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39-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:
- Loss: 65.8239
- Accuracy: 0.84
- Brier Loss: 0.2807
- Nll: 1.1327
- F1 Micro: 0.8400
- F1 Macro: 0.8280
- Ece: 0.1437
- Aurc: 0.0472
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:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Brier Loss | Nll | F1 Micro | F1 Macro | Ece | Aurc |
|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 25 | 69.1264 | 0.26 | 0.8707 | 4.9002 | 0.26 | 0.1920 | 0.3064 | 0.7815 |
| No log | 2.0 | 50 | 68.3319 | 0.545 | 0.5960 | 2.8558 | 0.545 | 0.4562 | 0.2850 | 0.2564 |
| No log | 3.0 | 75 | 67.8627 | 0.68 | 0.4406 | 1.6064 | 0.68 | 0.6157 | 0.2543 | 0.1333 |
| No log | 4.0 | 100 | 67.5797 | 0.75 | 0.3829 | 1.5484 | 0.75 | 0.7343 | 0.2220 | 0.1152 |
| No log | 5.0 | 125 | 67.2608 | 0.8 | 0.3072 | 1.7491 | 0.8000 | 0.7573 | 0.1809 | 0.0698 |
| No log | 6.0 | 150 | 67.0950 | 0.78 | 0.3169 | 1.7708 | 0.78 | 0.7441 | 0.1576 | 0.0607 |
| No log | 7.0 | 175 | 66.9178 | 0.755 | 0.3812 | 1.6929 | 0.755 | 0.6848 | 0.1899 | 0.1043 |
| No log | 8.0 | 200 | 66.7335 | 0.75 | 0.3763 | 1.7649 | 0.75 | 0.7399 | 0.1870 | 0.0806 |
| No log | 9.0 | 225 | 66.4371 | 0.805 | 0.3036 | 1.4686 | 0.805 | 0.7896 | 0.1378 | 0.0545 |
| No log | 10.0 | 250 | 66.6823 | 0.75 | 0.3924 | 1.8808 | 0.75 | 0.6665 | 0.1964 | 0.0829 |
| No log | 11.0 | 275 | 66.6079 | 0.775 | 0.3570 | 1.8872 | 0.775 | 0.7442 | 0.1811 | 0.0839 |
| No log | 12.0 | 300 | 66.4364 | 0.765 | 0.3689 | 1.6981 | 0.765 | 0.7550 | 0.1909 | 0.0732 |
| No log | 13.0 | 325 | 66.1317 | 0.785 | 0.3346 | 1.4062 | 0.785 | 0.7823 | 0.1753 | 0.0572 |
| No log | 14.0 | 350 | 66.5182 | 0.73 | 0.4453 | 1.4431 | 0.7300 | 0.7208 | 0.2310 | 0.0985 |
| No log | 15.0 | 375 | 66.5154 | 0.775 | 0.3769 | 1.4897 | 0.775 | 0.7398 | 0.1875 | 0.0821 |
| No log | 16.0 | 400 | 66.4191 | 0.8 | 0.3315 | 1.5327 | 0.8000 | 0.7771 | 0.1651 | 0.0685 |
| No log | 17.0 | 425 | 66.2374 | 0.765 | 0.3520 | 1.5388 | 0.765 | 0.7401 | 0.1767 | 0.0760 |
| No log | 18.0 | 450 | 66.2010 | 0.805 | 0.3320 | 1.4280 | 0.805 | 0.7721 | 0.1756 | 0.0684 |
| No log | 19.0 | 475 | 66.0335 | 0.85 | 0.2625 | 1.3549 | 0.85 | 0.8352 | 0.1431 | 0.0430 |
| 65.4034 | 20.0 | 500 | 66.2213 | 0.815 | 0.3213 | 1.3912 | 0.815 | 0.7955 | 0.1645 | 0.0579 |
| 65.4034 | 21.0 | 525 | 66.2647 | 0.77 | 0.3656 | 1.3241 | 0.7700 | 0.7743 | 0.1899 | 0.0755 |
| 65.4034 | 22.0 | 550 | 66.1220 | 0.86 | 0.2684 | 1.2459 | 0.8600 | 0.8354 | 0.1327 | 0.0473 |
| 65.4034 | 23.0 | 575 | 66.1615 | 0.85 | 0.2623 | 1.3400 | 0.85 | 0.8231 | 0.1291 | 0.0448 |
| 65.4034 | 24.0 | 600 | 66.2114 | 0.825 | 0.3130 | 1.4118 | 0.825 | 0.8122 | 0.1565 | 0.0498 |
| 65.4034 | 25.0 | 625 | 66.1048 | 0.835 | 0.2704 | 1.3571 | 0.835 | 0.8196 | 0.1405 | 0.0450 |
| 65.4034 | 26.0 | 650 | 65.9832 | 0.825 | 0.2990 | 1.1514 | 0.825 | 0.8253 | 0.1603 | 0.0423 |
| 65.4034 | 27.0 | 675 | 66.2567 | 0.805 | 0.3307 | 1.3509 | 0.805 | 0.8022 | 0.1699 | 0.0634 |
| 65.4034 | 28.0 | 700 | 66.0668 | 0.82 | 0.3172 | 1.1445 | 0.82 | 0.7973 | 0.1538 | 0.0419 |
| 65.4034 | 29.0 | 725 | 66.2254 | 0.81 | 0.3252 | 1.3290 | 0.81 | 0.8011 | 0.1659 | 0.0523 |
| 65.4034 | 30.0 | 750 | 65.9643 | 0.84 | 0.2697 | 1.2052 | 0.8400 | 0.8245 | 0.1319 | 0.0425 |
| 65.4034 | 31.0 | 775 | 66.3419 | 0.81 | 0.3249 | 1.2772 | 0.81 | 0.7969 | 0.1700 | 0.0612 |
| 65.4034 | 32.0 | 800 | 66.0324 | 0.825 | 0.3003 | 1.3138 | 0.825 | 0.8000 | 0.1584 | 0.0445 |
| 65.4034 | 33.0 | 825 | 66.3326 | 0.82 | 0.3336 | 1.2983 | 0.82 | 0.7826 | 0.1754 | 0.0590 |
| 65.4034 | 34.0 | 850 | 66.1374 | 0.825 | 0.3061 | 1.5645 | 0.825 | 0.8012 | 0.1500 | 0.0459 |
| 65.4034 | 35.0 | 875 | 66.2310 | 0.815 | 0.3207 | 1.5607 | 0.815 | 0.7939 | 0.1712 | 0.0646 |
| 65.4034 | 36.0 | 900 | 66.0388 | 0.84 | 0.2873 | 1.1966 | 0.8400 | 0.8327 | 0.1456 | 0.0585 |
| 65.4034 | 37.0 | 925 | 66.0520 | 0.835 | 0.2958 | 1.2728 | 0.835 | 0.8180 | 0.1508 | 0.0477 |
| 65.4034 | 38.0 | 950 | 65.9916 | 0.84 | 0.2783 | 1.1635 | 0.8400 | 0.8233 | 0.1398 | 0.0438 |
| 65.4034 | 39.0 | 975 | 65.9391 | 0.845 | 0.2743 | 1.2660 | 0.845 | 0.8289 | 0.1396 | 0.0458 |
| 64.0802 | 40.0 | 1000 | 65.9291 | 0.845 | 0.2762 | 1.3335 | 0.845 | 0.8259 | 0.1373 | 0.0430 |
| 64.0802 | 41.0 | 1025 | 65.8559 | 0.85 | 0.2686 | 1.3432 | 0.85 | 0.8338 | 0.1345 | 0.0428 |
| 64.0802 | 42.0 | 1050 | 65.8612 | 0.845 | 0.2772 | 1.2679 | 0.845 | 0.8255 | 0.1389 | 0.0431 |
| 64.0802 | 43.0 | 1075 | 65.8953 | 0.84 | 0.2742 | 1.2614 | 0.8400 | 0.8227 | 0.1408 | 0.0435 |
| 64.0802 | 44.0 | 1100 | 65.8569 | 0.835 | 0.2769 | 1.2730 | 0.835 | 0.8199 | 0.1426 | 0.0432 |
| 64.0802 | 45.0 | 1125 | 65.8610 | 0.84 | 0.2769 | 1.2622 | 0.8400 | 0.8248 | 0.1485 | 0.0425 |
| 64.0802 | 46.0 | 1150 | 65.8237 | 0.845 | 0.2729 | 1.1920 | 0.845 | 0.8334 | 0.1462 | 0.0432 |
| 64.0802 | 47.0 | 1175 | 65.8416 | 0.845 | 0.2785 | 1.1826 | 0.845 | 0.8317 | 0.1376 | 0.0431 |
| 64.0802 | 48.0 | 1200 | 65.8452 | 0.845 | 0.2817 | 1.1876 | 0.845 | 0.8317 | 0.1417 | 0.0441 |
| 64.0802 | 49.0 | 1225 | 65.8394 | 0.845 | 0.2750 | 1.1993 | 0.845 | 0.8309 | 0.1315 | 0.0419 |
| 64.0802 | 50.0 | 1250 | 65.8527 | 0.84 | 0.2796 | 1.1860 | 0.8400 | 0.8279 | 0.1410 | 0.0432 |
| 64.0802 | 51.0 | 1275 | 65.8286 | 0.845 | 0.2749 | 1.1977 | 0.845 | 0.8333 | 0.1444 | 0.0428 |
| 64.0802 | 52.0 | 1300 | 65.8296 | 0.83 | 0.2779 | 1.1926 | 0.83 | 0.8171 | 0.1382 | 0.0435 |
| 64.0802 | 53.0 | 1325 | 65.8121 | 0.83 | 0.2779 | 1.1955 | 0.83 | 0.8155 | 0.1387 | 0.0436 |
| 64.0802 | 54.0 | 1350 | 65.8361 | 0.825 | 0.2769 | 1.1909 | 0.825 | 0.8095 | 0.1435 | 0.0419 |
| 64.0802 | 55.0 | 1375 | 65.8370 | 0.83 | 0.2816 | 1.1925 | 0.83 | 0.8171 | 0.1416 | 0.0435 |
| 64.0802 | 56.0 | 1400 | 65.8301 | 0.825 | 0.2763 | 1.1908 | 0.825 | 0.8101 | 0.1393 | 0.0439 |
| 64.0802 | 57.0 | 1425 | 65.8301 | 0.82 | 0.2791 | 1.1881 | 0.82 | 0.8040 | 0.1443 | 0.0440 |
| 64.0802 | 58.0 | 1450 | 65.8324 | 0.83 | 0.2754 | 1.1938 | 0.83 | 0.8198 | 0.1387 | 0.0460 |
| 64.0802 | 59.0 | 1475 | 65.8407 | 0.825 | 0.2818 | 1.1893 | 0.825 | 0.8138 | 0.1393 | 0.0439 |
| 63.8765 | 60.0 | 1500 | 65.8236 | 0.84 | 0.2782 | 1.1871 | 0.8400 | 0.8290 | 0.1512 | 0.0449 |
| 63.8765 | 61.0 | 1525 | 65.8198 | 0.825 | 0.2846 | 1.1752 | 0.825 | 0.8138 | 0.1505 | 0.0438 |
| 63.8765 | 62.0 | 1550 | 65.8243 | 0.83 | 0.2796 | 1.1753 | 0.83 | 0.8196 | 0.1480 | 0.0445 |
| 63.8765 | 63.0 | 1575 | 65.8495 | 0.835 | 0.2781 | 1.1766 | 0.835 | 0.8257 | 0.1353 | 0.0451 |
| 63.8765 | 64.0 | 1600 | 65.8204 | 0.835 | 0.2833 | 1.1752 | 0.835 | 0.8239 | 0.1400 | 0.0447 |
| 63.8765 | 65.0 | 1625 | 65.8374 | 0.835 | 0.2800 | 1.1829 | 0.835 | 0.8239 | 0.1474 | 0.0441 |
| 63.8765 | 66.0 | 1650 | 65.8433 | 0.83 | 0.2855 | 1.1678 | 0.83 | 0.8148 | 0.1498 | 0.0444 |
| 63.8765 | 67.0 | 1675 | 65.8259 | 0.835 | 0.2820 | 1.1725 | 0.835 | 0.8257 | 0.1518 | 0.0457 |
| 63.8765 | 68.0 | 1700 | 65.8443 | 0.83 | 0.2841 | 1.1652 | 0.83 | 0.8196 | 0.1491 | 0.0457 |
| 63.8765 | 69.0 | 1725 | 65.8255 | 0.835 | 0.2849 | 1.1620 | 0.835 | 0.8247 | 0.1499 | 0.0460 |
| 63.8765 | 70.0 | 1750 | 65.8421 | 0.83 | 0.2870 | 1.1681 | 0.83 | 0.8196 | 0.1418 | 0.0475 |
| 63.8765 | 71.0 | 1775 | 65.8402 | 0.835 | 0.2839 | 1.1614 | 0.835 | 0.8230 | 0.1359 | 0.0466 |
| 63.8765 | 72.0 | 1800 | 65.8224 | 0.84 | 0.2831 | 1.1555 | 0.8400 | 0.8280 | 0.1467 | 0.0459 |
| 63.8765 | 73.0 | 1825 | 65.8233 | 0.84 | 0.2824 | 1.1578 | 0.8400 | 0.8280 | 0.1428 | 0.0465 |
| 63.8765 | 74.0 | 1850 | 65.8299 | 0.84 | 0.2814 | 1.1574 | 0.8400 | 0.8280 | 0.1469 | 0.0465 |
| 63.8765 | 75.0 | 1875 | 65.8309 | 0.835 | 0.2790 | 1.1575 | 0.835 | 0.8219 | 0.1407 | 0.0465 |
| 63.8765 | 76.0 | 1900 | 65.8199 | 0.84 | 0.2789 | 1.1496 | 0.8400 | 0.8280 | 0.1437 | 0.0460 |
| 63.8765 | 77.0 | 1925 | 65.8222 | 0.84 | 0.2828 | 1.1520 | 0.8400 | 0.8280 | 0.1539 | 0.0461 |
| 63.8765 | 78.0 | 1950 | 65.8312 | 0.84 | 0.2801 | 1.1459 | 0.8400 | 0.8280 | 0.1354 | 0.0458 |
| 63.8765 | 79.0 | 1975 | 65.8253 | 0.84 | 0.2836 | 1.1448 | 0.8400 | 0.8280 | 0.1542 | 0.0465 |
| 63.7964 | 80.0 | 2000 | 65.8332 | 0.84 | 0.2839 | 1.1408 | 0.8400 | 0.8280 | 0.1486 | 0.0462 |
| 63.7964 | 81.0 | 2025 | 65.8316 | 0.84 | 0.2818 | 1.1419 | 0.8400 | 0.8280 | 0.1430 | 0.0460 |
| 63.7964 | 82.0 | 2050 | 65.8238 | 0.84 | 0.2824 | 1.1387 | 0.8400 | 0.8280 | 0.1411 | 0.0452 |
| 63.7964 | 83.0 | 2075 | 65.8294 | 0.84 | 0.2786 | 1.1410 | 0.8400 | 0.8280 | 0.1539 | 0.0469 |
| 63.7964 | 84.0 | 2100 | 65.8267 | 0.84 | 0.2818 | 1.1391 | 0.8400 | 0.8280 | 0.1463 | 0.0471 |
| 63.7964 | 85.0 | 2125 | 65.8222 | 0.84 | 0.2814 | 1.1401 | 0.8400 | 0.8280 | 0.1463 | 0.0470 |
| 63.7964 | 86.0 | 2150 | 65.8264 | 0.84 | 0.2776 | 1.1380 | 0.8400 | 0.8280 | 0.1359 | 0.0460 |
| 63.7964 | 87.0 | 2175 | 65.8228 | 0.84 | 0.2781 | 1.1366 | 0.8400 | 0.8280 | 0.1468 | 0.0460 |
| 63.7964 | 88.0 | 2200 | 65.8229 | 0.84 | 0.2832 | 1.1367 | 0.8400 | 0.8280 | 0.1455 | 0.0476 |
| 63.7964 | 89.0 | 2225 | 65.8271 | 0.84 | 0.2792 | 1.1376 | 0.8400 | 0.8280 | 0.1598 | 0.0467 |
| 63.7964 | 90.0 | 2250 | 65.8234 | 0.84 | 0.2830 | 1.1352 | 0.8400 | 0.8280 | 0.1427 | 0.0474 |
| 63.7964 | 91.0 | 2275 | 65.8309 | 0.84 | 0.2804 | 1.1352 | 0.8400 | 0.8280 | 0.1426 | 0.0467 |
| 63.7964 | 92.0 | 2300 | 65.8305 | 0.84 | 0.2796 | 1.1345 | 0.8400 | 0.8280 | 0.1438 | 0.0466 |
| 63.7964 | 93.0 | 2325 | 65.8155 | 0.84 | 0.2808 | 1.1347 | 0.8400 | 0.8280 | 0.1499 | 0.0471 |
| 63.7964 | 94.0 | 2350 | 65.8218 | 0.84 | 0.2803 | 1.1336 | 0.8400 | 0.8280 | 0.1487 | 0.0473 |
| 63.7964 | 95.0 | 2375 | 65.8152 | 0.84 | 0.2812 | 1.1334 | 0.8400 | 0.8280 | 0.1441 | 0.0466 |
| 63.7964 | 96.0 | 2400 | 65.8230 | 0.84 | 0.2801 | 1.1344 | 0.8400 | 0.8280 | 0.1488 | 0.0472 |
| 63.7964 | 97.0 | 2425 | 65.8206 | 0.84 | 0.2808 | 1.1328 | 0.8400 | 0.8280 | 0.1490 | 0.0472 |
| 63.7964 | 98.0 | 2450 | 65.8221 | 0.84 | 0.2807 | 1.1332 | 0.8400 | 0.8280 | 0.1438 | 0.0474 |
| 63.7964 | 99.0 | 2475 | 65.8207 | 0.84 | 0.2809 | 1.1326 | 0.8400 | 0.8280 | 0.1446 | 0.0472 |
| 63.7613 | 100.0 | 2500 | 65.8239 | 0.84 | 0.2807 | 1.1327 | 0.8400 | 0.8280 | 0.1437 | 0.0472 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
