generated_from_trainer

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vit-tiny_tobacco3482_hint_

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 59.9929 0.25 0.8706 4.9000 0.25 0.1856 0.3000 0.7819
No log 2.0 50 59.2119 0.54 0.5951 2.8481 0.54 0.4540 0.2868 0.2585
No log 3.0 75 58.7608 0.675 0.4417 1.6161 0.675 0.6086 0.2356 0.1335
No log 4.0 100 58.5280 0.75 0.3897 1.7733 0.75 0.7378 0.2211 0.1173
No log 5.0 125 58.2236 0.81 0.3119 1.5196 0.81 0.7653 0.1573 0.0769
No log 6.0 150 58.0804 0.805 0.3048 1.6467 0.805 0.7766 0.1355 0.0599
No log 7.0 175 58.3912 0.645 0.5320 2.1424 0.645 0.6017 0.2645 0.1497
No log 8.0 200 57.7380 0.755 0.3634 1.4581 0.755 0.7173 0.1913 0.0920
No log 9.0 225 57.5060 0.805 0.2939 1.4346 0.805 0.7860 0.1603 0.0636
No log 10.0 250 57.5367 0.805 0.3345 1.7441 0.805 0.7872 0.1748 0.0727
No log 11.0 275 57.7193 0.725 0.4195 1.7223 0.7250 0.6706 0.2121 0.0984
No log 12.0 300 57.5447 0.785 0.3435 1.7574 0.785 0.7772 0.1667 0.0678
No log 13.0 325 57.4991 0.795 0.3335 1.5337 0.795 0.7724 0.1685 0.0895
No log 14.0 350 57.3536 0.835 0.2942 1.5660 0.835 0.8089 0.1451 0.0594
No log 15.0 375 57.5013 0.815 0.3096 1.7294 0.815 0.7978 0.1579 0.0696
No log 16.0 400 57.3610 0.835 0.2763 1.7078 0.835 0.8182 0.1354 0.0526
No log 17.0 425 57.3415 0.825 0.3002 1.3895 0.825 0.8249 0.1455 0.0651
No log 18.0 450 57.4573 0.79 0.3649 1.6263 0.79 0.7688 0.1936 0.0943
No log 19.0 475 57.5728 0.8 0.3261 1.7616 0.8000 0.7461 0.1669 0.0659
57.5035 20.0 500 57.3014 0.835 0.2982 1.3501 0.835 0.8175 0.1442 0.0549
57.5035 21.0 525 57.3792 0.82 0.3206 1.4779 0.82 0.7957 0.1698 0.0568
57.5035 22.0 550 57.6968 0.795 0.3627 1.8539 0.795 0.7468 0.1809 0.0698
57.5035 23.0 575 57.4539 0.8 0.3465 1.4210 0.8000 0.7787 0.1736 0.0776
57.5035 24.0 600 57.1479 0.815 0.2998 1.3434 0.815 0.7989 0.1513 0.0607
57.5035 25.0 625 57.3390 0.79 0.3482 1.2595 0.79 0.7803 0.1635 0.0652
57.5035 26.0 650 57.4046 0.82 0.3130 1.5825 0.82 0.8060 0.1495 0.0692
57.5035 27.0 675 57.1398 0.835 0.2643 1.5441 0.835 0.8185 0.1317 0.0485
57.5035 28.0 700 57.4322 0.82 0.3217 1.5260 0.82 0.7912 0.1576 0.0643
57.5035 29.0 725 57.1362 0.87 0.2291 1.3903 0.87 0.8621 0.1104 0.0539
57.5035 30.0 750 57.1131 0.855 0.2511 1.1423 0.855 0.8451 0.1292 0.0492
57.5035 31.0 775 56.8690 0.845 0.2454 1.2822 0.845 0.8265 0.1254 0.0473
57.5035 32.0 800 56.8384 0.855 0.2220 1.2243 0.855 0.8453 0.1119 0.0382
57.5035 33.0 825 56.9461 0.855 0.2450 1.2192 0.855 0.8537 0.1276 0.0395
57.5035 34.0 850 56.9061 0.85 0.2450 1.2097 0.85 0.8337 0.1216 0.0408
57.5035 35.0 875 56.9100 0.86 0.2413 1.2197 0.8600 0.8546 0.1189 0.0387
57.5035 36.0 900 56.9087 0.855 0.2444 1.2098 0.855 0.8460 0.1281 0.0379
57.5035 37.0 925 56.8923 0.86 0.2438 1.2156 0.8600 0.8509 0.1259 0.0378
57.5035 38.0 950 56.8908 0.85 0.2450 1.2187 0.85 0.8397 0.1236 0.0390
57.5035 39.0 975 56.8591 0.855 0.2404 1.2063 0.855 0.8411 0.1326 0.0383
56.2493 40.0 1000 56.8479 0.86 0.2352 1.2142 0.8600 0.8539 0.1257 0.0386
56.2493 41.0 1025 56.8762 0.86 0.2365 1.2166 0.8600 0.8492 0.1171 0.0383
56.2493 42.0 1050 56.8551 0.865 0.2321 1.2078 0.865 0.8547 0.1183 0.0383
56.2493 43.0 1075 56.8913 0.87 0.2360 1.2013 0.87 0.8617 0.1187 0.0410
56.2493 44.0 1100 56.8523 0.86 0.2359 1.2094 0.8600 0.8506 0.1214 0.0399
56.2493 45.0 1125 56.8546 0.87 0.2330 1.2028 0.87 0.8650 0.1233 0.0384
56.2493 46.0 1150 56.8536 0.865 0.2323 1.2099 0.865 0.8579 0.1230 0.0389
56.2493 47.0 1175 56.8490 0.865 0.2346 1.2095 0.865 0.8580 0.1139 0.0411
56.2493 48.0 1200 56.8569 0.88 0.2295 1.1277 0.88 0.8693 0.1238 0.0381
56.2493 49.0 1225 56.8528 0.875 0.2292 1.1966 0.875 0.8681 0.1264 0.0394
56.2493 50.0 1250 56.8462 0.875 0.2309 1.1215 0.875 0.8690 0.1178 0.0424
56.2493 51.0 1275 56.8438 0.87 0.2285 1.1259 0.87 0.8631 0.1304 0.0404
56.2493 52.0 1300 56.8660 0.865 0.2334 1.1231 0.865 0.8623 0.1343 0.0416
56.2493 53.0 1325 56.8802 0.885 0.2273 1.1220 0.885 0.8784 0.1202 0.0415
56.2493 54.0 1350 56.8581 0.885 0.2261 1.1938 0.885 0.8772 0.1286 0.0408
56.2493 55.0 1375 56.8348 0.875 0.2301 1.1953 0.875 0.8675 0.1267 0.0404
56.2493 56.0 1400 56.8489 0.87 0.2336 1.1974 0.87 0.8589 0.1079 0.0393
56.2493 57.0 1425 56.8508 0.87 0.2307 1.1928 0.87 0.8648 0.1143 0.0399
56.2493 58.0 1450 56.8172 0.875 0.2198 1.2030 0.875 0.8675 0.1062 0.0378
56.2493 59.0 1475 56.8662 0.87 0.2287 1.1354 0.87 0.8659 0.1198 0.0410
56.0552 60.0 1500 56.8437 0.88 0.2241 1.1968 0.88 0.8735 0.1127 0.0407
56.0552 61.0 1525 56.8468 0.87 0.2303 1.1998 0.87 0.8648 0.1170 0.0428
56.0552 62.0 1550 56.8575 0.865 0.2299 1.1940 0.865 0.8599 0.1171 0.0411
56.0552 63.0 1575 56.8451 0.875 0.2291 1.1981 0.875 0.8697 0.1225 0.0395
56.0552 64.0 1600 56.8355 0.875 0.2255 1.2009 0.875 0.8675 0.1137 0.0394
56.0552 65.0 1625 56.8490 0.875 0.2338 1.2653 0.875 0.8697 0.1259 0.0413
56.0552 66.0 1650 56.8206 0.87 0.2271 1.2860 0.87 0.8603 0.1197 0.0379
56.0552 67.0 1675 56.8592 0.87 0.2307 1.1992 0.87 0.8636 0.1210 0.0408
56.0552 68.0 1700 56.8339 0.865 0.2290 1.1968 0.865 0.8599 0.1101 0.0386
56.0552 69.0 1725 56.8533 0.87 0.2336 1.2625 0.87 0.8636 0.1154 0.0406
56.0552 70.0 1750 56.8281 0.87 0.2328 1.2012 0.87 0.8659 0.1229 0.0406
56.0552 71.0 1775 56.8431 0.875 0.2335 1.2557 0.875 0.8697 0.1318 0.0398
56.0552 72.0 1800 56.8396 0.865 0.2321 1.2659 0.865 0.8599 0.1165 0.0397
56.0552 73.0 1825 56.8229 0.86 0.2302 1.2615 0.8600 0.8524 0.1258 0.0402
56.0552 74.0 1850 56.8445 0.87 0.2344 1.2371 0.87 0.8659 0.1202 0.0393
56.0552 75.0 1875 56.8475 0.865 0.2341 1.2660 0.865 0.8599 0.1202 0.0423
56.0552 76.0 1900 56.8338 0.86 0.2320 1.2643 0.8600 0.8524 0.1296 0.0422
56.0552 77.0 1925 56.8481 0.87 0.2353 1.2665 0.87 0.8659 0.1266 0.0426
56.0552 78.0 1950 56.8328 0.865 0.2323 1.2584 0.865 0.8599 0.1128 0.0424
56.0552 79.0 1975 56.8382 0.86 0.2363 1.2658 0.8600 0.8553 0.1273 0.0425
55.9822 80.0 2000 56.8260 0.86 0.2354 1.2710 0.8600 0.8553 0.1129 0.0430
55.9822 81.0 2025 56.8474 0.86 0.2398 1.2679 0.8600 0.8553 0.1212 0.0433
55.9822 82.0 2050 56.8105 0.855 0.2320 1.2655 0.855 0.8478 0.1269 0.0423
55.9822 83.0 2075 56.8240 0.86 0.2347 1.2651 0.8600 0.8524 0.1312 0.0425
55.9822 84.0 2100 56.8350 0.86 0.2353 1.2690 0.8600 0.8553 0.1225 0.0435
55.9822 85.0 2125 56.8317 0.855 0.2371 1.2674 0.855 0.8478 0.1211 0.0433
55.9822 86.0 2150 56.8270 0.855 0.2364 1.2646 0.855 0.8478 0.1270 0.0433
55.9822 87.0 2175 56.8275 0.855 0.2359 1.2660 0.855 0.8478 0.1167 0.0423
55.9822 88.0 2200 56.8426 0.855 0.2385 1.2683 0.855 0.8478 0.1239 0.0428
55.9822 89.0 2225 56.8376 0.855 0.2368 1.2676 0.855 0.8478 0.1239 0.0426
55.9822 90.0 2250 56.8358 0.855 0.2382 1.2670 0.855 0.8451 0.1213 0.0435
55.9822 91.0 2275 56.8254 0.86 0.2374 1.2687 0.8600 0.8536 0.1308 0.0432
55.9822 92.0 2300 56.8269 0.855 0.2359 1.2684 0.855 0.8476 0.1223 0.0425
55.9822 93.0 2325 56.8324 0.85 0.2381 1.2708 0.85 0.8414 0.1224 0.0432
55.9822 94.0 2350 56.8344 0.85 0.2384 1.2682 0.85 0.8414 0.1222 0.0433
55.9822 95.0 2375 56.8344 0.85 0.2387 1.2708 0.85 0.8414 0.1228 0.0434
55.9822 96.0 2400 56.8342 0.85 0.2389 1.2687 0.85 0.8414 0.1222 0.0432
55.9822 97.0 2425 56.8339 0.85 0.2387 1.2713 0.85 0.8414 0.1222 0.0433
55.9822 98.0 2450 56.8342 0.85 0.2393 1.2708 0.85 0.8414 0.1228 0.0437
55.9822 99.0 2475 56.8325 0.85 0.2390 1.2703 0.85 0.8414 0.1228 0.0436
55.9517 100.0 2500 56.8340 0.85 0.2391 1.2700 0.85 0.8414 0.1228 0.0436

Framework versions