【Ubuntu 24.04.3】Quotient Network: experiments_on_svhn — q44

MSI Cyborg-15-A12VE

Acknowledgments and References

python ./src/train.py --model q44

Training: Epoch[001/182] Iteration[050/526] Loss: 2.2909 Acc:16.80%
Training: Epoch[001/182] Iteration[100/526] Loss: 2.2251 Acc:20.00%
Training: Epoch[001/182] Iteration[150/526] Loss: 2.0812 Acc:24.97%
Training: Epoch[001/182] Iteration[200/526] Loss: 1.8906 Acc:32.48%
Training: Epoch[001/182] Iteration[250/526] Loss: 1.7025 Acc:39.54%
Training: Epoch[001/182] Iteration[300/526] Loss: 1.5445 Acc:45.60%
Training: Epoch[001/182] Iteration[350/526] Loss: 1.4144 Acc:50.42%
Training: Epoch[001/182] Iteration[400/526] Loss: 1.3033 Acc:54.49%
Training: Epoch[001/182] Iteration[450/526] Loss: 1.2165 Acc:57.71%
Training: Epoch[001/182] Iteration[500/526] Loss: 1.1430 Acc:60.46%
Epoch[001/182] Train Acc: 61.66% Valid Acc:83.60% Train loss:1.1110 Valid loss:0.5171 LR:0.1
Training: Epoch[002/182] Iteration[050/526] Loss: 0.4731 Acc:85.05%
Training: Epoch[002/182] Iteration[100/526] Loss: 0.4497 Acc:86.05%
Training: Epoch[002/182] Iteration[150/526] Loss: 0.4377 Acc:86.52%
Training: Epoch[002/182] Iteration[200/526] Loss: 0.4283 Acc:86.93%
Training: Epoch[002/182] Iteration[250/526] Loss: 0.4249 Acc:86.96%
Training: Epoch[002/182] Iteration[300/526] Loss: 0.4175 Acc:87.10%
Training: Epoch[002/182] Iteration[350/526] Loss: 0.4082 Acc:87.34%
Training: Epoch[002/182] Iteration[400/526] Loss: 0.4013 Acc:87.54%
Training: Epoch[002/182] Iteration[450/526] Loss: 0.3967 Acc:87.67%
Training: Epoch[002/182] Iteration[500/526] Loss: 0.3936 Acc:87.82%
Epoch[002/182] Train Acc: 87.94% Valid Acc:89.03% Train loss:0.3913 Valid loss:0.3579 LR:0.1
Training: Epoch[003/182] Iteration[050/526] Loss: 0.3518 Acc:89.34%
Training: Epoch[003/182] Iteration[100/526] Loss: 0.3463 Acc:89.70%
Training: Epoch[003/182] Iteration[150/526] Loss: 0.3344 Acc:89.91%
Training: Epoch[003/182] Iteration[200/526] Loss: 0.3323 Acc:90.02%
Training: Epoch[003/182] Iteration[250/526] Loss: 0.3334 Acc:89.93%
Training: Epoch[003/182] Iteration[300/526] Loss: 0.3274 Acc:90.11%
Training: Epoch[003/182] Iteration[350/526] Loss: 0.3210 Acc:90.29%
Training: Epoch[003/182] Iteration[400/526] Loss: 0.3191 Acc:90.33%
Training: Epoch[003/182] Iteration[450/526] Loss: 0.3185 Acc:90.32%
Training: Epoch[003/182] Iteration[500/526] Loss: 0.3171 Acc:90.41%
Epoch[003/182] Train Acc: 90.42% Valid Acc:90.87% Train loss:0.3166 Valid loss:0.3098 LR:0.1
Training: Epoch[004/182] Iteration[050/526] Loss: 0.3013 Acc:91.20%
Training: Epoch[004/182] Iteration[100/526] Loss: 0.2963 Acc:91.41%
Training: Epoch[004/182] Iteration[150/526] Loss: 0.2891 Acc:91.31%
Training: Epoch[004/182] Iteration[200/526] Loss: 0.2859 Acc:91.45%
Training: Epoch[004/182] Iteration[250/526] Loss: 0.2832 Acc:91.46%
Training: Epoch[004/182] Iteration[300/526] Loss: 0.2816 Acc:91.57%
Training: Epoch[004/182] Iteration[350/526] Loss: 0.2804 Acc:91.63%
Training: Epoch[004/182] Iteration[400/526] Loss: 0.2801 Acc:91.61%
Training: Epoch[004/182] Iteration[450/526] Loss: 0.2796 Acc:91.67%
Training: Epoch[004/182] Iteration[500/526] Loss: 0.2776 Acc:91.73%
Epoch[004/182] Train Acc: 91.72% Valid Acc:92.18% Train loss:0.2771 Valid loss:0.2696 LR:0.1
Training: Epoch[005/182] Iteration[050/526] Loss: 0.2552 Acc:92.41%
Training: Epoch[005/182] Iteration[100/526] Loss: 0.2583 Acc:92.41%
Training: Epoch[005/182] Iteration[150/526] Loss: 0.2620 Acc:92.28%
Training: Epoch[005/182] Iteration[200/526] Loss: 0.2565 Acc:92.44%
Training: Epoch[005/182] Iteration[250/526] Loss: 0.2565 Acc:92.45%
Training: Epoch[005/182] Iteration[300/526] Loss: 0.2545 Acc:92.54%
Training: Epoch[005/182] Iteration[350/526] Loss: 0.2525 Acc:92.61%
Training: Epoch[005/182] Iteration[400/526] Loss: 0.2539 Acc:92.54%
Training: Epoch[005/182] Iteration[450/526] Loss: 0.2551 Acc:92.49%
Training: Epoch[005/182] Iteration[500/526] Loss: 0.2543 Acc:92.54%
Epoch[005/182] Train Acc: 92.52% Valid Acc:91.58% Train loss:0.2539 Valid loss:0.2796 LR:0.1
Training: Epoch[006/182] Iteration[050/526] Loss: 0.2257 Acc:92.98%
Training: Epoch[006/182] Iteration[100/526] Loss: 0.2404 Acc:92.75%
Training: Epoch[006/182] Iteration[150/526] Loss: 0.2458 Acc:92.61%
Training: Epoch[006/182] Iteration[200/526] Loss: 0.2443 Acc:92.67%
Training: Epoch[006/182] Iteration[250/526] Loss: 0.2413 Acc:92.80%
Training: Epoch[006/182] Iteration[300/526] Loss: 0.2410 Acc:92.82%
Training: Epoch[006/182] Iteration[350/526] Loss: 0.2431 Acc:92.76%
Training: Epoch[006/182] Iteration[400/526] Loss: 0.2432 Acc:92.78%
Training: Epoch[006/182] Iteration[450/526] Loss: 0.2421 Acc:92.84%
Training: Epoch[006/182] Iteration[500/526] Loss: 0.2406 Acc:92.89%
Epoch[006/182] Train Acc: 92.92% Valid Acc:92.68% Train loss:0.2397 Valid loss:0.2455 LR:0.1
Training: Epoch[007/182] Iteration[050/526] Loss: 0.2123 Acc:93.88%
Training: Epoch[007/182] Iteration[100/526] Loss: 0.2172 Acc:93.86%
Training: Epoch[007/182] Iteration[150/526] Loss: 0.2282 Acc:93.42%
Training: Epoch[007/182] Iteration[200/526] Loss: 0.2291 Acc:93.37%
Training: Epoch[007/182] Iteration[250/526] Loss: 0.2303 Acc:93.32%
Training: Epoch[007/182] Iteration[300/526] Loss: 0.2308 Acc:93.28%
Training: Epoch[007/182] Iteration[350/526] Loss: 0.2299 Acc:93.29%
Training: Epoch[007/182] Iteration[400/526] Loss: 0.2288 Acc:93.36%
Training: Epoch[007/182] Iteration[450/526] Loss: 0.2286 Acc:93.36%
Training: Epoch[007/182] Iteration[500/526] Loss: 0.2287 Acc:93.36%
Epoch[007/182] Train Acc: 93.35% Valid Acc:92.53% Train loss:0.2282 Valid loss:0.2530 LR:0.1
Training: Epoch[008/182] Iteration[050/526] Loss: 0.2194 Acc:93.66%
Training: Epoch[008/182] Iteration[100/526] Loss: 0.2090 Acc:93.92%
Training: Epoch[008/182] Iteration[150/526] Loss: 0.2174 Acc:93.60%
Training: Epoch[008/182] Iteration[200/526] Loss: 0.2174 Acc:93.64%
Training: Epoch[008/182] Iteration[250/526] Loss: 0.2187 Acc:93.65%
Training: Epoch[008/182] Iteration[300/526] Loss: 0.2194 Acc:93.61%
Training: Epoch[008/182] Iteration[350/526] Loss: 0.2203 Acc:93.59%
Training: Epoch[008/182] Iteration[400/526] Loss: 0.2166 Acc:93.71%
Training: Epoch[008/182] Iteration[450/526] Loss: 0.2165 Acc:93.70%
Training: Epoch[008/182] Iteration[500/526] Loss: 0.2176 Acc:93.68%
Epoch[008/182] Train Acc: 93.62% Valid Acc:92.05% Train loss:0.2192 Valid loss:0.2661 LR:0.1
Training: Epoch[009/182] Iteration[050/526] Loss: 0.2030 Acc:94.33%
Training: Epoch[009/182] Iteration[100/526] Loss: 0.2057 Acc:94.20%
Training: Epoch[009/182] Iteration[150/526] Loss: 0.2031 Acc:94.15%
Training: Epoch[009/182] Iteration[200/526] Loss: 0.2029 Acc:94.16%
Training: Epoch[009/182] Iteration[250/526] Loss: 0.2066 Acc:94.02%
Training: Epoch[009/182] Iteration[300/526] Loss: 0.2079 Acc:94.02%
Training: Epoch[009/182] Iteration[350/526] Loss: 0.2095 Acc:94.00%
Training: Epoch[009/182] Iteration[400/526] Loss: 0.2080 Acc:94.02%
Training: Epoch[009/182] Iteration[450/526] Loss: 0.2073 Acc:94.00%
Training: Epoch[009/182] Iteration[500/526] Loss: 0.2091 Acc:93.95%
Epoch[009/182] Train Acc: 93.97% Valid Acc:92.83% Train loss:0.2090 Valid loss:0.2463 LR:0.1
Training: Epoch[010/182] Iteration[050/526] Loss: 0.1964 Acc:94.61%
Training: Epoch[010/182] Iteration[100/526] Loss: 0.1995 Acc:94.52%
Training: Epoch[010/182] Iteration[150/526] Loss: 0.2042 Acc:94.25%
Training: Epoch[010/182] Iteration[200/526] Loss: 0.2000 Acc:94.27%
Training: Epoch[010/182] Iteration[250/526] Loss: 0.2069 Acc:94.06%
Training: Epoch[010/182] Iteration[300/526] Loss: 0.2082 Acc:94.05%
Training: Epoch[010/182] Iteration[350/526] Loss: 0.2091 Acc:93.98%
Training: Epoch[010/182] Iteration[400/526] Loss: 0.2059 Acc:94.04%
Training: Epoch[010/182] Iteration[450/526] Loss: 0.2074 Acc:93.99%
Training: Epoch[010/182] Iteration[500/526] Loss: 0.2064 Acc:94.01%
Epoch[010/182] Train Acc: 93.99% Valid Acc:92.65% Train loss:0.2071 Valid loss:0.2513 LR:0.1
Training: Epoch[011/182] Iteration[050/526] Loss: 0.2009 Acc:94.16%
Training: Epoch[011/182] Iteration[100/526] Loss: 0.2021 Acc:94.22%
Training: Epoch[011/182] Iteration[150/526] Loss: 0.2001 Acc:94.21%
Training: Epoch[011/182] Iteration[200/526] Loss: 0.2018 Acc:94.21%
Training: Epoch[011/182] Iteration[250/526] Loss: 0.2001 Acc:94.18%
Training: Epoch[011/182] Iteration[300/526] Loss: 0.1994 Acc:94.21%
Training: Epoch[011/182] Iteration[350/526] Loss: 0.2013 Acc:94.10%
Training: Epoch[011/182] Iteration[400/526] Loss: 0.2018 Acc:94.10%
Training: Epoch[011/182] Iteration[450/526] Loss: 0.2017 Acc:94.12%
Training: Epoch[011/182] Iteration[500/526] Loss: 0.2011 Acc:94.14%
Epoch[011/182] Train Acc: 94.14% Valid Acc:93.48% Train loss:0.2015 Valid loss:0.2317 LR:0.1
Training: Epoch[012/182] Iteration[050/526] Loss: 0.1902 Acc:94.70%
Training: Epoch[012/182] Iteration[100/526] Loss: 0.1869 Acc:94.42%
Training: Epoch[012/182] Iteration[150/526] Loss: 0.1875 Acc:94.52%
Training: Epoch[012/182] Iteration[200/526] Loss: 0.1918 Acc:94.45%
Training: Epoch[012/182] Iteration[250/526] Loss: 0.1916 Acc:94.44%
Training: Epoch[012/182] Iteration[300/526] Loss: 0.1935 Acc:94.34%
Training: Epoch[012/182] Iteration[350/526] Loss: 0.1959 Acc:94.28%
Training: Epoch[012/182] Iteration[400/526] Loss: 0.1957 Acc:94.29%
Training: Epoch[012/182] Iteration[450/526] Loss: 0.1934 Acc:94.35%
Training: Epoch[012/182] Iteration[500/526] Loss: 0.1958 Acc:94.25%
Epoch[012/182] Train Acc: 94.23% Valid Acc:93.12% Train loss:0.1960 Valid loss:0.2438 LR:0.1
Training: Epoch[013/182] Iteration[050/526] Loss: 0.1711 Acc:94.98%
Training: Epoch[013/182] Iteration[100/526] Loss: 0.1748 Acc:94.83%
Training: Epoch[013/182] Iteration[150/526] Loss: 0.1807 Acc:94.68%
Training: Epoch[013/182] Iteration[200/526] Loss: 0.1852 Acc:94.57%
Training: Epoch[013/182] Iteration[250/526] Loss: 0.1866 Acc:94.56%
Training: Epoch[013/182] Iteration[300/526] Loss: 0.1878 Acc:94.48%
Training: Epoch[013/182] Iteration[350/526] Loss: 0.1872 Acc:94.57%
Training: Epoch[013/182] Iteration[400/526] Loss: 0.1866 Acc:94.59%
Training: Epoch[013/182] Iteration[450/526] Loss: 0.1879 Acc:94.57%
Training: Epoch[013/182] Iteration[500/526] Loss: 0.1903 Acc:94.49%
Epoch[013/182] Train Acc: 94.51% Valid Acc:93.25% Train loss:0.1898 Valid loss:0.2322 LR:0.1
Training: Epoch[014/182] Iteration[050/526] Loss: 0.1981 Acc:94.19%
Training: Epoch[014/182] Iteration[100/526] Loss: 0.1995 Acc:94.27%
Training: Epoch[014/182] Iteration[150/526] Loss: 0.1952 Acc:94.39%
Training: Epoch[014/182] Iteration[200/526] Loss: 0.1914 Acc:94.50%
Training: Epoch[014/182] Iteration[250/526] Loss: 0.1872 Acc:94.59%
Training: Epoch[014/182] Iteration[300/526] Loss: 0.1845 Acc:94.69%
Training: Epoch[014/182] Iteration[350/526] Loss: 0.1854 Acc:94.68%
Training: Epoch[014/182] Iteration[400/526] Loss: 0.1854 Acc:94.65%
Training: Epoch[014/182] Iteration[450/526] Loss: 0.1866 Acc:94.63%
Training: Epoch[014/182] Iteration[500/526] Loss: 0.1854 Acc:94.67%
Epoch[014/182] Train Acc: 94.62% Valid Acc:93.20% Train loss:0.1871 Valid loss:0.2286 LR:0.1
Training: Epoch[015/182] Iteration[050/526] Loss: 0.1646 Acc:95.19%
Training: Epoch[015/182] Iteration[100/526] Loss: 0.1784 Acc:94.84%
Training: Epoch[015/182] Iteration[150/526] Loss: 0.1832 Acc:94.62%
Training: Epoch[015/182] Iteration[200/526] Loss: 0.1833 Acc:94.61%
Training: Epoch[015/182] Iteration[250/526] Loss: 0.1864 Acc:94.53%
Training: Epoch[015/182] Iteration[300/526] Loss: 0.1847 Acc:94.59%
Training: Epoch[015/182] Iteration[350/526] Loss: 0.1839 Acc:94.64%
Training: Epoch[015/182] Iteration[400/526] Loss: 0.1847 Acc:94.60%
Training: Epoch[015/182] Iteration[450/526] Loss: 0.1867 Acc:94.54%
Training: Epoch[015/182] Iteration[500/526] Loss: 0.1867 Acc:94.53%
Epoch[015/182] Train Acc: 94.54% Valid Acc:93.50% Train loss:0.1862 Valid loss:0.2360 LR:0.1
Training: Epoch[016/182] Iteration[050/526] Loss: 0.1772 Acc:94.53%
Training: Epoch[016/182] Iteration[100/526] Loss: 0.1773 Acc:94.61%
Training: Epoch[016/182] Iteration[150/526] Loss: 0.1825 Acc:94.67%
Training: Epoch[016/182] Iteration[200/526] Loss: 0.1833 Acc:94.66%
Training: Epoch[016/182] Iteration[250/526] Loss: 0.1820 Acc:94.67%
Training: Epoch[016/182] Iteration[300/526] Loss: 0.1808 Acc:94.70%
Training: Epoch[016/182] Iteration[350/526] Loss: 0.1822 Acc:94.68%
Training: Epoch[016/182] Iteration[400/526] Loss: 0.1802 Acc:94.73%
Training: Epoch[016/182] Iteration[450/526] Loss: 0.1827 Acc:94.66%
Training: Epoch[016/182] Iteration[500/526] Loss: 0.1832 Acc:94.67%
Epoch[016/182] Train Acc: 94.67% Valid Acc:93.03% Train loss:0.1832 Valid loss:0.2341 LR:0.1
Training: Epoch[017/182] Iteration[050/526] Loss: 0.1741 Acc:95.28%
Training: Epoch[017/182] Iteration[100/526] Loss: 0.1688 Acc:95.10%
Training: Epoch[017/182] Iteration[150/526] Loss: 0.1752 Acc:95.05%
Training: Epoch[017/182] Iteration[200/526] Loss: 0.1737 Acc:95.05%
Training: Epoch[017/182] Iteration[250/526] Loss: 0.1751 Acc:94.92%
Training: Epoch[017/182] Iteration[300/526] Loss: 0.1760 Acc:94.87%
Training: Epoch[017/182] Iteration[350/526] Loss: 0.1781 Acc:94.78%
Training: Epoch[017/182] Iteration[400/526] Loss: 0.1799 Acc:94.75%
Training: Epoch[017/182] Iteration[450/526] Loss: 0.1799 Acc:94.72%
Training: Epoch[017/182] Iteration[500/526] Loss: 0.1820 Acc:94.68%
Epoch[017/182] Train Acc: 94.67% Valid Acc:93.48% Train loss:0.1816 Valid loss:0.2276 LR:0.1
Training: Epoch[018/182] Iteration[050/526] Loss: 0.1690 Acc:95.20%
Training: Epoch[018/182] Iteration[100/526] Loss: 0.1688 Acc:95.24%
Training: Epoch[018/182] Iteration[150/526] Loss: 0.1710 Acc:95.17%
Training: Epoch[018/182] Iteration[200/526] Loss: 0.1765 Acc:94.95%
Training: Epoch[018/182] Iteration[250/526] Loss: 0.1728 Acc:94.99%
Training: Epoch[018/182] Iteration[300/526] Loss: 0.1729 Acc:95.03%
Training: Epoch[018/182] Iteration[350/526] Loss: 0.1735 Acc:95.03%
Training: Epoch[018/182] Iteration[400/526] Loss: 0.1750 Acc:94.93%
Training: Epoch[018/182] Iteration[450/526] Loss: 0.1768 Acc:94.86%
Training: Epoch[018/182] Iteration[500/526] Loss: 0.1776 Acc:94.84%
Epoch[018/182] Train Acc: 94.84% Valid Acc:93.18% Train loss:0.1778 Valid loss:0.2365 LR:0.1
Training: Epoch[019/182] Iteration[050/526] Loss: 0.1513 Acc:95.91%
Training: Epoch[019/182] Iteration[100/526] Loss: 0.1629 Acc:95.41%
Training: Epoch[019/182] Iteration[150/526] Loss: 0.1647 Acc:95.40%
Training: Epoch[019/182] Iteration[200/526] Loss: 0.1684 Acc:95.23%
Training: Epoch[019/182] Iteration[250/526] Loss: 0.1683 Acc:95.22%
Training: Epoch[019/182] Iteration[300/526] Loss: 0.1665 Acc:95.26%
Training: Epoch[019/182] Iteration[350/526] Loss: 0.1677 Acc:95.19%
Training: Epoch[019/182] Iteration[400/526] Loss: 0.1693 Acc:95.14%
Training: Epoch[019/182] Iteration[450/526] Loss: 0.1709 Acc:95.07%
Training: Epoch[019/182] Iteration[500/526] Loss: 0.1739 Acc:94.97%
Epoch[019/182] Train Acc: 94.93% Valid Acc:93.48% Train loss:0.1746 Valid loss:0.2325 LR:0.1
Training: Epoch[020/182] Iteration[050/526] Loss: 0.1458 Acc:95.58%
Training: Epoch[020/182] Iteration[100/526] Loss: 0.1612 Acc:95.32%
Training: Epoch[020/182] Iteration[150/526] Loss: 0.1632 Acc:95.19%
Training: Epoch[020/182] Iteration[200/526] Loss: 0.1643 Acc:95.13%
Training: Epoch[020/182] Iteration[250/526] Loss: 0.1638 Acc:95.22%
Training: Epoch[020/182] Iteration[300/526] Loss: 0.1685 Acc:95.10%
Training: Epoch[020/182] Iteration[350/526] Loss: 0.1690 Acc:95.09%
Training: Epoch[020/182] Iteration[400/526] Loss: 0.1701 Acc:95.08%
Training: Epoch[020/182] Iteration[450/526] Loss: 0.1717 Acc:95.04%
Training: Epoch[020/182] Iteration[500/526] Loss: 0.1722 Acc:95.04%
Epoch[020/182] Train Acc: 95.05% Valid Acc:92.67% Train loss:0.1724 Valid loss:0.2503 LR:0.1
Training: Epoch[021/182] Iteration[050/526] Loss: 0.1549 Acc:95.38%
Training: Epoch[021/182] Iteration[100/526] Loss: 0.1568 Acc:95.41%
Training: Epoch[021/182] Iteration[150/526] Loss: 0.1708 Acc:95.13%
Training: Epoch[021/182] Iteration[200/526] Loss: 0.1750 Acc:95.03%
Training: Epoch[021/182] Iteration[250/526] Loss: 0.1749 Acc:95.04%
Training: Epoch[021/182] Iteration[300/526] Loss: 0.1720 Acc:95.13%
Training: Epoch[021/182] Iteration[350/526] Loss: 0.1723 Acc:95.09%
Training: Epoch[021/182] Iteration[400/526] Loss: 0.1731 Acc:95.03%
Training: Epoch[021/182] Iteration[450/526] Loss: 0.1718 Acc:95.05%
Training: Epoch[021/182] Iteration[500/526] Loss: 0.1706 Acc:95.07%
Epoch[021/182] Train Acc: 95.09% Valid Acc:93.38% Train loss:0.1703 Valid loss:0.2341 LR:0.1
Training: Epoch[022/182] Iteration[050/526] Loss: 0.1523 Acc:95.67%
Training: Epoch[022/182] Iteration[100/526] Loss: 0.1630 Acc:95.40%
Training: Epoch[022/182] Iteration[150/526] Loss: 0.1595 Acc:95.35%
Training: Epoch[022/182] Iteration[200/526] Loss: 0.1621 Acc:95.29%
Training: Epoch[022/182] Iteration[250/526] Loss: 0.1644 Acc:95.33%
Training: Epoch[022/182] Iteration[300/526] Loss: 0.1655 Acc:95.25%
Training: Epoch[022/182] Iteration[350/526] Loss: 0.1669 Acc:95.20%
Training: Epoch[022/182] Iteration[400/526] Loss: 0.1695 Acc:95.10%
Training: Epoch[022/182] Iteration[450/526] Loss: 0.1721 Acc:94.99%
Training: Epoch[022/182] Iteration[500/526] Loss: 0.1716 Acc:95.01%
Epoch[022/182] Train Acc: 94.98% Valid Acc:93.13% Train loss:0.1728 Valid loss:0.2510 LR:0.1
Training: Epoch[023/182] Iteration[050/526] Loss: 0.1580 Acc:95.72%
Training: Epoch[023/182] Iteration[100/526] Loss: 0.1623 Acc:95.34%
Training: Epoch[023/182] Iteration[150/526] Loss: 0.1619 Acc:95.40%
Training: Epoch[023/182] Iteration[200/526] Loss: 0.1607 Acc:95.38%
Training: Epoch[023/182] Iteration[250/526] Loss: 0.1676 Acc:95.21%
Training: Epoch[023/182] Iteration[300/526] Loss: 0.1641 Acc:95.27%
Training: Epoch[023/182] Iteration[350/526] Loss: 0.1648 Acc:95.19%
Training: Epoch[023/182] Iteration[400/526] Loss: 0.1670 Acc:95.17%
Training: Epoch[023/182] Iteration[450/526] Loss: 0.1665 Acc:95.16%
Training: Epoch[023/182] Iteration[500/526] Loss: 0.1671 Acc:95.15%
Epoch[023/182] Train Acc: 95.16% Valid Acc:93.30% Train loss:0.1671 Valid loss:0.2379 LR:0.1
Training: Epoch[024/182] Iteration[050/526] Loss: 0.1565 Acc:95.66%
Training: Epoch[024/182] Iteration[100/526] Loss: 0.1568 Acc:95.40%
Training: Epoch[024/182] Iteration[150/526] Loss: 0.1590 Acc:95.31%
Training: Epoch[024/182] Iteration[200/526] Loss: 0.1596 Acc:95.34%
Training: Epoch[024/182] Iteration[250/526] Loss: 0.1596 Acc:95.37%
Training: Epoch[024/182] Iteration[300/526] Loss: 0.1620 Acc:95.31%
Training: Epoch[024/182] Iteration[350/526] Loss: 0.1657 Acc:95.20%
Training: Epoch[024/182] Iteration[400/526] Loss: 0.1672 Acc:95.20%
Training: Epoch[024/182] Iteration[450/526] Loss: 0.1653 Acc:95.26%
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Epoch[024/182] Train Acc: 95.25% Valid Acc:92.52% Train loss:0.1654 Valid loss:0.2608 LR:0.1
Training: Epoch[025/182] Iteration[050/526] Loss: 0.1700 Acc:95.08%
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Epoch[025/182] Train Acc: 95.37% Valid Acc:92.02% Train loss:0.1638 Valid loss:0.2813 LR:0.1
Training: Epoch[026/182] Iteration[050/526] Loss: 0.1497 Acc:95.81%
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Epoch[026/182] Train Acc: 95.24% Valid Acc:93.38% Train loss:0.1633 Valid loss:0.2358 LR:0.1
Training: Epoch[027/182] Iteration[050/526] Loss: 0.1365 Acc:95.92%
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Epoch[027/182] Train Acc: 95.27% Valid Acc:93.70% Train loss:0.1625 Valid loss:0.2369 LR:0.1
Training: Epoch[028/182] Iteration[050/526] Loss: 0.1474 Acc:95.70%
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Epoch[028/182] Train Acc: 95.41% Valid Acc:93.03% Train loss:0.1601 Valid loss:0.2541 LR:0.1
Training: Epoch[029/182] Iteration[050/526] Loss: 0.1428 Acc:95.83%
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Epoch[029/182] Train Acc: 95.26% Valid Acc:92.95% Train loss:0.1614 Valid loss:0.2581 LR:0.1
Training: Epoch[030/182] Iteration[050/526] Loss: 0.1445 Acc:95.75%
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Epoch[030/182] Train Acc: 95.45% Valid Acc:93.80% Train loss:0.1590 Valid loss:0.2285 LR:0.1
Training: Epoch[031/182] Iteration[050/526] Loss: 0.1642 Acc:95.02%
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Epoch[031/182] Train Acc: 95.41% Valid Acc:92.37% Train loss:0.1588 Valid loss:0.2617 LR:0.1
Training: Epoch[032/182] Iteration[050/526] Loss: 0.1449 Acc:95.86%
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Epoch[032/182] Train Acc: 95.42% Valid Acc:93.70% Train loss:0.1590 Valid loss:0.2270 LR:0.1
Training: Epoch[033/182] Iteration[050/526] Loss: 0.1602 Acc:95.75%
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Epoch[033/182] Train Acc: 95.50% Valid Acc:93.75% Train loss:0.1550 Valid loss:0.2288 LR:0.1
Training: Epoch[034/182] Iteration[050/526] Loss: 0.1598 Acc:95.73%
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Epoch[034/182] Train Acc: 95.61% Valid Acc:93.53% Train loss:0.1524 Valid loss:0.2368 LR:0.1
Training: Epoch[035/182] Iteration[050/526] Loss: 0.1401 Acc:96.22%
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Epoch[035/182] Train Acc: 95.55% Valid Acc:93.90% Train loss:0.1530 Valid loss:0.2262 LR:0.1
Training: Epoch[036/182] Iteration[050/526] Loss: 0.1487 Acc:95.42%
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Epoch[036/182] Train Acc: 95.58% Valid Acc:92.65% Train loss:0.1528 Valid loss:0.2597 LR:0.1
Training: Epoch[037/182] Iteration[050/526] Loss: 0.1341 Acc:95.81%
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Epoch[037/182] Train Acc: 95.64% Valid Acc:93.33% Train loss:0.1509 Valid loss:0.2388 LR:0.1
Training: Epoch[038/182] Iteration[050/526] Loss: 0.1403 Acc:96.05%
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Epoch[038/182] Train Acc: 95.70% Valid Acc:94.27% Train loss:0.1489 Valid loss:0.2162 LR:0.1
Training: Epoch[039/182] Iteration[050/526] Loss: 0.1405 Acc:95.72%
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Epoch[039/182] Train Acc: 95.64% Valid Acc:94.02% Train loss:0.1504 Valid loss:0.2299 LR:0.1
Training: Epoch[040/182] Iteration[050/526] Loss: 0.1402 Acc:96.00%
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Epoch[040/182] Train Acc: 95.75% Valid Acc:93.18% Train loss:0.1476 Valid loss:0.2431 LR:0.1
Training: Epoch[041/182] Iteration[050/526] Loss: 0.1267 Acc:96.02%
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Epoch[041/182] Train Acc: 95.75% Valid Acc:93.57% Train loss:0.1462 Valid loss:0.2335 LR:0.1
Training: Epoch[042/182] Iteration[050/526] Loss: 0.1448 Acc:95.73%
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Epoch[042/182] Train Acc: 95.74% Valid Acc:94.08% Train loss:0.1470 Valid loss:0.2255 LR:0.1
Training: Epoch[043/182] Iteration[050/526] Loss: 0.1470 Acc:95.98%
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Epoch[043/182] Train Acc: 95.76% Valid Acc:92.85% Train loss:0.1471 Valid loss:0.2751 LR:0.1
Training: Epoch[044/182] Iteration[050/526] Loss: 0.1418 Acc:96.20%
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Epoch[044/182] Train Acc: 95.80% Valid Acc:94.13% Train loss:0.1467 Valid loss:0.2144 LR:0.1
Training: Epoch[045/182] Iteration[050/526] Loss: 0.1328 Acc:96.02%
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Epoch[045/182] Train Acc: 95.85% Valid Acc:93.78% Train loss:0.1448 Valid loss:0.2386 LR:0.1
Training: Epoch[046/182] Iteration[050/526] Loss: 0.1390 Acc:96.17%
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Epoch[046/182] Train Acc: 95.95% Valid Acc:93.78% Train loss:0.1437 Valid loss:0.2273 LR:0.1
Training: Epoch[047/182] Iteration[050/526] Loss: 0.1304 Acc:96.06%
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Epoch[047/182] Train Acc: 95.82% Valid Acc:93.67% Train loss:0.1421 Valid loss:0.2276 LR:0.1
Training: Epoch[048/182] Iteration[050/526] Loss: 0.1353 Acc:95.91%
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Epoch[048/182] Train Acc: 95.79% Valid Acc:93.60% Train loss:0.1440 Valid loss:0.2434 LR:0.1
Training: Epoch[049/182] Iteration[050/526] Loss: 0.1143 Acc:96.66%
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Epoch[049/182] Train Acc: 95.89% Valid Acc:93.42% Train loss:0.1424 Valid loss:0.2389 LR:0.1
Training: Epoch[050/182] Iteration[050/526] Loss: 0.1351 Acc:96.14%
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Epoch[050/182] Train Acc: 96.01% Valid Acc:93.57% Train loss:0.1402 Valid loss:0.2456 LR:0.1
Training: Epoch[051/182] Iteration[050/526] Loss: 0.1243 Acc:96.30%
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Epoch[051/182] Train Acc: 95.96% Valid Acc:94.30% Train loss:0.1411 Valid loss:0.2046 LR:0.1
Training: Epoch[052/182] Iteration[050/526] Loss: 0.1462 Acc:95.53%
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Epoch[052/182] Train Acc: 95.87% Valid Acc:93.45% Train loss:0.1406 Valid loss:0.2394 LR:0.1
Training: Epoch[053/182] Iteration[050/526] Loss: 0.1290 Acc:96.33%
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Epoch[053/182] Train Acc: 95.90% Valid Acc:93.50% Train loss:0.1415 Valid loss:0.2472 LR:0.1
Training: Epoch[054/182] Iteration[050/526] Loss: 0.1318 Acc:96.25%
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Epoch[054/182] Train Acc: 95.97% Valid Acc:93.15% Train loss:0.1392 Valid loss:0.2535 LR:0.1
Training: Epoch[055/182] Iteration[050/526] Loss: 0.1364 Acc:95.97%
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Epoch[055/182] Train Acc: 95.96% Valid Acc:94.00% Train loss:0.1390 Valid loss:0.2388 LR:0.1
Training: Epoch[056/182] Iteration[050/526] Loss: 0.1348 Acc:96.12%
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Epoch[056/182] Train Acc: 95.94% Valid Acc:94.02% Train loss:0.1388 Valid loss:0.2264 LR:0.1
Training: Epoch[057/182] Iteration[050/526] Loss: 0.1230 Acc:96.23%
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Epoch[057/182] Train Acc: 96.03% Valid Acc:93.98% Train loss:0.1364 Valid loss:0.2241 LR:0.1
Training: Epoch[058/182] Iteration[050/526] Loss: 0.1241 Acc:96.27%
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Epoch[058/182] Train Acc: 96.09% Valid Acc:93.97% Train loss:0.1351 Valid loss:0.2202 LR:0.1
Training: Epoch[059/182] Iteration[050/526] Loss: 0.1348 Acc:96.11%
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Epoch[059/182] Train Acc: 95.98% Valid Acc:92.87% Train loss:0.1363 Valid loss:0.2491 LR:0.1
Training: Epoch[060/182] Iteration[050/526] Loss: 0.1320 Acc:96.03%
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Epoch[060/182] Train Acc: 96.03% Valid Acc:94.15% Train loss:0.1361 Valid loss:0.2299 LR:0.1
Training: Epoch[061/182] Iteration[050/526] Loss: 0.1349 Acc:96.27%
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Epoch[061/182] Train Acc: 95.90% Valid Acc:94.28% Train loss:0.1391 Valid loss:0.2125 LR:0.1
Training: Epoch[062/182] Iteration[050/526] Loss: 0.1286 Acc:96.27%
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Epoch[062/182] Train Acc: 96.03% Valid Acc:92.88% Train loss:0.1374 Valid loss:0.2474 LR:0.1
Training: Epoch[063/182] Iteration[050/526] Loss: 0.1303 Acc:96.47%
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Epoch[063/182] Train Acc: 96.10% Valid Acc:93.35% Train loss:0.1339 Valid loss:0.2435 LR:0.1
Training: Epoch[064/182] Iteration[050/526] Loss: 0.1231 Acc:96.33%
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Epoch[064/182] Train Acc: 96.08% Valid Acc:92.72% Train loss:0.1341 Valid loss:0.2760 LR:0.1
Training: Epoch[065/182] Iteration[050/526] Loss: 0.1345 Acc:96.20%
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Epoch[065/182] Train Acc: 96.07% Valid Acc:93.22% Train loss:0.1334 Valid loss:0.2554 LR:0.1
Training: Epoch[066/182] Iteration[050/526] Loss: 0.1269 Acc:96.55%
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Epoch[066/182] Train Acc: 96.12% Valid Acc:93.50% Train loss:0.1332 Valid loss:0.2474 LR:0.1
Training: Epoch[067/182] Iteration[050/526] Loss: 0.1255 Acc:96.36%
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Epoch[067/182] Train Acc: 96.14% Valid Acc:93.58% Train loss:0.1313 Valid loss:0.2272 LR:0.1
Training: Epoch[068/182] Iteration[050/526] Loss: 0.1339 Acc:96.25%
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Epoch[068/182] Train Acc: 96.11% Valid Acc:93.35% Train loss:0.1327 Valid loss:0.2383 LR:0.1
Training: Epoch[069/182] Iteration[050/526] Loss: 0.1242 Acc:96.47%
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Epoch[069/182] Train Acc: 96.15% Valid Acc:93.32% Train loss:0.1311 Valid loss:0.2598 LR:0.1
Training: Epoch[070/182] Iteration[050/526] Loss: 0.1309 Acc:96.20%
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Epoch[070/182] Train Acc: 96.10% Valid Acc:93.83% Train loss:0.1319 Valid loss:0.2227 LR:0.1
Training: Epoch[071/182] Iteration[050/526] Loss: 0.1123 Acc:96.84%
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Epoch[071/182] Train Acc: 96.27% Valid Acc:94.22% Train loss:0.1301 Valid loss:0.2136 LR:0.1
Training: Epoch[072/182] Iteration[050/526] Loss: 0.1181 Acc:96.77%
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Epoch[072/182] Train Acc: 96.20% Valid Acc:94.35% Train loss:0.1307 Valid loss:0.2149 LR:0.1
Training: Epoch[073/182] Iteration[050/526] Loss: 0.1142 Acc:96.83%
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Epoch[073/182] Train Acc: 96.30% Valid Acc:94.18% Train loss:0.1297 Valid loss:0.2277 LR:0.1
Training: Epoch[074/182] Iteration[050/526] Loss: 0.1158 Acc:96.59%
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Epoch[074/182] Train Acc: 96.24% Valid Acc:93.45% Train loss:0.1296 Valid loss:0.2357 LR:0.1
Training: Epoch[075/182] Iteration[050/526] Loss: 0.1276 Acc:96.25%
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Epoch[075/182] Train Acc: 96.41% Valid Acc:94.28% Train loss:0.1254 Valid loss:0.2272 LR:0.1
Training: Epoch[076/182] Iteration[050/526] Loss: 0.1175 Acc:96.62%
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Epoch[076/182] Train Acc: 96.07% Valid Acc:93.83% Train loss:0.1328 Valid loss:0.2375 LR:0.1
Training: Epoch[077/182] Iteration[050/526] Loss: 0.1226 Acc:96.28%
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Epoch[077/182] Train Acc: 96.27% Valid Acc:93.65% Train loss:0.1284 Valid loss:0.2434 LR:0.1
Training: Epoch[078/182] Iteration[050/526] Loss: 0.1139 Acc:96.84%
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Epoch[078/182] Train Acc: 96.40% Valid Acc:93.78% Train loss:0.1254 Valid loss:0.2346 LR:0.1
Training: Epoch[079/182] Iteration[050/526] Loss: 0.1128 Acc:96.67%
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Epoch[079/182] Train Acc: 96.25% Valid Acc:93.47% Train loss:0.1288 Valid loss:0.2220 LR:0.1
Training: Epoch[080/182] Iteration[050/526] Loss: 0.1213 Acc:96.41%
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Epoch[080/182] Train Acc: 96.22% Valid Acc:93.25% Train loss:0.1314 Valid loss:0.2639 LR:0.1
Training: Epoch[081/182] Iteration[050/526] Loss: 0.1207 Acc:96.38%
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Epoch[081/182] Train Acc: 96.18% Valid Acc:94.20% Train loss:0.1282 Valid loss:0.2245 LR:0.1
Training: Epoch[082/182] Iteration[050/526] Loss: 0.1117 Acc:96.55%
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Epoch[082/182] Train Acc: 96.28% Valid Acc:93.37% Train loss:0.1275 Valid loss:0.2486 LR:0.1
Training: Epoch[083/182] Iteration[050/526] Loss: 0.1244 Acc:96.42%
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Epoch[083/182] Train Acc: 96.28% Valid Acc:94.05% Train loss:0.1276 Valid loss:0.2145 LR:0.1
Training: Epoch[084/182] Iteration[050/526] Loss: 0.1221 Acc:96.28%
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Epoch[084/182] Train Acc: 96.31% Valid Acc:93.32% Train loss:0.1261 Valid loss:0.2334 LR:0.1
Training: Epoch[085/182] Iteration[050/526] Loss: 0.1168 Acc:96.72%
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Epoch[085/182] Train Acc: 96.31% Valid Acc:93.87% Train loss:0.1271 Valid loss:0.2341 LR:0.1
Training: Epoch[086/182] Iteration[050/526] Loss: 0.1169 Acc:96.16%
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Epoch[086/182] Train Acc: 96.17% Valid Acc:93.47% Train loss:0.1278 Valid loss:0.2359 LR:0.1
Training: Epoch[087/182] Iteration[050/526] Loss: 0.1261 Acc:96.25%
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Epoch[087/182] Train Acc: 96.22% Valid Acc:93.77% Train loss:0.1270 Valid loss:0.2290 LR:0.1
Training: Epoch[088/182] Iteration[050/526] Loss: 0.1044 Acc:96.92%
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Epoch[088/182] Train Acc: 96.34% Valid Acc:93.70% Train loss:0.1245 Valid loss:0.2361 LR:0.1
Training: Epoch[089/182] Iteration[050/526] Loss: 0.1111 Acc:96.78%
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Epoch[089/182] Train Acc: 96.28% Valid Acc:94.05% Train loss:0.1276 Valid loss:0.2218 LR:0.1
Training: Epoch[090/182] Iteration[050/526] Loss: 0.1081 Acc:97.05%
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Epoch[090/182] Train Acc: 96.32% Valid Acc:93.45% Train loss:0.1248 Valid loss:0.2438 LR:0.1
Training: Epoch[091/182] Iteration[050/526] Loss: 0.1144 Acc:96.80%
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Epoch[091/182] Train Acc: 96.31% Valid Acc:94.00% Train loss:0.1259 Valid loss:0.2193 LR:0.1
Training: Epoch[092/182] Iteration[050/526] Loss: 0.1222 Acc:96.16%
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Epoch[092/182] Train Acc: 96.49% Valid Acc:92.77% Train loss:0.1211 Valid loss:0.2776 LR:0.1
Training: Epoch[093/182] Iteration[050/526] Loss: 0.1137 Acc:96.72%
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Epoch[093/182] Train Acc: 97.81% Valid Acc:95.53% Train loss:0.0799 Valid loss:0.1790 LR:0.010000000000000002
Training: Epoch[094/182] Iteration[050/526] Loss: 0.0573 Acc:98.27%
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Epoch[094/182] Train Acc: 98.34% Valid Acc:95.62% Train loss:0.0620 Valid loss:0.1847 LR:0.010000000000000002
Training: Epoch[095/182] Iteration[050/526] Loss: 0.0623 Acc:98.38%
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Epoch[095/182] Train Acc: 98.54% Valid Acc:95.60% Train loss:0.0565 Valid loss:0.1873 LR:0.010000000000000002
Training: Epoch[096/182] Iteration[050/526] Loss: 0.0538 Acc:98.58%
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Epoch[096/182] Train Acc: 98.64% Valid Acc:95.65% Train loss:0.0507 Valid loss:0.1885 LR:0.010000000000000002
Training: Epoch[097/182] Iteration[050/526] Loss: 0.0464 Acc:98.78%
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Epoch[097/182] Train Acc: 98.76% Valid Acc:95.72% Train loss:0.0482 Valid loss:0.1931 LR:0.010000000000000002
Training: Epoch[098/182] Iteration[050/526] Loss: 0.0406 Acc:98.84%
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Epoch[098/182] Train Acc: 98.81% Valid Acc:95.73% Train loss:0.0449 Valid loss:0.1911 LR:0.010000000000000002
Training: Epoch[099/182] Iteration[050/526] Loss: 0.0372 Acc:99.03%
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Epoch[099/182] Train Acc: 98.91% Valid Acc:95.58% Train loss:0.0422 Valid loss:0.2001 LR:0.010000000000000002
Training: Epoch[100/182] Iteration[050/526] Loss: 0.0410 Acc:98.97%
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Epoch[100/182] Train Acc: 98.97% Valid Acc:95.55% Train loss:0.0407 Valid loss:0.2002 LR:0.010000000000000002
Training: Epoch[101/182] Iteration[050/526] Loss: 0.0305 Acc:99.25%
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Epoch[101/182] Train Acc: 99.03% Valid Acc:95.75% Train loss:0.0382 Valid loss:0.2000 LR:0.010000000000000002
Training: Epoch[102/182] Iteration[050/526] Loss: 0.0364 Acc:99.11%
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Epoch[102/182] Train Acc: 99.06% Valid Acc:95.77% Train loss:0.0371 Valid loss:0.2034 LR:0.010000000000000002
Training: Epoch[103/182] Iteration[050/526] Loss: 0.0432 Acc:98.94%
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Epoch[103/182] Train Acc: 99.11% Valid Acc:95.63% Train loss:0.0346 Valid loss:0.2084 LR:0.010000000000000002
Training: Epoch[104/182] Iteration[050/526] Loss: 0.0379 Acc:99.11%
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Epoch[104/182] Train Acc: 99.14% Valid Acc:95.48% Train loss:0.0339 Valid loss:0.2129 LR:0.010000000000000002
Training: Epoch[105/182] Iteration[050/526] Loss: 0.0295 Acc:99.30%
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Epoch[105/182] Train Acc: 99.16% Valid Acc:95.58% Train loss:0.0319 Valid loss:0.2117 LR:0.010000000000000002
Training: Epoch[106/182] Iteration[050/526] Loss: 0.0305 Acc:99.19%
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Epoch[106/182] Train Acc: 99.19% Valid Acc:95.83% Train loss:0.0312 Valid loss:0.2100 LR:0.010000000000000002
Training: Epoch[107/182] Iteration[050/526] Loss: 0.0339 Acc:99.23%
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Epoch[107/182] Train Acc: 99.20% Valid Acc:95.47% Train loss:0.0306 Valid loss:0.2214 LR:0.010000000000000002
Training: Epoch[108/182] Iteration[050/526] Loss: 0.0258 Acc:99.42%
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Epoch[108/182] Train Acc: 99.26% Valid Acc:95.70% Train loss:0.0285 Valid loss:0.2234 LR:0.010000000000000002
Training: Epoch[109/182] Iteration[050/526] Loss: 0.0218 Acc:99.42%
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Epoch[109/182] Train Acc: 99.31% Valid Acc:95.55% Train loss:0.0263 Valid loss:0.2243 LR:0.010000000000000002
Training: Epoch[110/182] Iteration[050/526] Loss: 0.0293 Acc:99.33%
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Epoch[110/182] Train Acc: 99.27% Valid Acc:95.55% Train loss:0.0271 Valid loss:0.2330 LR:0.010000000000000002
Training: Epoch[111/182] Iteration[050/526] Loss: 0.0256 Acc:99.28%
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Epoch[111/182] Train Acc: 99.32% Valid Acc:95.62% Train loss:0.0251 Valid loss:0.2266 LR:0.010000000000000002
Training: Epoch[112/182] Iteration[050/526] Loss: 0.0234 Acc:99.42%
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Epoch[112/182] Train Acc: 99.37% Valid Acc:95.62% Train loss:0.0249 Valid loss:0.2242 LR:0.010000000000000002
Training: Epoch[113/182] Iteration[050/526] Loss: 0.0227 Acc:99.38%
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Epoch[113/182] Train Acc: 99.33% Valid Acc:95.60% Train loss:0.0242 Valid loss:0.2365 LR:0.010000000000000002
Training: Epoch[114/182] Iteration[050/526] Loss: 0.0220 Acc:99.38%
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Epoch[114/182] Train Acc: 99.37% Valid Acc:95.55% Train loss:0.0225 Valid loss:0.2404 LR:0.010000000000000002
Training: Epoch[115/182] Iteration[050/526] Loss: 0.0237 Acc:99.33%
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Epoch[115/182] Train Acc: 99.41% Valid Acc:95.40% Train loss:0.0218 Valid loss:0.2363 LR:0.010000000000000002
Training: Epoch[116/182] Iteration[050/526] Loss: 0.0222 Acc:99.50%
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Epoch[116/182] Train Acc: 99.45% Valid Acc:95.43% Train loss:0.0204 Valid loss:0.2421 LR:0.010000000000000002
Training: Epoch[117/182] Iteration[050/526] Loss: 0.0201 Acc:99.53%
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Epoch[117/182] Train Acc: 99.45% Valid Acc:95.33% Train loss:0.0196 Valid loss:0.2492 LR:0.010000000000000002
Training: Epoch[118/182] Iteration[050/526] Loss: 0.0217 Acc:99.50%
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Epoch[118/182] Train Acc: 99.46% Valid Acc:95.15% Train loss:0.0201 Valid loss:0.2531 LR:0.010000000000000002
Training: Epoch[119/182] Iteration[050/526] Loss: 0.0232 Acc:99.28%
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Epoch[119/182] Train Acc: 99.44% Valid Acc:95.42% Train loss:0.0193 Valid loss:0.2407 LR:0.010000000000000002
Training: Epoch[120/182] Iteration[050/526] Loss: 0.0234 Acc:99.31%
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Epoch[120/182] Train Acc: 99.43% Valid Acc:95.55% Train loss:0.0201 Valid loss:0.2391 LR:0.010000000000000002
Training: Epoch[121/182] Iteration[050/526] Loss: 0.0144 Acc:99.56%
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Epoch[121/182] Train Acc: 99.49% Valid Acc:95.50% Train loss:0.0184 Valid loss:0.2614 LR:0.010000000000000002
Training: Epoch[122/182] Iteration[050/526] Loss: 0.0135 Acc:99.61%
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Epoch[122/182] Train Acc: 99.53% Valid Acc:95.62% Train loss:0.0174 Valid loss:0.2693 LR:0.010000000000000002
Training: Epoch[123/182] Iteration[050/526] Loss: 0.0163 Acc:99.44%
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Epoch[123/182] Train Acc: 99.50% Valid Acc:95.53% Train loss:0.0177 Valid loss:0.2520 LR:0.010000000000000002
Training: Epoch[124/182] Iteration[050/526] Loss: 0.0167 Acc:99.58%
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Epoch[124/182] Train Acc: 99.49% Valid Acc:95.27% Train loss:0.0181 Valid loss:0.2615 LR:0.010000000000000002
Training: Epoch[125/182] Iteration[050/526] Loss: 0.0149 Acc:99.53%
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Epoch[125/182] Train Acc: 99.54% Valid Acc:95.37% Train loss:0.0166 Valid loss:0.2614 LR:0.010000000000000002
Training: Epoch[126/182] Iteration[050/526] Loss: 0.0152 Acc:99.58%
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Epoch[126/182] Train Acc: 99.49% Valid Acc:95.40% Train loss:0.0170 Valid loss:0.2706 LR:0.010000000000000002
Training: Epoch[127/182] Iteration[050/526] Loss: 0.0162 Acc:99.58%
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Epoch[127/182] Train Acc: 99.51% Valid Acc:95.15% Train loss:0.0169 Valid loss:0.2653 LR:0.010000000000000002
Training: Epoch[128/182] Iteration[050/526] Loss: 0.0184 Acc:99.47%
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Epoch[128/182] Train Acc: 99.55% Valid Acc:95.43% Train loss:0.0159 Valid loss:0.2567 LR:0.010000000000000002
Training: Epoch[129/182] Iteration[050/526] Loss: 0.0148 Acc:99.62%
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Epoch[129/182] Train Acc: 99.54% Valid Acc:95.38% Train loss:0.0154 Valid loss:0.2493 LR:0.010000000000000002
Training: Epoch[130/182] Iteration[050/526] Loss: 0.0117 Acc:99.58%
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Epoch[130/182] Train Acc: 99.52% Valid Acc:95.40% Train loss:0.0158 Valid loss:0.2609 LR:0.010000000000000002
Training: Epoch[131/182] Iteration[050/526] Loss: 0.0157 Acc:99.47%
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Epoch[131/182] Train Acc: 99.53% Valid Acc:95.33% Train loss:0.0155 Valid loss:0.2703 LR:0.010000000000000002
Training: Epoch[132/182] Iteration[050/526] Loss: 0.0178 Acc:99.47%
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Epoch[132/182] Train Acc: 99.55% Valid Acc:95.57% Train loss:0.0153 Valid loss:0.2590 LR:0.010000000000000002
Training: Epoch[133/182] Iteration[050/526] Loss: 0.0138 Acc:99.62%
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Epoch[133/182] Train Acc: 99.60% Valid Acc:95.03% Train loss:0.0136 Valid loss:0.2694 LR:0.010000000000000002
Training: Epoch[134/182] Iteration[050/526] Loss: 0.0144 Acc:99.61%
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Epoch[134/182] Train Acc: 99.59% Valid Acc:95.28% Train loss:0.0140 Valid loss:0.2719 LR:0.010000000000000002
Training: Epoch[135/182] Iteration[050/526] Loss: 0.0125 Acc:99.66%
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Epoch[135/182] Train Acc: 99.62% Valid Acc:95.18% Train loss:0.0130 Valid loss:0.2759 LR:0.010000000000000002
Training: Epoch[136/182] Iteration[050/526] Loss: 0.0104 Acc:99.70%
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Epoch[136/182] Train Acc: 99.56% Valid Acc:95.23% Train loss:0.0141 Valid loss:0.2791 LR:0.010000000000000002
Training: Epoch[137/182] Iteration[050/526] Loss: 0.0128 Acc:99.62%
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Epoch[137/182] Train Acc: 99.70% Valid Acc:95.47% Train loss:0.0111 Valid loss:0.2674 LR:0.0010000000000000002
Training: Epoch[138/182] Iteration[050/526] Loss: 0.0102 Acc:99.73%
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Epoch[138/182] Train Acc: 99.76% Valid Acc:95.50% Train loss:0.0092 Valid loss:0.2683 LR:0.0010000000000000002
Training: Epoch[139/182] Iteration[050/526] Loss: 0.0087 Acc:99.77%
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Epoch[139/182] Train Acc: 99.79% Valid Acc:95.55% Train loss:0.0080 Valid loss:0.2693 LR:0.0010000000000000002
Training: Epoch[140/182] Iteration[050/526] Loss: 0.0072 Acc:99.81%
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Epoch[140/182] Train Acc: 99.80% Valid Acc:95.50% Train loss:0.0079 Valid loss:0.2715 LR:0.0010000000000000002
Training: Epoch[141/182] Iteration[050/526] Loss: 0.0079 Acc:99.77%
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Epoch[141/182] Train Acc: 99.82% Valid Acc:95.50% Train loss:0.0070 Valid loss:0.2730 LR:0.0010000000000000002
Training: Epoch[142/182] Iteration[050/526] Loss: 0.0103 Acc:99.70%
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Epoch[142/182] Train Acc: 99.81% Valid Acc:95.53% Train loss:0.0072 Valid loss:0.2725 LR:0.0010000000000000002
Training: Epoch[143/182] Iteration[050/526] Loss: 0.0080 Acc:99.83%
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Epoch[143/182] Train Acc: 99.85% Valid Acc:95.55% Train loss:0.0063 Valid loss:0.2746 LR:0.0010000000000000002
Training: Epoch[144/182] Iteration[050/526] Loss: 0.0067 Acc:99.84%
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Epoch[144/182] Train Acc: 99.83% Valid Acc:95.60% Train loss:0.0071 Valid loss:0.2767 LR:0.0010000000000000002
Training: Epoch[145/182] Iteration[050/526] Loss: 0.0050 Acc:99.92%
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Epoch[145/182] Train Acc: 99.85% Valid Acc:95.68% Train loss:0.0064 Valid loss:0.2750 LR:0.0010000000000000002
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Epoch[146/182] Train Acc: 99.85% Valid Acc:95.55% Train loss:0.0065 Valid loss:0.2773 LR:0.0010000000000000002
Training: Epoch[147/182] Iteration[050/526] Loss: 0.0060 Acc:99.84%
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Epoch[147/182] Train Acc: 99.84% Valid Acc:95.65% Train loss:0.0062 Valid loss:0.2741 LR:0.0010000000000000002
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Epoch[148/182] Train Acc: 99.85% Valid Acc:95.53% Train loss:0.0063 Valid loss:0.2763 LR:0.0010000000000000002
Training: Epoch[149/182] Iteration[050/526] Loss: 0.0048 Acc:99.92%
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Epoch[149/182] Train Acc: 99.85% Valid Acc:95.63% Train loss:0.0061 Valid loss:0.2748 LR:0.0010000000000000002
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Epoch[150/182] Train Acc: 99.88% Valid Acc:95.55% Train loss:0.0055 Valid loss:0.2782 LR:0.0010000000000000002
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Epoch[151/182] Train Acc: 99.84% Valid Acc:95.57% Train loss:0.0062 Valid loss:0.2794 LR:0.0010000000000000002
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Epoch[152/182] Train Acc: 99.87% Valid Acc:95.58% Train loss:0.0058 Valid loss:0.2806 LR:0.0010000000000000002
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Epoch[153/182] Train Acc: 99.89% Valid Acc:95.58% Train loss:0.0055 Valid loss:0.2802 LR:0.0010000000000000002
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Epoch[154/182] Train Acc: 99.87% Valid Acc:95.55% Train loss:0.0057 Valid loss:0.2795 LR:0.0010000000000000002
Training: Epoch[155/182] Iteration[050/526] Loss: 0.0045 Acc:99.88%
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Epoch[155/182] Train Acc: 99.86% Valid Acc:95.60% Train loss:0.0055 Valid loss:0.2779 LR:0.0010000000000000002
Training: Epoch[156/182] Iteration[050/526] Loss: 0.0042 Acc:99.94%
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Epoch[156/182] Train Acc: 99.87% Valid Acc:95.63% Train loss:0.0053 Valid loss:0.2794 LR:0.0010000000000000002
Training: Epoch[157/182] Iteration[050/526] Loss: 0.0047 Acc:99.92%
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Epoch[157/182] Train Acc: 99.88% Valid Acc:95.58% Train loss:0.0053 Valid loss:0.2820 LR:0.0010000000000000002
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Epoch[158/182] Train Acc: 99.90% Valid Acc:95.47% Train loss:0.0051 Valid loss:0.2811 LR:0.0010000000000000002
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Epoch[159/182] Train Acc: 99.88% Valid Acc:95.45% Train loss:0.0053 Valid loss:0.2827 LR:0.0010000000000000002
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Epoch[160/182] Train Acc: 99.88% Valid Acc:95.50% Train loss:0.0052 Valid loss:0.2834 LR:0.0010000000000000002
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Epoch[161/182] Train Acc: 99.89% Valid Acc:95.50% Train loss:0.0050 Valid loss:0.2865 LR:0.0010000000000000002
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Epoch[162/182] Train Acc: 99.90% Valid Acc:95.62% Train loss:0.0049 Valid loss:0.2840 LR:0.0010000000000000002
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Epoch[163/182] Train Acc: 99.89% Valid Acc:95.52% Train loss:0.0050 Valid loss:0.2838 LR:0.0010000000000000002
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Epoch[164/182] Train Acc: 99.89% Valid Acc:95.48% Train loss:0.0049 Valid loss:0.2838 LR:0.0010000000000000002
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Epoch[165/182] Train Acc: 99.89% Valid Acc:95.45% Train loss:0.0047 Valid loss:0.2879 LR:0.0010000000000000002
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Training: Epoch[166/182] Iteration[500/526] Loss: 0.0050 Acc:99.89%
Epoch[166/182] Train Acc: 99.89% Valid Acc:95.48% Train loss:0.0050 Valid loss:0.2891 LR:0.0010000000000000002
Training: Epoch[167/182] Iteration[050/526] Loss: 0.0039 Acc:99.94%
Training: Epoch[167/182] Iteration[100/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[167/182] Iteration[150/526] Loss: 0.0039 Acc:99.92%
Training: Epoch[167/182] Iteration[200/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[167/182] Iteration[250/526] Loss: 0.0044 Acc:99.91%
Training: Epoch[167/182] Iteration[300/526] Loss: 0.0044 Acc:99.91%
Training: Epoch[167/182] Iteration[350/526] Loss: 0.0044 Acc:99.91%
Training: Epoch[167/182] Iteration[400/526] Loss: 0.0046 Acc:99.90%
Training: Epoch[167/182] Iteration[450/526] Loss: 0.0045 Acc:99.91%
Training: Epoch[167/182] Iteration[500/526] Loss: 0.0045 Acc:99.91%
Epoch[167/182] Train Acc: 99.90% Valid Acc:95.57% Train loss:0.0045 Valid loss:0.2856 LR:0.0010000000000000002
Training: Epoch[168/182] Iteration[050/526] Loss: 0.0045 Acc:99.88%
Training: Epoch[168/182] Iteration[100/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[168/182] Iteration[150/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[168/182] Iteration[200/526] Loss: 0.0040 Acc:99.92%
Training: Epoch[168/182] Iteration[250/526] Loss: 0.0040 Acc:99.92%
Training: Epoch[168/182] Iteration[300/526] Loss: 0.0040 Acc:99.92%
Training: Epoch[168/182] Iteration[350/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[168/182] Iteration[400/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[168/182] Iteration[450/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[168/182] Iteration[500/526] Loss: 0.0047 Acc:99.89%
Epoch[168/182] Train Acc: 99.89% Valid Acc:95.47% Train loss:0.0047 Valid loss:0.2876 LR:0.0010000000000000002
Training: Epoch[169/182] Iteration[050/526] Loss: 0.0039 Acc:99.94%
Training: Epoch[169/182] Iteration[100/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[169/182] Iteration[150/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[169/182] Iteration[200/526] Loss: 0.0044 Acc:99.90%
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Training: Epoch[169/182] Iteration[300/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[169/182] Iteration[350/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[169/182] Iteration[400/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[169/182] Iteration[450/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[169/182] Iteration[500/526] Loss: 0.0044 Acc:99.90%
Epoch[169/182] Train Acc: 99.90% Valid Acc:95.53% Train loss:0.0044 Valid loss:0.2879 LR:0.0010000000000000002
Training: Epoch[170/182] Iteration[050/526] Loss: 0.0047 Acc:99.89%
Training: Epoch[170/182] Iteration[100/526] Loss: 0.0047 Acc:99.87%
Training: Epoch[170/182] Iteration[150/526] Loss: 0.0044 Acc:99.89%
Training: Epoch[170/182] Iteration[200/526] Loss: 0.0046 Acc:99.89%
Training: Epoch[170/182] Iteration[250/526] Loss: 0.0049 Acc:99.89%
Training: Epoch[170/182] Iteration[300/526] Loss: 0.0051 Acc:99.88%
Training: Epoch[170/182] Iteration[350/526] Loss: 0.0050 Acc:99.88%
Training: Epoch[170/182] Iteration[400/526] Loss: 0.0051 Acc:99.88%
Training: Epoch[170/182] Iteration[450/526] Loss: 0.0049 Acc:99.89%
Training: Epoch[170/182] Iteration[500/526] Loss: 0.0049 Acc:99.89%
Epoch[170/182] Train Acc: 99.89% Valid Acc:95.57% Train loss:0.0048 Valid loss:0.2883 LR:0.0010000000000000002
Training: Epoch[171/182] Iteration[050/526] Loss: 0.0063 Acc:99.86%
Training: Epoch[171/182] Iteration[100/526] Loss: 0.0053 Acc:99.90%
Training: Epoch[171/182] Iteration[150/526] Loss: 0.0049 Acc:99.90%
Training: Epoch[171/182] Iteration[200/526] Loss: 0.0047 Acc:99.91%
Training: Epoch[171/182] Iteration[250/526] Loss: 0.0045 Acc:99.91%
Training: Epoch[171/182] Iteration[300/526] Loss: 0.0046 Acc:99.90%
Training: Epoch[171/182] Iteration[350/526] Loss: 0.0045 Acc:99.91%
Training: Epoch[171/182] Iteration[400/526] Loss: 0.0046 Acc:99.90%
Training: Epoch[171/182] Iteration[450/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[171/182] Iteration[500/526] Loss: 0.0046 Acc:99.89%
Epoch[171/182] Train Acc: 99.89% Valid Acc:95.43% Train loss:0.0047 Valid loss:0.2861 LR:0.0010000000000000002
Training: Epoch[172/182] Iteration[050/526] Loss: 0.0041 Acc:99.97%
Training: Epoch[172/182] Iteration[100/526] Loss: 0.0042 Acc:99.93%
Training: Epoch[172/182] Iteration[150/526] Loss: 0.0044 Acc:99.92%
Training: Epoch[172/182] Iteration[200/526] Loss: 0.0041 Acc:99.93%
Training: Epoch[172/182] Iteration[250/526] Loss: 0.0041 Acc:99.93%
Training: Epoch[172/182] Iteration[300/526] Loss: 0.0041 Acc:99.93%
Training: Epoch[172/182] Iteration[350/526] Loss: 0.0041 Acc:99.93%
Training: Epoch[172/182] Iteration[400/526] Loss: 0.0042 Acc:99.92%
Training: Epoch[172/182] Iteration[450/526] Loss: 0.0043 Acc:99.92%
Training: Epoch[172/182] Iteration[500/526] Loss: 0.0044 Acc:99.92%
Epoch[172/182] Train Acc: 99.92% Valid Acc:95.47% Train loss:0.0045 Valid loss:0.2871 LR:0.0010000000000000002
Training: Epoch[173/182] Iteration[050/526] Loss: 0.0040 Acc:99.94%
Training: Epoch[173/182] Iteration[100/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[173/182] Iteration[150/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[173/182] Iteration[200/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[173/182] Iteration[250/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[173/182] Iteration[300/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[173/182] Iteration[350/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[173/182] Iteration[400/526] Loss: 0.0047 Acc:99.89%
Training: Epoch[173/182] Iteration[450/526] Loss: 0.0047 Acc:99.89%
Training: Epoch[173/182] Iteration[500/526] Loss: 0.0047 Acc:99.89%
Epoch[173/182] Train Acc: 99.89% Valid Acc:95.47% Train loss:0.0047 Valid loss:0.2882 LR:0.0010000000000000002
Training: Epoch[174/182] Iteration[050/526] Loss: 0.0038 Acc:99.91%
Training: Epoch[174/182] Iteration[100/526] Loss: 0.0039 Acc:99.93%
Training: Epoch[174/182] Iteration[150/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[174/182] Iteration[200/526] Loss: 0.0040 Acc:99.92%
Training: Epoch[174/182] Iteration[250/526] Loss: 0.0042 Acc:99.92%
Training: Epoch[174/182] Iteration[300/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[174/182] Iteration[350/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[174/182] Iteration[400/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[174/182] Iteration[450/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[174/182] Iteration[500/526] Loss: 0.0044 Acc:99.90%
Epoch[174/182] Train Acc: 99.90% Valid Acc:95.42% Train loss:0.0045 Valid loss:0.2898 LR:0.0010000000000000002
Training: Epoch[175/182] Iteration[050/526] Loss: 0.0046 Acc:99.86%
Training: Epoch[175/182] Iteration[100/526] Loss: 0.0041 Acc:99.89%
Training: Epoch[175/182] Iteration[150/526] Loss: 0.0040 Acc:99.91%
Training: Epoch[175/182] Iteration[200/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[175/182] Iteration[250/526] Loss: 0.0042 Acc:99.91%
Training: Epoch[175/182] Iteration[300/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[175/182] Iteration[350/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[175/182] Iteration[400/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[175/182] Iteration[450/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[175/182] Iteration[500/526] Loss: 0.0041 Acc:99.92%
Epoch[175/182] Train Acc: 99.91% Valid Acc:95.47% Train loss:0.0043 Valid loss:0.2892 LR:0.0010000000000000002
Training: Epoch[176/182] Iteration[050/526] Loss: 0.0039 Acc:99.92%
Training: Epoch[176/182] Iteration[100/526] Loss: 0.0038 Acc:99.94%
Training: Epoch[176/182] Iteration[150/526] Loss: 0.0035 Acc:99.94%
Training: Epoch[176/182] Iteration[200/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[176/182] Iteration[250/526] Loss: 0.0044 Acc:99.89%
Training: Epoch[176/182] Iteration[300/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[176/182] Iteration[350/526] Loss: 0.0044 Acc:99.89%
Training: Epoch[176/182] Iteration[400/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[176/182] Iteration[450/526] Loss: 0.0044 Acc:99.90%
Training: Epoch[176/182] Iteration[500/526] Loss: 0.0044 Acc:99.90%
Epoch[176/182] Train Acc: 99.90% Valid Acc:95.40% Train loss:0.0045 Valid loss:0.2922 LR:0.0010000000000000002
Training: Epoch[177/182] Iteration[050/526] Loss: 0.0043 Acc:99.94%
Training: Epoch[177/182] Iteration[100/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[177/182] Iteration[150/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[177/182] Iteration[200/526] Loss: 0.0048 Acc:99.88%
Training: Epoch[177/182] Iteration[250/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[177/182] Iteration[300/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[177/182] Iteration[350/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[177/182] Iteration[400/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[177/182] Iteration[450/526] Loss: 0.0042 Acc:99.91%
Training: Epoch[177/182] Iteration[500/526] Loss: 0.0041 Acc:99.91%
Epoch[177/182] Train Acc: 99.91% Valid Acc:95.45% Train loss:0.0041 Valid loss:0.2924 LR:0.0010000000000000002
Training: Epoch[178/182] Iteration[050/526] Loss: 0.0045 Acc:99.91%
Training: Epoch[178/182] Iteration[100/526] Loss: 0.0054 Acc:99.86%
Training: Epoch[178/182] Iteration[150/526] Loss: 0.0050 Acc:99.87%
Training: Epoch[178/182] Iteration[200/526] Loss: 0.0052 Acc:99.86%
Training: Epoch[178/182] Iteration[250/526] Loss: 0.0049 Acc:99.88%
Training: Epoch[178/182] Iteration[300/526] Loss: 0.0048 Acc:99.88%
Training: Epoch[178/182] Iteration[350/526] Loss: 0.0047 Acc:99.89%
Training: Epoch[178/182] Iteration[400/526] Loss: 0.0046 Acc:99.88%
Training: Epoch[178/182] Iteration[450/526] Loss: 0.0045 Acc:99.88%
Training: Epoch[178/182] Iteration[500/526] Loss: 0.0045 Acc:99.89%
Epoch[178/182] Train Acc: 99.89% Valid Acc:95.37% Train loss:0.0045 Valid loss:0.2943 LR:0.0010000000000000002
Training: Epoch[179/182] Iteration[050/526] Loss: 0.0052 Acc:99.86%
Training: Epoch[179/182] Iteration[100/526] Loss: 0.0047 Acc:99.90%
Training: Epoch[179/182] Iteration[150/526] Loss: 0.0050 Acc:99.90%
Training: Epoch[179/182] Iteration[200/526] Loss: 0.0048 Acc:99.90%
Training: Epoch[179/182] Iteration[250/526] Loss: 0.0049 Acc:99.90%
Training: Epoch[179/182] Iteration[300/526] Loss: 0.0048 Acc:99.90%
Training: Epoch[179/182] Iteration[350/526] Loss: 0.0046 Acc:99.91%
Training: Epoch[179/182] Iteration[400/526] Loss: 0.0046 Acc:99.90%
Training: Epoch[179/182] Iteration[450/526] Loss: 0.0045 Acc:99.90%
Training: Epoch[179/182] Iteration[500/526] Loss: 0.0044 Acc:99.91%
Epoch[179/182] Train Acc: 99.91% Valid Acc:95.45% Train loss:0.0044 Valid loss:0.2924 LR:0.0010000000000000002
Training: Epoch[180/182] Iteration[050/526] Loss: 0.0049 Acc:99.84%
Training: Epoch[180/182] Iteration[100/526] Loss: 0.0050 Acc:99.85%
Training: Epoch[180/182] Iteration[150/526] Loss: 0.0046 Acc:99.87%
Training: Epoch[180/182] Iteration[200/526] Loss: 0.0049 Acc:99.85%
Training: Epoch[180/182] Iteration[250/526] Loss: 0.0050 Acc:99.85%
Training: Epoch[180/182] Iteration[300/526] Loss: 0.0051 Acc:99.86%
Training: Epoch[180/182] Iteration[350/526] Loss: 0.0050 Acc:99.87%
Training: Epoch[180/182] Iteration[400/526] Loss: 0.0048 Acc:99.88%
Training: Epoch[180/182] Iteration[450/526] Loss: 0.0047 Acc:99.88%
Training: Epoch[180/182] Iteration[500/526] Loss: 0.0048 Acc:99.88%
Epoch[180/182] Train Acc: 99.88% Valid Acc:95.47% Train loss:0.0048 Valid loss:0.2928 LR:0.0010000000000000002
Training: Epoch[181/182] Iteration[050/526] Loss: 0.0033 Acc:99.92%
Training: Epoch[181/182] Iteration[100/526] Loss: 0.0049 Acc:99.87%
Training: Epoch[181/182] Iteration[150/526] Loss: 0.0045 Acc:99.89%
Training: Epoch[181/182] Iteration[200/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[181/182] Iteration[250/526] Loss: 0.0042 Acc:99.91%
Training: Epoch[181/182] Iteration[300/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[181/182] Iteration[350/526] Loss: 0.0041 Acc:99.91%
Training: Epoch[181/182] Iteration[400/526] Loss: 0.0043 Acc:99.91%
Training: Epoch[181/182] Iteration[450/526] Loss: 0.0043 Acc:99.90%
Training: Epoch[181/182] Iteration[500/526] Loss: 0.0043 Acc:99.90%
Epoch[181/182] Train Acc: 99.90% Valid Acc:95.50% Train loss:0.0044 Valid loss:0.2901 LR:0.0010000000000000002
Training: Epoch[182/182] Iteration[050/526] Loss: 0.0043 Acc:99.94%
Training: Epoch[182/182] Iteration[100/526] Loss: 0.0044 Acc:99.91%
Training: Epoch[182/182] Iteration[150/526] Loss: 0.0041 Acc:99.92%
Training: Epoch[182/182] Iteration[200/526] Loss: 0.0039 Acc:99.92%
Training: Epoch[182/182] Iteration[250/526] Loss: 0.0039 Acc:99.92%
Training: Epoch[182/182] Iteration[300/526] Loss: 0.0038 Acc:99.92%
Training: Epoch[182/182] Iteration[350/526] Loss: 0.0039 Acc:99.91%
Training: Epoch[182/182] Iteration[400/526] Loss: 0.0041 Acc:99.90%
Training: Epoch[182/182] Iteration[450/526] Loss: 0.0042 Acc:99.90%
Training: Epoch[182/182] Iteration[500/526] Loss: 0.0044 Acc:99.90%
Epoch[182/182] Train Acc: 99.90% Valid Acc:95.42% Train loss:0.0044 Valid loss:0.2920 LR:0.0010000000000000002

python ./src/eval.py --model q44 --check_point ./results/05-26_11-57/checkpoint_best.pkl

Acknowledgments and References

• Quotient Network-A Network Similar to ResNet but Learning Quotients (GitHub)

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