": 0.1607176959514618, "accuracy": 0.9444444179534912 }, { "epoch": 37, "loss": 0.16179387271404266, "accuracy": 0.949999988079071 }, { "epoch": 38, "loss": 0.1575034260749817, "accuracy": 0.9527778029441833 }, { "epoch": 39, "loss": 0.15783733129501343, "accuracy": 0.9527778029441833 }, { "epoch": 40, "loss": 0.15653936564922333, "accuracy": 0.949999988079071 }, { "epoch": 41, "loss": 0.1522180289030075, "accuracy": 0.9583333134651184 }, { "epoch": 42, "loss": 0.15698011219501495, "accuracy": 0.9444444179534912 }, { "epoch": 43, "loss": 0.15239740908145905, "accuracy": 0.9555555582046509 }, { "epoch": 44, "loss": 0.15321007370948792, "accuracy": 0.949999988079071 }, { "epoch": 45, "loss": 0.14974796772003174, "accuracy": 0.9583333134651184 }, { "epoch": 46, "loss": 0.1499839872121811, "accuracy": 0.9555555582046509 }, { "epoch": 47, "loss": 0.15110650658607483, "accuracy": 0.9555555582046509 }, { "epoch": 48, "loss": 0.14976166188716888, "accuracy": 0.9555555582046509 }, { "epoch": 49, "loss": 0.14750215411186218, "accuracy": 0.9583333134651184 }, { "epoch": 50, "loss": 0.14939309656620026, "accuracy": 0.9583333134651184 }, { "epoch": 51, "loss": 0.14820720255374908, "accuracy": 0.9555555582046509 }, { "epoch": 52, "loss": 0.14682379364967346, "accuracy": 0.9611111283302307 }, { "epoch": 53, "loss": 0.14747405052185059, "accuracy": 0.9638888835906982 }, { "epoch": 54, "loss": 0.14627613127231598, "accuracy": 0.9583333134651184 }, { "epoch": 55, "loss": 0.14527377486228943, "accuracy": 0.9611111283302307 }, { "epoch": 56, "loss": 0.1461504101753235, "accuracy": 0.9638888835906982 }, { "epoch": 57, "loss": 0.14353594183921814, "accuracy": 0.9611111283302307 }, { "epoch": 58, "loss": 0.1434544175863266, "accuracy": 0.9638888835906982 }, { "epoch": 59, "loss": 0.1446603387594223, "accuracy": 0.9638888835906982 }, { "epoch": 60, "loss": 0.14308564364910126, "accuracy": 0.9666666388511658 }, { "epoch": 61, "loss": 0.14408275485038757, "accuracy": 0.9666666388511658 }, { "epoch": 62, "loss": 0.14186227321624756, "accuracy": 0.9666666388511658 }, { "epoch": 63, "loss": 0.14267458021640778, "accuracy": 0.9666666388511658 }, { "epoch": 64, "loss": 0.14266346395015717, "accuracy": 0.9666666388511658 }, { "epoch": 65, "loss": 0.1409655064344406, "accuracy": 0.9666666388511658 }, { "epoch": 66, "loss": 0.1415521800518036, "accuracy": 0.9666666388511658 }, { "epoch": 67, "loss": 0.14115026593208313, "accuracy": 0.9666666388511658 }, { "epoch": 68, "loss": 0.14010559022426605, "accuracy": 0.9666666388511658 }, { "epoch": 69, "loss": 0.1387651115655899, "accuracy": 0.9638888835906982 }, { "epoch": 70, "loss": 0.1427721232175827, "accuracy": 0.9638888835906982 }, { "epoch": 71, "loss": 0.14114348590373993, "accuracy": 0.9638888835906982 }, { "epoch": 72, "loss": 0.13945133984088898, "accuracy": 0.9666666388511658 }, { "epoch": 73, "loss": 0.13850858807563782, "accuracy": 0.9666666388511658 }, { "epoch": 74, "loss": 0.13899411261081696, "accuracy": 0.9638888835906982 }, { "epoch": 75, "loss": 0.13814300298690796, "accuracy": 0.9638888835906982 }, { "epoch": 76, "loss": 0.13860869407653809, "accuracy": 0.9638888835906982 }, { "epoch": 77, "loss": 0.13671238720417023, "accuracy": 0.9666666388511658 }, { "epoch": 78, "loss": 0.13863924145698547, "accuracy": 0.9638888835906982 }, { "epoch": 79, "loss": 0.137712761759758, "accuracy": 0.9666666388511658 }, { "epoch": 80, "loss": 0.13703790307044983, "accuracy": 0.9666666388511658 } ], "qat4": [ { "epoch": 1, "loss": 0.11089041829109192, "accuracy": 0.9694444537162781 }, { "epoch": 2, "loss": 0.10967477411031723, "accuracy": 0.9694444537162781 }, { "epoch": 3, "loss": 0.11179042607545853, "accuracy": 0.9666666388511658 }, { "epoch": 4, "loss": 0.1108294203877449, "accuracy": 0.9666666388511658 }, { "epoch": 5, "loss": 0.10943599045276642, "accuracy": 0.9666666388511658 }, { "epoch": 6, "loss": 0.1105421781539917, "accuracy": 0.9666666388511658 }, { "epoch": 7, "loss": 0.11103229224681854, "accuracy": 0.9666666388511658 }, { "epoch": 8, "loss": 0.10886583477258682, "accuracy": 0.9666666388511658 }, { "epoch": 9, "loss": 0.11027988791465759, "accuracy": 0.9666666388511658 }, { "epoch": 10, "loss": 0.11068695783615112, "accuracy": 0.9666666388511658 }, { "epoch": 11, "loss": 0.11171538382768631, "accuracy": 0.9666666388511658 }, { "epoch": 12, "loss": 0.1119917631149292, "accuracy": 0.9666666388511658 }, { "epoch": 13, "loss": 0.1096629649400711, "accuracy": 0.9666666388511658 }, { "epoch": 14, "loss": 0.11319966614246368, "accuracy": 0.9666666388511658 }, { "epoch": 15, "loss": 0.10932598263025284, "accuracy": 0.9694444537162781 }, { "epoch": 16, "loss": 0.1108936220407486, "accuracy": 0.9694444537162781 }, { "epoch": 17, "loss": 0.11072861403226852, "accuracy": 0.9666666388511658 }, { "epoch": 18, "loss": 0.10970323532819748, "accuracy": 0.9666666388511658 }, { "epoch": 19, "loss": 0.11076656728982925, "accuracy": 0.9666666388511658 }, { "epoch": 20, "loss": 0.11198713630437851, "accuracy": 0.9666666388511658 } ] }, "rows": [ { "name": "teacher", "state_bytes": 19240, "weight_values": 4736, "nonzero_weights": 4736, "validation": { "loss": 0.11019589006900787, "accuracy": 0.9694444537162781, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 2, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 9, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 1, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 8, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 5, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 2, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 7, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 2, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 9, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.08890001475811005, "accuracy": 0.9750000238418579, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 9, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 9, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 1, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 2, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [], "fixes": [], "class_correct": [ 35, 36, 35, 37, 35, 34, 36, 35, 33, 35 ] }, { "name": "ptq8", "state_bytes": 5328, "weight_values": 4736, "nonzero_weights": 4697, "validation": { "loss": 0.11006207764148712, "accuracy": 0.9694444537162781, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 2, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 9, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 1, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 8, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 5, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 2, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 7, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 2, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 9, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.08881640434265137, "accuracy": 0.9750000238418579, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 9, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 9, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 1, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 2, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [], "fixes": [], "class_correct": [ 35, 36, 35, 37, 35, 34, 36, 35, 33, 35 ] }, { "name": "ptq4", "state_bytes": 2960, "weight_values": 4736, "nonzero_weights": 4116, "validation": { "loss": 0.11367719620466232, "accuracy": 0.9611111283302307, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 3, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 9, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 1, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 8, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 1, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 3, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 7, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 2, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 8, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.09745125472545624, "accuracy": 0.9722222089767456, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 7, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 9, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 4, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 1, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [ 1747, 632 ], "fixes": [ 498 ], "class_correct": [ 35, 35, 34, 37, 35, 34, 36, 36, 33, 35 ] }, { "name": "qat4", "state_bytes": 2960, "weight_values": 4736, "nonzero_weights": 4107, "validation": { "loss": 0.10886583477258682, "accuracy": 0.9666666388511658, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 2, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 9, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 1, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 8, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 5, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 2, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 7, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 2, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 8, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.09035040438175201, "accuracy": 0.9750000238418579, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 9, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 5, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 4, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 2, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [ 1747 ], "fixes": [ 120 ], "class_correct": [ 35, 35, 35, 37, 35, 35, 36, 35, 33, 35 ] }, { "name": "prune90", "state_bytes": 19240, "weight_values": 4736, "nonzero_weights": 474, "validation": { "loss": 1.3850820064544678, "accuracy": 0.5972222089767456, "predictions": [ 7, 1, 4, 4, 4, 4, 4, 8, 4, 0, 6, 4, 0, 4, 0, 9, 9, 1, 8, 4, 1, 7, 8, 1, 1, 4, 0, 4, 4, 2, 3, 7, 4, 1, 3, 5, 9, 0, 6, 4, 0, 4, 4, 1, 1, 4, 4, 6, 6, 4, 4, 0, 4, 6, 2, 4, 1, 4, 4, 0, 4, 6, 8, 6, 8, 3, 0, 4, 4, 6, 6, 4, 4, 4, 4, 1, 0, 8, 9, 4, 8, 4, 2, 8, 6, 2, 4, 4, 0, 0, 0, 3, 6, 6, 6, 4, 1, 6, 4, 1, 2, 7, 6, 8, 1, 0, 4, 2, 4, 1, 4, 8, 4, 4, 1, 6, 8, 9, 4, 0, 4, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 4, 8, 8, 3, 1, 2, 1, 4, 0, 2, 4, 4, 0, 4, 0, 0, 4, 9, 4, 6, 4, 4, 1, 8, 3, 1, 8, 4, 6, 4, 4, 4, 4, 6, 8, 7, 9, 4, 3, 4, 4, 4, 4, 3, 4, 8, 2, 4, 1, 1, 6, 8, 9, 6, 4, 4, 6, 8, 7, 0, 4, 4, 1, 1, 8, 4, 1, 8, 4, 3, 7, 4, 8, 2, 4, 7, 1, 6, 9, 3, 4, 6, 4, 1, 6, 0, 7, 4, 9, 8, 9, 3, 6, 1, 4, 8, 4, 3, 8, 1, 8, 3, 4, 4, 1, 7, 4, 4, 2, 3, 1, 0, 4, 8, 1, 4, 4, 4, 6, 4, 2, 4, 9, 4, 0, 6, 9, 4, 7, 6, 4, 2, 4, 3, 7, 4, 8, 6, 7, 4, 8, 7, 0, 0, 8, 1, 8, 9, 8, 8, 6, 9, 8, 4, 8, 1, 6, 9, 6, 7, 4, 4, 4, 8, 7, 1, 9, 2, 4, 8, 1, 8, 4, 2, 7, 6, 4, 6, 4, 0, 4, 2, 4, 4, 2, 1, 1, 2, 4, 4, 4, 4, 4, 4, 9, 9, 3, 6, 4, 3, 0, 4, 4, 9, 4, 6, 4, 2, 4, 3, 8, 6, 4, 8, 4, 0, 4, 4, 4, 4, 7, 0, 3, 4, 7, 6 ] }, "test": { "loss": 1.3969619274139404, "accuracy": 0.5972222089767456, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 8, 2, 6, 0, 6, 8, 1, 8, 8, 0, 2, 4, 6, 8, 4, 4, 3, 8, 4, 4, 9, 3, 8, 0, 1, 4, 6, 8, 4, 4, 3, 1, 6, 4, 4, 3, 0, 2, 4, 8, 6, 4, 4, 0, 9, 8, 6, 4, 4, 3, 7, 6, 0, 0, 8, 8, 3, 3, 6, 6, 7, 4, 9, 4, 4, 1, 1, 4, 4, 4, 6, 4, 6, 1, 4, 6, 8, 9, 1, 7, 2, 6, 4, 9, 6, 3, 3, 1, 9, 2, 6, 4, 7, 3, 4, 4, 4, 8, 4, 7, 0, 6, 7, 8, 0, 4, 1, 6, 1, 2, 4, 8, 3, 8, 4, 4, 4, 3, 4, 0, 4, 6, 0, 1, 3, 0, 4, 4, 4, 3, 4, 8, 6, 8, 1, 4, 2, 8, 8, 4, 9, 4, 4, 0, 8, 6, 5, 6, 4, 1, 8, 7, 3, 7, 3, 4, 9, 6, 4, 8, 9, 0, 6, 9, 4, 6, 0, 6, 7, 2, 4, 6, 4, 4, 4, 1, 4, 0, 4, 3, 8, 6, 7, 4, 9, 0, 4, 8, 3, 1, 0, 4, 4, 0, 8, 4, 1, 2, 3, 9, 4, 9, 7, 4, 2, 7, 4, 0, 4, 9, 4, 4, 4, 0, 9, 8, 9, 6, 1, 6, 4, 3, 6, 2, 1, 8, 2, 1, 1, 8, 4, 0, 4, 6, 6, 3, 1, 6, 9, 4, 8, 1, 1, 6, 0, 4, 4, 4, 8, 0, 8, 0, 1, 2, 4, 1, 4, 1, 4, 1, 4, 0, 8, 6, 8, 2, 4, 4, 4, 4, 1, 4, 9, 6, 9, 4, 6, 4, 4, 1, 8, 8, 7, 4, 4, 1, 0, 8, 9, 4, 8, 4, 0, 6, 8, 2, 4, 6, 6, 6, 9, 1, 4, 4, 3, 4, 4, 1, 3, 6, 9, 4, 9, 1, 4, 4, 2, 9, 8, 4, 8, 2, 8, 4, 8, 4, 4, 9, 6, 7, 1, 8, 4, 4, 4, 6, 1, 6, 0, 9, 4, 4, 7, 1, 8, 4, 9, 7, 6, 1, 8, 1, 9 ] }, "regressions": [ 116, 766, 1506, 145, 1612, 889, 30, 1523, 365, 53, 333, 85, 1723, 1359, 1666, 1407, 1034, 1118, 1763, 89, 1404, 443, 1080, 1458, 469, 1705, 1300, 1177, 554, 1468, 1266, 105, 253, 1679, 117, 997, 19, 1322, 896, 521, 1736, 226, 588, 1550, 1734, 781, 132, 384, 508, 1395, 827, 963, 1097, 1750, 857, 948, 820, 470, 1014, 1583, 782, 1389, 1129, 1440, 364, 1650, 1333, 692, 1461, 139, 1558, 216, 1008, 1, 90, 27, 61, 115, 504, 899, 926, 1743, 811, 903, 1615, 436, 1203, 1098, 763, 155, 1747, 24, 1605, 345, 1656, 398, 1344, 511, 995, 282, 1513, 849, 1068, 1548, 1275, 96, 696, 779, 807, 1619, 523, 418, 632, 256, 361, 1533, 32, 822, 112, 184, 1602, 884, 791, 33, 698, 708, 1366, 755, 81, 1570, 1597, 962, 1672, 1289, 680, 949, 1417, 1218 ], "fixes": [ 1495, 1301 ], "class_correct": [ 28, 29, 16, 21, 35, 1, 32, 12, 17, 24 ] }, { "name": "units16", "state_bytes": 4840, "weight_values": 1184, "nonzero_weights": 1184, "validation": { "loss": 1.501094102859497, "accuracy": 0.5916666388511658, "predictions": [ 2, 3, 4, 3, 5, 3, 3, 3, 3, 0, 3, 3, 0, 2, 0, 3, 2, 2, 3, 6, 3, 7, 3, 6, 2, 2, 0, 2, 5, 2, 3, 2, 4, 2, 3, 5, 3, 0, 6, 4, 0, 3, 3, 4, 2, 6, 4, 2, 6, 3, 4, 0, 4, 6, 2, 5, 6, 5, 3, 2, 3, 6, 5, 6, 5, 2, 0, 4, 2, 0, 6, 6, 5, 4, 0, 6, 0, 3, 2, 4, 5, 5, 2, 8, 2, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 6, 6, 5, 2, 2, 2, 2, 6, 2, 6, 0, 5, 2, 2, 0, 4, 2, 4, 4, 6, 6, 5, 5, 8, 0, 2, 3, 0, 3, 6, 4, 2, 4, 4, 2, 0, 2, 6, 6, 2, 2, 3, 3, 0, 2, 3, 3, 0, 2, 4, 0, 3, 4, 0, 0, 4, 3, 2, 6, 4, 2, 3, 3, 3, 5, 2, 5, 5, 2, 0, 5, 4, 6, 3, 2, 2, 4, 3, 4, 3, 0, 2, 3, 2, 3, 2, 4, 3, 2, 6, 3, 3, 6, 2, 3, 3, 2, 2, 2, 6, 6, 3, 3, 2, 2, 3, 3, 4, 3, 2, 3, 3, 2, 2, 2, 2, 6, 2, 3, 4, 6, 0, 0, 2, 0, 3, 3, 2, 3, 3, 3, 5, 3, 5, 2, 4, 5, 2, 3, 2, 3, 4, 3, 3, 2, 4, 6, 2, 3, 6, 0, 3, 3, 6, 4, 5, 5, 2, 5, 2, 7, 3, 0, 0, 6, 3, 8, 2, 6, 5, 2, 4, 3, 3, 5, 5, 6, 2, 5, 3, 2, 2, 0, 2, 6, 2, 5, 3, 2, 6, 3, 3, 6, 2, 6, 6, 2, 6, 2, 2, 5, 4, 3, 2, 6, 3, 2, 6, 2, 6, 5, 5, 2, 2, 6, 5, 6, 3, 0, 5, 2, 3, 3, 2, 6, 2, 2, 3, 3, 5, 3, 6, 5, 3, 2, 3, 6, 6, 3, 0, 4, 3, 3, 6, 6, 4, 2, 5, 3, 2, 2, 5, 2, 4, 0, 3, 2, 2, 2, 2, 0, 5, 3, 2, 8 ] }, "test": { "loss": 1.4361746311187744, "accuracy": 0.605555534362793, "predictions": [ 3, 3, 4, 6, 3, 2, 6, 2, 5, 6, 0, 6, 3, 6, 3, 5, 0, 2, 5, 6, 2, 0, 4, 3, 8, 4, 2, 5, 5, 2, 0, 2, 4, 2, 2, 4, 4, 3, 6, 6, 6, 4, 3, 0, 2, 0, 3, 0, 5, 5, 0, 3, 3, 6, 4, 8, 3, 2, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 3, 2, 4, 2, 6, 2, 2, 3, 6, 4, 8, 6, 4, 6, 3, 3, 6, 3, 2, 6, 0, 5, 6, 3, 3, 3, 3, 2, 6, 4, 2, 3, 3, 4, 4, 5, 4, 3, 0, 3, 2, 2, 0, 5, 2, 3, 3, 2, 5, 3, 3, 5, 4, 5, 3, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 4, 8, 6, 8, 3, 6, 2, 5, 2, 5, 3, 4, 2, 0, 2, 2, 5, 6, 3, 4, 3, 2, 3, 2, 3, 3, 5, 2, 2, 2, 7, 0, 6, 5, 2, 3, 0, 6, 2, 2, 6, 5, 5, 3, 4, 2, 4, 0, 5, 5, 5, 6, 2, 3, 3, 0, 4, 3, 3, 2, 0, 4, 5, 0, 3, 4, 3, 2, 3, 3, 4, 3, 3, 4, 2, 2, 6, 0, 4, 3, 3, 3, 2, 0, 3, 2, 2, 6, 3, 6, 6, 3, 6, 2, 2, 5, 2, 3, 3, 5, 5, 0, 3, 6, 6, 3, 6, 6, 5, 2, 2, 0, 2, 5, 0, 5, 4, 5, 3, 0, 5, 0, 3, 2, 4, 4, 6, 6, 4, 3, 6, 0, 2, 6, 3, 2, 5, 4, 4, 2, 3, 2, 3, 6, 3, 3, 2, 4, 6, 2, 2, 3, 3, 3, 3, 6, 0, 3, 7, 2, 2, 4, 0, 3, 2, 2, 3, 3, 6, 6, 2, 3, 4, 2, 3, 0, 5, 3, 3, 6, 5, 4, 3, 3, 2, 5, 2, 2, 5, 2, 2, 2, 3, 2, 5, 4, 5, 3, 2, 3, 0, 5, 7, 3, 2, 6, 6, 6, 2, 5, 3, 5, 2, 6, 2, 6, 3, 2, 2, 3, 2, 6, 2 ] }, "regressions": [ 1471, 1166, 1424, 1476, 200, 1401, 1612, 1523, 765, 1233, 787, 53, 85, 141, 1723, 123, 1666, 1543, 819, 545, 1757, 349, 1080, 1458, 856, 482, 514, 471, 665, 1436, 1616, 554, 1432, 1468, 105, 253, 1339, 777, 997, 19, 424, 1736, 387, 780, 384, 508, 1395, 963, 1097, 235, 350, 533, 857, 325, 948, 820, 1580, 1583, 543, 1440, 364, 1377, 1314, 251, 122, 753, 332, 139, 1066, 1324, 216, 1304, 1008, 1, 1155, 90, 27, 61, 1152, 504, 899, 926, 1199, 1195, 1743, 903, 1615, 675, 1103, 1386, 1455, 517, 1747, 1178, 456, 1605, 1485, 771, 295, 511, 995, 1394, 1295, 426, 849, 1068, 1083, 96, 1279, 807, 1619, 523, 418, 361, 151, 774, 1316, 493, 1533, 1520, 112, 884, 505, 698, 1570, 1678, 685, 862, 341, 293, 1251, 949, 1030, 537, 1218 ], "fixes": [ 498, 46 ], "class_correct": [ 34, 0, 35, 36, 34, 33, 36, 4, 6, 0 ] }, { "name": "hard16", "state_bytes": 4840, "weight_values": 1184, "nonzero_weights": 1184, "validation": { "loss": 0.1267658919095993, "accuracy": 0.9638888835906982, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 2, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 5, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 9, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 2, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 5, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 2, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 4, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 8, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 8, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.11306042224168777, "accuracy": 0.9666666388511658, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 6, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 9, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 9, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 4, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 1, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [ 1311, 1747, 632 ], "fixes": [], "class_correct": [ 35, 35, 34, 37, 34, 34, 36, 35, 33, 35 ] }, { "name": "distill16", "state_bytes": 4840, "weight_values": 1184, "nonzero_weights": 1184, "validation": { "loss": 0.13671238720417023, "accuracy": 0.9666666388511658, "predictions": [ 7, 1, 4, 5, 9, 5, 9, 8, 9, 0, 8, 3, 0, 7, 0, 9, 9, 1, 3, 4, 1, 7, 8, 6, 1, 1, 0, 7, 5, 2, 3, 3, 4, 1, 3, 5, 9, 0, 6, 4, 0, 5, 9, 1, 1, 6, 4, 7, 6, 9, 4, 0, 1, 6, 2, 5, 1, 5, 8, 2, 7, 6, 5, 6, 5, 2, 0, 4, 7, 8, 6, 6, 5, 4, 0, 1, 0, 8, 9, 4, 5, 5, 2, 8, 7, 2, 3, 4, 0, 0, 0, 3, 6, 6, 3, 4, 1, 5, 9, 1, 2, 7, 6, 1, 1, 0, 5, 2, 7, 9, 4, 2, 4, 4, 1, 6, 5, 9, 8, 0, 7, 3, 0, 3, 6, 4, 9, 4, 4, 7, 0, 7, 6, 6, 2, 2, 3, 3, 0, 2, 9, 9, 0, 2, 4, 0, 3, 4, 0, 0, 4, 9, 2, 6, 4, 7, 8, 8, 3, 1, 7, 5, 5, 8, 0, 5, 4, 6, 3, 7, 9, 4, 3, 4, 9, 0, 2, 3, 5, 8, 2, 4, 8, 1, 6, 8, 9, 6, 2, 3, 3, 8, 7, 2, 1, 1, 9, 1, 8, 7, 1, 3, 4, 3, 7, 1, 8, 2, 1, 7, 1, 6, 9, 3, 4, 6, 0, 0, 7, 0, 3, 5, 7, 2, 9, 3, 5, 1, 5, 2, 4, 5, 1, 1, 8, 3, 4, 3, 8, 7, 4, 1, 2, 3, 1, 0, 9, 8, 1, 4, 5, 5, 7, 5, 2, 7, 9, 0, 0, 6, 3, 8, 7, 6, 5, 2, 4, 3, 3, 5, 8, 6, 7, 5, 8, 7, 2, 0, 8, 1, 2, 9, 3, 8, 6, 9, 8, 6, 2, 1, 6, 9, 6, 7, 2, 5, 4, 8, 7, 1, 9, 2, 6, 2, 1, 5, 5, 2, 7, 6, 5, 6, 8, 0, 5, 2, 8, 9, 2, 1, 1, 2, 9, 3, 5, 9, 6, 5, 9, 9, 3, 6, 6, 3, 0, 4, 3, 9, 1, 6, 4, 2, 5, 3, 8, 7, 5, 8, 4, 0, 9, 7, 7, 2, 7, 0, 5, 9, 7, 8 ] }, "test": { "loss": 0.1088726595044136, "accuracy": 0.9694444537162781, "predictions": [ 1, 9, 4, 6, 9, 7, 6, 2, 5, 6, 0, 6, 3, 1, 8, 5, 0, 2, 9, 6, 2, 0, 4, 3, 8, 4, 7, 9, 5, 8, 0, 1, 4, 8, 2, 1, 4, 3, 1, 6, 1, 4, 3, 0, 2, 0, 8, 8, 5, 5, 0, 9, 3, 6, 4, 8, 3, 7, 6, 0, 0, 8, 3, 3, 3, 6, 5, 7, 4, 9, 2, 4, 1, 1, 8, 7, 3, 6, 4, 8, 1, 4, 6, 8, 9, 1, 3, 2, 6, 0, 9, 6, 3, 3, 1, 9, 2, 8, 4, 7, 3, 8, 4, 4, 5, 4, 9, 0, 8, 7, 2, 0, 5, 1, 8, 9, 2, 5, 8, 3, 5, 4, 5, 9, 3, 3, 0, 4, 6, 0, 0, 3, 0, 5, 6, 4, 3, 1, 8, 6, 8, 1, 4, 2, 5, 2, 9, 8, 4, 7, 0, 2, 7, 5, 6, 1, 1, 3, 7, 3, 7, 3, 7, 9, 7, 7, 2, 9, 0, 6, 9, 2, 8, 0, 6, 7, 2, 6, 5, 5, 5, 7, 1, 4, 0, 5, 5, 5, 6, 7, 9, 9, 0, 4, 8, 3, 1, 0, 4, 5, 0, 8, 4, 9, 2, 3, 9, 4, 9, 3, 7, 2, 7, 1, 0, 1, 9, 1, 7, 7, 0, 9, 2, 7, 6, 8, 6, 1, 3, 6, 2, 1, 8, 2, 8, 9, 5, 4, 0, 8, 6, 6, 3, 0, 6, 9, 2, 8, 1, 1, 5, 0, 5, 4, 5, 8, 0, 5, 0, 1, 2, 4, 4, 4, 1, 4, 1, 0, 0, 3, 6, 3, 2, 5, 4, 4, 2, 1, 2, 9, 6, 9, 9, 7, 4, 6, 1, 8, 8, 3, 9, 9, 1, 0, 3, 7, 8, 2, 4, 0, 3, 8, 2, 9, 8, 6, 6, 7, 5, 4, 1, 3, 0, 9, 1, 3, 6, 9, 4, 9, 1, 7, 5, 2, 9, 5, 7, 2, 2, 3, 7, 5, 4, 5, 9, 7, 3, 0, 5, 7, 5, 7, 6, 1, 6, 2, 9, 3, 5, 7, 1, 2, 6, 9, 7, 7, 1, 2, 1, 7 ] }, "regressions": [ 1747, 632 ], "fixes": [], "class_correct": [ 35, 35, 34, 37, 35, 34, 36, 35, 33, 35 ] } ] }