generated_from_trainer

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6_e_200-tiny_tobacco3482_kd_CEKD_t1.5_a0.5

This model is a fine-tuned version of WinKawaks/vit-tiny-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

Training results

Training Loss Epoch Step Validation Loss Accuracy Brier Loss Nll F1 Micro F1 Macro Ece Aurc
No log 1.0 25 1.6826 0.23 0.8622 4.7953 0.23 0.1892 0.2929 0.7651
No log 2.0 50 1.0374 0.53 0.6004 2.7646 0.53 0.4280 0.2624 0.2619
No log 3.0 75 0.8158 0.665 0.4678 2.4034 0.665 0.5565 0.2488 0.1416
No log 4.0 100 0.6879 0.72 0.3838 1.5355 0.72 0.6873 0.2297 0.1064
No log 5.0 125 0.6511 0.775 0.3538 1.5183 0.775 0.7285 0.2235 0.0915
No log 6.0 150 0.7310 0.755 0.3579 1.3899 0.755 0.7257 0.2190 0.0926
No log 7.0 175 0.5698 0.795 0.3246 1.3920 0.795 0.7691 0.2251 0.0956
No log 8.0 200 0.5675 0.805 0.3064 1.4278 0.805 0.7733 0.2093 0.0655
No log 9.0 225 0.5986 0.8 0.3356 1.5317 0.8000 0.7890 0.2249 0.0913
No log 10.0 250 0.6158 0.755 0.3475 1.5027 0.755 0.7340 0.2152 0.0782
No log 11.0 275 0.5353 0.815 0.3037 1.6003 0.815 0.8143 0.2305 0.0749
No log 12.0 300 0.5460 0.825 0.3008 1.7407 0.825 0.8070 0.2378 0.0856
No log 13.0 325 0.4905 0.83 0.2787 1.1328 0.83 0.8099 0.2344 0.0481
No log 14.0 350 0.4913 0.795 0.2881 1.2261 0.795 0.7521 0.2121 0.0661
No log 15.0 375 0.4773 0.835 0.2753 1.2716 0.835 0.8140 0.2125 0.0636
No log 16.0 400 0.4848 0.84 0.2751 1.5983 0.8400 0.8139 0.2195 0.0707
No log 17.0 425 0.4994 0.805 0.2886 1.5637 0.805 0.7689 0.2049 0.0617
No log 18.0 450 0.4610 0.835 0.2871 1.3906 0.835 0.8122 0.2175 0.0675
No log 19.0 475 0.4594 0.84 0.2669 1.2217 0.8400 0.8214 0.2022 0.0516
0.4534 20.0 500 0.4793 0.815 0.2874 1.4445 0.815 0.7965 0.2024 0.0641
0.4534 21.0 525 0.5185 0.785 0.3215 1.8358 0.785 0.7743 0.2250 0.0850
0.4534 22.0 550 0.4339 0.83 0.2635 1.2137 0.83 0.8200 0.1944 0.0610
0.4534 23.0 575 0.4640 0.825 0.2770 1.4137 0.825 0.8086 0.1800 0.0674
0.4534 24.0 600 0.4528 0.825 0.2692 1.3148 0.825 0.8077 0.1912 0.0678
0.4534 25.0 625 0.4361 0.84 0.2600 1.4205 0.8400 0.8278 0.2066 0.0534
0.4534 26.0 650 0.4239 0.835 0.2590 1.2112 0.835 0.8224 0.1850 0.0544
0.4534 27.0 675 0.4294 0.82 0.2636 1.2671 0.82 0.8023 0.1866 0.0619
0.4534 28.0 700 0.4327 0.84 0.2633 1.3084 0.8400 0.8283 0.1954 0.0628
0.4534 29.0 725 0.4309 0.825 0.2640 1.4275 0.825 0.8022 0.2117 0.0667
0.4534 30.0 750 0.4299 0.83 0.2636 1.3161 0.83 0.8103 0.2110 0.0620
0.4534 31.0 775 0.4345 0.835 0.2634 1.4605 0.835 0.8269 0.1998 0.0562
0.4534 32.0 800 0.4404 0.83 0.2743 1.3965 0.83 0.8077 0.2198 0.0669
0.4534 33.0 825 0.4254 0.83 0.2614 1.3734 0.83 0.8133 0.1990 0.0567
0.4534 34.0 850 0.4271 0.835 0.2632 1.3963 0.835 0.8164 0.1932 0.0649
0.4534 35.0 875 0.4284 0.835 0.2636 1.3713 0.835 0.8164 0.2127 0.0634
0.4534 36.0 900 0.4262 0.835 0.2628 1.4403 0.835 0.8164 0.1926 0.0649
0.4534 37.0 925 0.4253 0.835 0.2621 1.3813 0.835 0.8164 0.2015 0.0628
0.4534 38.0 950 0.4262 0.835 0.2626 1.4528 0.835 0.8164 0.1971 0.0628
0.4534 39.0 975 0.4271 0.835 0.2629 1.4410 0.835 0.8164 0.1933 0.0627
0.0663 40.0 1000 0.4283 0.835 0.2639 1.4647 0.835 0.8164 0.1996 0.0631
0.0663 41.0 1025 0.4272 0.835 0.2639 1.4417 0.835 0.8164 0.2088 0.0630
0.0663 42.0 1050 0.4276 0.835 0.2640 1.3976 0.835 0.8164 0.1992 0.0634
0.0663 43.0 1075 0.4270 0.835 0.2633 1.4392 0.835 0.8164 0.1892 0.0628
0.0663 44.0 1100 0.4264 0.835 0.2635 1.4429 0.835 0.8164 0.1885 0.0631
0.0663 45.0 1125 0.4269 0.835 0.2637 1.4461 0.835 0.8164 0.1974 0.0629
0.0663 46.0 1150 0.4268 0.835 0.2636 1.4415 0.835 0.8164 0.1866 0.0625
0.0663 47.0 1175 0.4269 0.835 0.2641 1.4646 0.835 0.8164 0.1812 0.0636
0.0663 48.0 1200 0.4271 0.835 0.2639 1.3990 0.835 0.8164 0.1865 0.0631
0.0663 49.0 1225 0.4267 0.835 0.2639 1.4474 0.835 0.8164 0.1946 0.0629
0.0663 50.0 1250 0.4273 0.835 0.2642 1.4492 0.835 0.8164 0.1802 0.0631
0.0663 51.0 1275 0.4272 0.835 0.2644 1.4475 0.835 0.8164 0.1942 0.0630
0.0663 52.0 1300 0.4283 0.835 0.2648 1.5157 0.835 0.8164 0.1963 0.0635
0.0663 53.0 1325 0.4271 0.835 0.2643 1.5046 0.835 0.8164 0.1955 0.0633
0.0663 54.0 1350 0.4271 0.835 0.2642 1.4629 0.835 0.8164 0.1790 0.0617
0.0663 55.0 1375 0.4278 0.835 0.2649 1.5752 0.835 0.8164 0.2007 0.0635
0.0663 56.0 1400 0.4280 0.835 0.2648 1.5165 0.835 0.8164 0.1706 0.0631
0.0663 57.0 1425 0.4275 0.835 0.2644 1.5134 0.835 0.8164 0.1864 0.0629
0.0663 58.0 1450 0.4270 0.835 0.2643 1.5088 0.835 0.8164 0.1883 0.0630
0.0663 59.0 1475 0.4273 0.835 0.2644 1.5111 0.835 0.8164 0.1951 0.0630
0.0615 60.0 1500 0.4281 0.835 0.2651 1.5727 0.835 0.8164 0.2084 0.0630
0.0615 61.0 1525 0.4271 0.835 0.2647 1.5198 0.835 0.8164 0.1957 0.0631
0.0615 62.0 1550 0.4276 0.835 0.2649 1.5139 0.835 0.8164 0.1969 0.0630
0.0615 63.0 1575 0.4269 0.835 0.2646 1.4579 0.835 0.8164 0.1802 0.0629
0.0615 64.0 1600 0.4275 0.835 0.2648 1.5144 0.835 0.8164 0.2006 0.0632
0.0615 65.0 1625 0.4276 0.835 0.2649 1.5129 0.835 0.8164 0.1846 0.0632
0.0615 66.0 1650 0.4272 0.835 0.2647 1.5165 0.835 0.8164 0.1796 0.0629
0.0615 67.0 1675 0.4273 0.835 0.2647 1.5141 0.835 0.8164 0.1882 0.0631
0.0615 68.0 1700 0.4276 0.835 0.2649 1.5146 0.835 0.8164 0.1799 0.0631
0.0615 69.0 1725 0.4275 0.835 0.2649 1.5215 0.835 0.8164 0.1799 0.0631
0.0615 70.0 1750 0.4275 0.835 0.2647 1.5124 0.835 0.8164 0.1884 0.0632
0.0615 71.0 1775 0.4278 0.835 0.2652 1.5245 0.835 0.8164 0.1800 0.0631
0.0615 72.0 1800 0.4277 0.835 0.2650 1.5169 0.835 0.8164 0.1802 0.0631
0.0615 73.0 1825 0.4277 0.835 0.2651 1.5282 0.835 0.8164 0.1804 0.0633
0.0615 74.0 1850 0.4273 0.835 0.2650 1.5156 0.835 0.8164 0.1804 0.0632
0.0615 75.0 1875 0.4278 0.835 0.2653 1.5706 0.835 0.8164 0.1804 0.0632
0.0615 76.0 1900 0.4275 0.835 0.2651 1.5337 0.835 0.8164 0.1807 0.0633
0.0615 77.0 1925 0.4276 0.835 0.2652 1.5357 0.835 0.8164 0.1804 0.0633
0.0615 78.0 1950 0.4275 0.835 0.2651 1.5701 0.835 0.8164 0.1805 0.0633
0.0615 79.0 1975 0.4277 0.835 0.2651 1.5161 0.835 0.8164 0.1807 0.0633
0.0614 80.0 2000 0.4278 0.835 0.2653 1.5709 0.835 0.8164 0.1808 0.0632
0.0614 81.0 2025 0.4278 0.835 0.2653 1.5703 0.835 0.8164 0.1804 0.0632
0.0614 82.0 2050 0.4278 0.835 0.2653 1.5700 0.835 0.8164 0.1806 0.0633
0.0614 83.0 2075 0.4277 0.835 0.2652 1.5700 0.835 0.8164 0.1803 0.0631
0.0614 84.0 2100 0.4276 0.835 0.2652 1.5694 0.835 0.8164 0.1804 0.0632
0.0614 85.0 2125 0.4275 0.835 0.2652 1.5702 0.835 0.8164 0.1807 0.0633
0.0614 86.0 2150 0.4276 0.835 0.2652 1.5699 0.835 0.8164 0.1805 0.0633
0.0614 87.0 2175 0.4277 0.835 0.2653 1.5703 0.835 0.8164 0.1805 0.0633
0.0614 88.0 2200 0.4277 0.835 0.2652 1.5702 0.835 0.8164 0.1882 0.0632
0.0614 89.0 2225 0.4277 0.835 0.2653 1.5702 0.835 0.8164 0.1806 0.0633
0.0614 90.0 2250 0.4276 0.835 0.2653 1.5696 0.835 0.8164 0.1806 0.0633
0.0614 91.0 2275 0.4277 0.835 0.2653 1.5698 0.835 0.8164 0.1805 0.0632
0.0614 92.0 2300 0.4276 0.835 0.2652 1.5699 0.835 0.8164 0.1805 0.0632
0.0614 93.0 2325 0.4277 0.835 0.2653 1.5700 0.835 0.8164 0.1805 0.0632
0.0614 94.0 2350 0.4276 0.835 0.2653 1.5698 0.835 0.8164 0.1805 0.0632
0.0614 95.0 2375 0.4277 0.835 0.2653 1.5699 0.835 0.8164 0.1805 0.0632
0.0614 96.0 2400 0.4276 0.835 0.2653 1.5700 0.835 0.8164 0.1805 0.0632
0.0614 97.0 2425 0.4277 0.835 0.2653 1.5699 0.835 0.8164 0.1805 0.0632
0.0614 98.0 2450 0.4276 0.835 0.2653 1.5699 0.835 0.8164 0.1805 0.0632
0.0614 99.0 2475 0.4277 0.835 0.2653 1.5700 0.835 0.8164 0.1805 0.0632
0.0614 100.0 2500 0.4277 0.835 0.2653 1.5700 0.835 0.8164 0.1805 0.0632

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