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81-tiny_tobacco3482_og_simkd
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: 230.0462
- Accuracy: 0.845
- Brier Loss: 0.2451
- Nll: 1.1250
- F1 Micro: 0.845
- F1 Macro: 0.8350
- Ece: 0.1115
- Aurc: 0.0383
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: 16
- eval_batch_size: 16
- 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 | 50 | 238.2967 | 0.275 | 0.8789 | 6.2995 | 0.275 | 0.1849 | 0.2898 | 0.4790 |
| No log | 2.0 | 100 | 236.7866 | 0.41 | 0.7214 | 3.0130 | 0.41 | 0.2599 | 0.2544 | 0.3985 |
| No log | 3.0 | 150 | 235.3687 | 0.59 | 0.5690 | 2.4483 | 0.59 | 0.4507 | 0.2464 | 0.2336 |
| No log | 4.0 | 200 | 234.7639 | 0.65 | 0.4658 | 2.3318 | 0.65 | 0.4996 | 0.2365 | 0.1474 |
| No log | 5.0 | 250 | 234.0798 | 0.675 | 0.4692 | 2.3351 | 0.675 | 0.5158 | 0.2359 | 0.1335 |
| No log | 6.0 | 300 | 234.2002 | 0.68 | 0.4267 | 2.1570 | 0.68 | 0.5724 | 0.1990 | 0.1124 |
| No log | 7.0 | 350 | 234.1154 | 0.665 | 0.4874 | 2.9269 | 0.665 | 0.5631 | 0.2249 | 0.1259 |
| No log | 8.0 | 400 | 233.2390 | 0.77 | 0.3224 | 1.8874 | 0.7700 | 0.6850 | 0.1754 | 0.0695 |
| No log | 9.0 | 450 | 233.1396 | 0.755 | 0.3583 | 2.1139 | 0.755 | 0.7060 | 0.1573 | 0.0802 |
| 234.3515 | 10.0 | 500 | 233.5895 | 0.705 | 0.4653 | 3.2740 | 0.705 | 0.6813 | 0.2183 | 0.1180 |
| 234.3515 | 11.0 | 550 | 233.0481 | 0.745 | 0.3803 | 2.7330 | 0.745 | 0.6697 | 0.1730 | 0.0936 |
| 234.3515 | 12.0 | 600 | 232.9339 | 0.78 | 0.3319 | 1.8094 | 0.78 | 0.7416 | 0.1700 | 0.0660 |
| 234.3515 | 13.0 | 650 | 233.0181 | 0.755 | 0.3182 | 1.9630 | 0.755 | 0.7596 | 0.1772 | 0.0823 |
| 234.3515 | 14.0 | 700 | 232.4934 | 0.815 | 0.2659 | 1.3869 | 0.815 | 0.7749 | 0.1512 | 0.0511 |
| 234.3515 | 15.0 | 750 | 232.6922 | 0.79 | 0.3361 | 1.8793 | 0.79 | 0.7671 | 0.1633 | 0.0926 |
| 234.3515 | 16.0 | 800 | 232.3391 | 0.815 | 0.2785 | 1.5488 | 0.815 | 0.8038 | 0.1476 | 0.0549 |
| 234.3515 | 17.0 | 850 | 232.5412 | 0.775 | 0.3100 | 2.0192 | 0.775 | 0.7675 | 0.1617 | 0.0502 |
| 234.3515 | 18.0 | 900 | 232.5307 | 0.785 | 0.3211 | 1.6793 | 0.785 | 0.7541 | 0.1679 | 0.0676 |
| 234.3515 | 19.0 | 950 | 232.3055 | 0.825 | 0.2862 | 1.5993 | 0.825 | 0.8204 | 0.1443 | 0.0620 |
| 231.365 | 20.0 | 1000 | 232.5636 | 0.78 | 0.3431 | 2.6048 | 0.78 | 0.7835 | 0.1658 | 0.0847 |
| 231.365 | 21.0 | 1050 | 231.8748 | 0.845 | 0.2737 | 1.4332 | 0.845 | 0.8454 | 0.1616 | 0.0602 |
| 231.365 | 22.0 | 1100 | 232.1032 | 0.825 | 0.2557 | 1.6240 | 0.825 | 0.8290 | 0.1422 | 0.0442 |
| 231.365 | 23.0 | 1150 | 231.7278 | 0.835 | 0.2740 | 1.6260 | 0.835 | 0.8246 | 0.1541 | 0.0613 |
| 231.365 | 24.0 | 1200 | 231.9350 | 0.84 | 0.2636 | 1.6028 | 0.8400 | 0.8410 | 0.1472 | 0.0471 |
| 231.365 | 25.0 | 1250 | 231.6054 | 0.82 | 0.2753 | 1.3835 | 0.82 | 0.8090 | 0.1526 | 0.0478 |
| 231.365 | 26.0 | 1300 | 231.6516 | 0.84 | 0.2737 | 1.3849 | 0.8400 | 0.8354 | 0.1492 | 0.0543 |
| 231.365 | 27.0 | 1350 | 231.5453 | 0.84 | 0.2536 | 1.1384 | 0.8400 | 0.8265 | 0.1363 | 0.0431 |
| 231.365 | 28.0 | 1400 | 231.4833 | 0.85 | 0.2292 | 1.1206 | 0.85 | 0.8350 | 0.1250 | 0.0362 |
| 231.365 | 29.0 | 1450 | 231.3722 | 0.815 | 0.2856 | 1.1706 | 0.815 | 0.8038 | 0.1606 | 0.0486 |
| 230.3328 | 30.0 | 1500 | 231.3517 | 0.84 | 0.2608 | 1.3387 | 0.8400 | 0.8382 | 0.1366 | 0.0483 |
| 230.3328 | 31.0 | 1550 | 231.3705 | 0.815 | 0.2724 | 1.2558 | 0.815 | 0.7992 | 0.1448 | 0.0463 |
| 230.3328 | 32.0 | 1600 | 231.4319 | 0.84 | 0.2588 | 1.0691 | 0.8400 | 0.8301 | 0.1317 | 0.0435 |
| 230.3328 | 33.0 | 1650 | 231.2119 | 0.86 | 0.2323 | 1.1693 | 0.8600 | 0.8609 | 0.1229 | 0.0470 |
| 230.3328 | 34.0 | 1700 | 231.2836 | 0.83 | 0.2477 | 1.1294 | 0.83 | 0.8201 | 0.1398 | 0.0406 |
| 230.3328 | 35.0 | 1750 | 231.2669 | 0.845 | 0.2569 | 1.1508 | 0.845 | 0.8369 | 0.1357 | 0.0449 |
| 230.3328 | 36.0 | 1800 | 231.0634 | 0.85 | 0.2422 | 1.0830 | 0.85 | 0.8404 | 0.1372 | 0.0419 |
| 230.3328 | 37.0 | 1850 | 231.1141 | 0.85 | 0.2398 | 1.0879 | 0.85 | 0.8455 | 0.1347 | 0.0437 |
| 230.3328 | 38.0 | 1900 | 231.0520 | 0.815 | 0.2626 | 1.2325 | 0.815 | 0.8077 | 0.1304 | 0.0478 |
| 230.3328 | 39.0 | 1950 | 230.9089 | 0.83 | 0.2507 | 1.1245 | 0.83 | 0.8258 | 0.1347 | 0.0487 |
| 229.6409 | 40.0 | 2000 | 231.0532 | 0.86 | 0.2207 | 1.1258 | 0.8600 | 0.8464 | 0.1206 | 0.0428 |
| 229.6409 | 41.0 | 2050 | 230.9307 | 0.855 | 0.2350 | 1.1326 | 0.855 | 0.8498 | 0.1284 | 0.0401 |
| 229.6409 | 42.0 | 2100 | 230.8493 | 0.86 | 0.2306 | 1.1075 | 0.8600 | 0.8548 | 0.1441 | 0.0417 |
| 229.6409 | 43.0 | 2150 | 230.7516 | 0.87 | 0.2198 | 1.0312 | 0.87 | 0.8587 | 0.1184 | 0.0404 |
| 229.6409 | 44.0 | 2200 | 230.8540 | 0.85 | 0.2485 | 1.1724 | 0.85 | 0.8444 | 0.1425 | 0.0451 |
| 229.6409 | 45.0 | 2250 | 230.7995 | 0.86 | 0.2284 | 1.1183 | 0.8600 | 0.8490 | 0.1284 | 0.0368 |
| 229.6409 | 46.0 | 2300 | 230.7162 | 0.825 | 0.2701 | 1.1206 | 0.825 | 0.8159 | 0.1390 | 0.0437 |
| 229.6409 | 47.0 | 2350 | 230.5593 | 0.855 | 0.2341 | 1.2242 | 0.855 | 0.8459 | 0.1226 | 0.0392 |
| 229.6409 | 48.0 | 2400 | 230.6472 | 0.86 | 0.2377 | 1.0233 | 0.8600 | 0.8558 | 0.1319 | 0.0354 |
| 229.6409 | 49.0 | 2450 | 230.7080 | 0.84 | 0.2548 | 1.1208 | 0.8400 | 0.8294 | 0.1484 | 0.0426 |
| 229.142 | 50.0 | 2500 | 230.5862 | 0.845 | 0.2543 | 1.2129 | 0.845 | 0.8322 | 0.1358 | 0.0415 |
| 229.142 | 51.0 | 2550 | 230.6550 | 0.845 | 0.2462 | 1.0937 | 0.845 | 0.8333 | 0.1306 | 0.0411 |
| 229.142 | 52.0 | 2600 | 230.5789 | 0.835 | 0.2595 | 1.1393 | 0.835 | 0.8249 | 0.1369 | 0.0428 |
| 229.142 | 53.0 | 2650 | 230.5895 | 0.85 | 0.2519 | 1.0185 | 0.85 | 0.8447 | 0.1263 | 0.0439 |
| 229.142 | 54.0 | 2700 | 230.4955 | 0.86 | 0.2402 | 1.0837 | 0.8600 | 0.8590 | 0.1382 | 0.0394 |
| 229.142 | 55.0 | 2750 | 230.4579 | 0.84 | 0.2560 | 1.1514 | 0.8400 | 0.8312 | 0.1439 | 0.0431 |
| 229.142 | 56.0 | 2800 | 230.5190 | 0.845 | 0.2527 | 1.2868 | 0.845 | 0.8334 | 0.1342 | 0.0406 |
| 229.142 | 57.0 | 2850 | 230.4989 | 0.84 | 0.2536 | 1.0785 | 0.8400 | 0.8278 | 0.1377 | 0.0397 |
| 229.142 | 58.0 | 2900 | 230.4445 | 0.84 | 0.2416 | 1.2104 | 0.8400 | 0.8340 | 0.1339 | 0.0383 |
| 229.142 | 59.0 | 2950 | 230.3159 | 0.87 | 0.2211 | 1.1138 | 0.87 | 0.8630 | 0.1171 | 0.0394 |
| 228.7442 | 60.0 | 3000 | 230.3405 | 0.835 | 0.2603 | 1.1327 | 0.835 | 0.8273 | 0.1422 | 0.0416 |
| 228.7442 | 61.0 | 3050 | 230.3892 | 0.845 | 0.2395 | 1.1619 | 0.845 | 0.8308 | 0.1263 | 0.0377 |
| 228.7442 | 62.0 | 3100 | 230.3728 | 0.84 | 0.2478 | 1.0053 | 0.8400 | 0.8291 | 0.1208 | 0.0389 |
| 228.7442 | 63.0 | 3150 | 230.2486 | 0.845 | 0.2545 | 1.1989 | 0.845 | 0.8438 | 0.1364 | 0.0434 |
| 228.7442 | 64.0 | 3200 | 230.2353 | 0.84 | 0.2512 | 1.1260 | 0.8400 | 0.8330 | 0.1191 | 0.0430 |
| 228.7442 | 65.0 | 3250 | 230.2041 | 0.845 | 0.2429 | 1.1529 | 0.845 | 0.8384 | 0.1343 | 0.0401 |
| 228.7442 | 66.0 | 3300 | 230.2439 | 0.845 | 0.2511 | 1.1125 | 0.845 | 0.8366 | 0.1367 | 0.0430 |
| 228.7442 | 67.0 | 3350 | 230.1510 | 0.85 | 0.2471 | 1.0528 | 0.85 | 0.8457 | 0.1414 | 0.0402 |
| 228.7442 | 68.0 | 3400 | 230.2274 | 0.85 | 0.2455 | 1.1150 | 0.85 | 0.8397 | 0.1311 | 0.0427 |
| 228.7442 | 69.0 | 3450 | 230.2165 | 0.845 | 0.2524 | 1.0517 | 0.845 | 0.8421 | 0.1312 | 0.0410 |
| 228.4757 | 70.0 | 3500 | 230.1976 | 0.835 | 0.2600 | 1.0845 | 0.835 | 0.8258 | 0.1353 | 0.0410 |
| 228.4757 | 71.0 | 3550 | 230.1062 | 0.85 | 0.2487 | 1.1447 | 0.85 | 0.8410 | 0.1297 | 0.0427 |
| 228.4757 | 72.0 | 3600 | 229.9867 | 0.835 | 0.2584 | 1.0641 | 0.835 | 0.8273 | 0.1236 | 0.0440 |
| 228.4757 | 73.0 | 3650 | 230.1918 | 0.845 | 0.2411 | 1.1521 | 0.845 | 0.8363 | 0.1373 | 0.0389 |
| 228.4757 | 74.0 | 3700 | 230.0781 | 0.85 | 0.2524 | 1.0980 | 0.85 | 0.8390 | 0.1298 | 0.0409 |
| 228.4757 | 75.0 | 3750 | 230.1432 | 0.835 | 0.2554 | 1.0967 | 0.835 | 0.8230 | 0.1227 | 0.0407 |
| 228.4757 | 76.0 | 3800 | 230.1512 | 0.84 | 0.2535 | 1.0945 | 0.8400 | 0.8295 | 0.1321 | 0.0422 |
| 228.4757 | 77.0 | 3850 | 230.0682 | 0.84 | 0.2502 | 1.0301 | 0.8400 | 0.8370 | 0.1312 | 0.0403 |
| 228.4757 | 78.0 | 3900 | 230.0357 | 0.835 | 0.2521 | 1.1572 | 0.835 | 0.8293 | 0.1244 | 0.0412 |
| 228.4757 | 79.0 | 3950 | 230.1252 | 0.845 | 0.2509 | 1.0961 | 0.845 | 0.8381 | 0.1273 | 0.0409 |
| 228.2815 | 80.0 | 4000 | 230.0584 | 0.845 | 0.2539 | 1.0795 | 0.845 | 0.8363 | 0.1235 | 0.0432 |
| 228.2815 | 81.0 | 4050 | 229.9967 | 0.85 | 0.2427 | 1.1156 | 0.85 | 0.8382 | 0.1184 | 0.0394 |
| 228.2815 | 82.0 | 4100 | 230.0755 | 0.84 | 0.2563 | 1.0833 | 0.8400 | 0.8302 | 0.1295 | 0.0406 |
| 228.2815 | 83.0 | 4150 | 230.0798 | 0.845 | 0.2477 | 1.1713 | 0.845 | 0.8385 | 0.1259 | 0.0427 |
| 228.2815 | 84.0 | 4200 | 230.0299 | 0.84 | 0.2477 | 1.0907 | 0.8400 | 0.8260 | 0.1213 | 0.0383 |
| 228.2815 | 85.0 | 4250 | 230.0568 | 0.845 | 0.2483 | 1.0763 | 0.845 | 0.8350 | 0.1238 | 0.0409 |
| 228.2815 | 86.0 | 4300 | 230.0743 | 0.85 | 0.2464 | 1.0549 | 0.85 | 0.8418 | 0.1271 | 0.0398 |
| 228.2815 | 87.0 | 4350 | 230.0061 | 0.845 | 0.2505 | 1.1585 | 0.845 | 0.8350 | 0.1312 | 0.0375 |
| 228.2815 | 88.0 | 4400 | 229.9674 | 0.845 | 0.2478 | 1.0763 | 0.845 | 0.8346 | 0.1394 | 0.0410 |
| 228.2815 | 89.0 | 4450 | 229.9697 | 0.85 | 0.2451 | 1.0833 | 0.85 | 0.8406 | 0.1324 | 0.0364 |
| 228.1298 | 90.0 | 4500 | 230.0305 | 0.845 | 0.2496 | 1.1008 | 0.845 | 0.8350 | 0.1308 | 0.0395 |
| 228.1298 | 91.0 | 4550 | 229.9740 | 0.845 | 0.2495 | 1.0605 | 0.845 | 0.8350 | 0.1309 | 0.0413 |
| 228.1298 | 92.0 | 4600 | 229.9962 | 0.85 | 0.2497 | 1.1193 | 0.85 | 0.8408 | 0.1294 | 0.0399 |
| 228.1298 | 93.0 | 4650 | 229.9740 | 0.85 | 0.2491 | 1.0496 | 0.85 | 0.8383 | 0.1270 | 0.0390 |
| 228.1298 | 94.0 | 4700 | 229.9698 | 0.84 | 0.2516 | 1.0644 | 0.8400 | 0.8295 | 0.1430 | 0.0398 |
| 228.1298 | 95.0 | 4750 | 229.9247 | 0.845 | 0.2516 | 1.1705 | 0.845 | 0.8350 | 0.1227 | 0.0371 |
| 228.1298 | 96.0 | 4800 | 230.0451 | 0.84 | 0.2507 | 1.0970 | 0.8400 | 0.8285 | 0.1368 | 0.0391 |
| 228.1298 | 97.0 | 4850 | 229.9402 | 0.85 | 0.2495 | 1.1427 | 0.85 | 0.8430 | 0.1379 | 0.0413 |
| 228.1298 | 98.0 | 4900 | 230.0130 | 0.84 | 0.2532 | 1.0964 | 0.8400 | 0.8285 | 0.1412 | 0.0389 |
| 228.1298 | 99.0 | 4950 | 230.0200 | 0.845 | 0.2482 | 1.0916 | 0.845 | 0.8317 | 0.1190 | 0.0392 |
| 228.0583 | 100.0 | 5000 | 230.0462 | 0.845 | 0.2451 | 1.1250 | 0.845 | 0.8350 | 0.1115 | 0.0383 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
