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171-tiny_tobacco3482_kd_NKD_t1.0_g1.5
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:
- Loss: 4.3051
- Accuracy: 0.815
- Brier Loss: 0.3074
- Nll: 1.7785
- F1 Micro: 0.815
- F1 Macro: 0.8049
- Ece: 0.1516
- Aurc: 0.0489
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: 64
- eval_batch_size: 64
- 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 | 13 | 5.0451 | 0.22 | 0.8885 | 8.4566 | 0.22 | 0.1247 | 0.2851 | 0.7928 |
No log | 2.0 | 26 | 4.5055 | 0.385 | 0.7765 | 3.9655 | 0.3850 | 0.3066 | 0.3049 | 0.4178 |
No log | 3.0 | 39 | 4.3096 | 0.52 | 0.6691 | 3.8146 | 0.52 | 0.3950 | 0.3177 | 0.2860 |
No log | 4.0 | 52 | 4.1755 | 0.575 | 0.5907 | 2.9444 | 0.575 | 0.4546 | 0.2729 | 0.2029 |
No log | 5.0 | 65 | 4.0437 | 0.675 | 0.5104 | 2.4241 | 0.675 | 0.5995 | 0.2991 | 0.1354 |
No log | 6.0 | 78 | 4.0642 | 0.69 | 0.4602 | 2.3471 | 0.69 | 0.5925 | 0.2798 | 0.1256 |
No log | 7.0 | 91 | 4.0104 | 0.695 | 0.4319 | 2.2902 | 0.695 | 0.6109 | 0.2430 | 0.1101 |
No log | 8.0 | 104 | 4.1702 | 0.7 | 0.4296 | 2.5778 | 0.7 | 0.6065 | 0.2231 | 0.1201 |
No log | 9.0 | 117 | 4.2785 | 0.695 | 0.4433 | 2.7331 | 0.695 | 0.6269 | 0.2296 | 0.1283 |
No log | 10.0 | 130 | 3.9853 | 0.725 | 0.3705 | 2.0880 | 0.7250 | 0.6477 | 0.1971 | 0.0874 |
No log | 11.0 | 143 | 3.9595 | 0.725 | 0.3506 | 2.1144 | 0.7250 | 0.6431 | 0.1650 | 0.0750 |
No log | 12.0 | 156 | 3.8678 | 0.735 | 0.3504 | 2.0683 | 0.735 | 0.6839 | 0.2047 | 0.0764 |
No log | 13.0 | 169 | 3.9641 | 0.745 | 0.3520 | 2.0788 | 0.745 | 0.6754 | 0.1899 | 0.0837 |
No log | 14.0 | 182 | 4.0188 | 0.725 | 0.3639 | 2.3771 | 0.7250 | 0.6643 | 0.1740 | 0.0893 |
No log | 15.0 | 195 | 3.8558 | 0.765 | 0.3342 | 1.4620 | 0.765 | 0.7097 | 0.1866 | 0.0696 |
No log | 16.0 | 208 | 3.9103 | 0.79 | 0.3416 | 1.7139 | 0.79 | 0.7662 | 0.2043 | 0.0770 |
No log | 17.0 | 221 | 4.0320 | 0.795 | 0.3548 | 1.8525 | 0.795 | 0.7690 | 0.1901 | 0.0924 |
No log | 18.0 | 234 | 3.8974 | 0.79 | 0.3264 | 1.8646 | 0.79 | 0.7582 | 0.1656 | 0.0739 |
No log | 19.0 | 247 | 3.8235 | 0.815 | 0.3074 | 1.4771 | 0.815 | 0.8185 | 0.1825 | 0.0617 |
No log | 20.0 | 260 | 3.8918 | 0.805 | 0.3150 | 1.6824 | 0.805 | 0.7893 | 0.1859 | 0.0631 |
No log | 21.0 | 273 | 3.8919 | 0.785 | 0.3161 | 1.7951 | 0.785 | 0.7725 | 0.1450 | 0.0701 |
No log | 22.0 | 286 | 3.8626 | 0.795 | 0.3121 | 1.6707 | 0.795 | 0.7832 | 0.1570 | 0.0684 |
No log | 23.0 | 299 | 3.8132 | 0.825 | 0.2906 | 1.4511 | 0.825 | 0.8097 | 0.1552 | 0.0564 |
No log | 24.0 | 312 | 3.8680 | 0.81 | 0.3048 | 1.9348 | 0.81 | 0.8027 | 0.1572 | 0.0611 |
No log | 25.0 | 325 | 3.8305 | 0.81 | 0.2954 | 1.5734 | 0.81 | 0.7999 | 0.1645 | 0.0556 |
No log | 26.0 | 338 | 3.8050 | 0.81 | 0.2965 | 1.7904 | 0.81 | 0.8013 | 0.1495 | 0.0546 |
No log | 27.0 | 351 | 3.9524 | 0.79 | 0.3212 | 2.0459 | 0.79 | 0.7846 | 0.1643 | 0.0669 |
No log | 28.0 | 364 | 3.9299 | 0.81 | 0.3076 | 1.7819 | 0.81 | 0.7967 | 0.1393 | 0.0601 |
No log | 29.0 | 377 | 3.9315 | 0.805 | 0.3158 | 2.0697 | 0.805 | 0.8046 | 0.1618 | 0.0663 |
No log | 30.0 | 390 | 3.8141 | 0.825 | 0.2853 | 1.9079 | 0.825 | 0.8150 | 0.1487 | 0.0528 |
No log | 31.0 | 403 | 3.8682 | 0.815 | 0.2932 | 1.9092 | 0.815 | 0.8030 | 0.1448 | 0.0585 |
No log | 32.0 | 416 | 3.8275 | 0.82 | 0.2823 | 1.6793 | 0.82 | 0.8043 | 0.1459 | 0.0508 |
No log | 33.0 | 429 | 3.8782 | 0.82 | 0.2895 | 1.6565 | 0.82 | 0.8077 | 0.1465 | 0.0542 |
No log | 34.0 | 442 | 3.8433 | 0.825 | 0.2891 | 1.6481 | 0.825 | 0.8157 | 0.1467 | 0.0525 |
No log | 35.0 | 455 | 3.8403 | 0.82 | 0.2891 | 1.5960 | 0.82 | 0.8090 | 0.1398 | 0.0497 |
No log | 36.0 | 468 | 3.8627 | 0.81 | 0.2848 | 1.6935 | 0.81 | 0.8015 | 0.1557 | 0.0471 |
No log | 37.0 | 481 | 3.8992 | 0.81 | 0.2937 | 1.8237 | 0.81 | 0.7991 | 0.1511 | 0.0515 |
No log | 38.0 | 494 | 3.9662 | 0.82 | 0.2978 | 1.8392 | 0.82 | 0.8143 | 0.1503 | 0.0527 |
3.5354 | 39.0 | 507 | 3.9440 | 0.825 | 0.2899 | 1.7818 | 0.825 | 0.8159 | 0.1454 | 0.0540 |
3.5354 | 40.0 | 520 | 3.9479 | 0.81 | 0.2959 | 1.7465 | 0.81 | 0.7986 | 0.1504 | 0.0501 |
3.5354 | 41.0 | 533 | 3.9760 | 0.815 | 0.2964 | 1.7821 | 0.815 | 0.8049 | 0.1519 | 0.0522 |
3.5354 | 42.0 | 546 | 3.9696 | 0.82 | 0.2906 | 1.7671 | 0.82 | 0.8127 | 0.1468 | 0.0503 |
3.5354 | 43.0 | 559 | 4.0107 | 0.81 | 0.2994 | 1.8207 | 0.81 | 0.7986 | 0.1474 | 0.0517 |
3.5354 | 44.0 | 572 | 3.9970 | 0.815 | 0.2913 | 1.7706 | 0.815 | 0.8049 | 0.1465 | 0.0504 |
3.5354 | 45.0 | 585 | 3.9890 | 0.815 | 0.2886 | 1.6384 | 0.815 | 0.8049 | 0.1516 | 0.0495 |
3.5354 | 46.0 | 598 | 4.0585 | 0.82 | 0.3006 | 1.7773 | 0.82 | 0.8127 | 0.1522 | 0.0518 |
3.5354 | 47.0 | 611 | 4.0448 | 0.825 | 0.2925 | 1.8226 | 0.825 | 0.8109 | 0.1540 | 0.0505 |
3.5354 | 48.0 | 624 | 4.0918 | 0.815 | 0.3016 | 1.8403 | 0.815 | 0.8049 | 0.1492 | 0.0512 |
3.5354 | 49.0 | 637 | 4.0677 | 0.82 | 0.2971 | 1.8256 | 0.82 | 0.8127 | 0.1396 | 0.0493 |
3.5354 | 50.0 | 650 | 4.0831 | 0.815 | 0.2986 | 1.8232 | 0.815 | 0.8049 | 0.1479 | 0.0513 |
3.5354 | 51.0 | 663 | 4.0846 | 0.815 | 0.2994 | 1.8268 | 0.815 | 0.8049 | 0.1525 | 0.0496 |
3.5354 | 52.0 | 676 | 4.0828 | 0.82 | 0.2978 | 1.7538 | 0.82 | 0.8127 | 0.1425 | 0.0486 |
3.5354 | 53.0 | 689 | 4.0890 | 0.815 | 0.3004 | 1.7552 | 0.815 | 0.8049 | 0.1491 | 0.0485 |
3.5354 | 54.0 | 702 | 4.1299 | 0.815 | 0.3029 | 1.8902 | 0.815 | 0.8049 | 0.1614 | 0.0506 |
3.5354 | 55.0 | 715 | 4.1200 | 0.815 | 0.3016 | 1.8279 | 0.815 | 0.8049 | 0.1510 | 0.0499 |
3.5354 | 56.0 | 728 | 4.1196 | 0.815 | 0.3008 | 1.8883 | 0.815 | 0.8049 | 0.1503 | 0.0503 |
3.5354 | 57.0 | 741 | 4.1200 | 0.815 | 0.3003 | 1.7620 | 0.815 | 0.8049 | 0.1499 | 0.0490 |
3.5354 | 58.0 | 754 | 4.1419 | 0.815 | 0.3017 | 1.8463 | 0.815 | 0.8049 | 0.1459 | 0.0499 |
3.5354 | 59.0 | 767 | 4.1527 | 0.815 | 0.3041 | 1.8269 | 0.815 | 0.8049 | 0.1618 | 0.0496 |
3.5354 | 60.0 | 780 | 4.1362 | 0.815 | 0.3002 | 1.7666 | 0.815 | 0.8049 | 0.1461 | 0.0489 |
3.5354 | 61.0 | 793 | 4.1470 | 0.815 | 0.3009 | 1.8213 | 0.815 | 0.8049 | 0.1471 | 0.0491 |
3.5354 | 62.0 | 806 | 4.1503 | 0.815 | 0.2991 | 1.8235 | 0.815 | 0.8049 | 0.1604 | 0.0496 |
3.5354 | 63.0 | 819 | 4.1544 | 0.815 | 0.3003 | 1.7546 | 0.815 | 0.8049 | 0.1518 | 0.0487 |
3.5354 | 64.0 | 832 | 4.1713 | 0.815 | 0.3023 | 1.8223 | 0.815 | 0.8049 | 0.1543 | 0.0499 |
3.5354 | 65.0 | 845 | 4.1716 | 0.815 | 0.3010 | 1.8213 | 0.815 | 0.8049 | 0.1485 | 0.0494 |
3.5354 | 66.0 | 858 | 4.1956 | 0.815 | 0.3042 | 1.8287 | 0.815 | 0.8049 | 0.1637 | 0.0496 |
3.5354 | 67.0 | 871 | 4.1845 | 0.815 | 0.3018 | 1.8259 | 0.815 | 0.8049 | 0.1519 | 0.0488 |
3.5354 | 68.0 | 884 | 4.2055 | 0.815 | 0.3037 | 1.8339 | 0.815 | 0.8049 | 0.1504 | 0.0496 |
3.5354 | 69.0 | 897 | 4.2079 | 0.815 | 0.3039 | 1.8281 | 0.815 | 0.8049 | 0.1554 | 0.0491 |
3.5354 | 70.0 | 910 | 4.2125 | 0.815 | 0.3034 | 1.7637 | 0.815 | 0.8049 | 0.1500 | 0.0490 |
3.5354 | 71.0 | 923 | 4.2179 | 0.815 | 0.3035 | 1.8254 | 0.815 | 0.8049 | 0.1531 | 0.0492 |
3.5354 | 72.0 | 936 | 4.2270 | 0.815 | 0.3040 | 1.8270 | 0.815 | 0.8049 | 0.1528 | 0.0493 |
3.5354 | 73.0 | 949 | 4.2294 | 0.815 | 0.3041 | 1.8260 | 0.815 | 0.8049 | 0.1531 | 0.0488 |
3.5354 | 74.0 | 962 | 4.2383 | 0.815 | 0.3043 | 1.8261 | 0.815 | 0.8049 | 0.1513 | 0.0492 |
3.5354 | 75.0 | 975 | 4.2441 | 0.815 | 0.3051 | 1.7691 | 0.815 | 0.8049 | 0.1539 | 0.0488 |
3.5354 | 76.0 | 988 | 4.2500 | 0.815 | 0.3051 | 1.8287 | 0.815 | 0.8049 | 0.1540 | 0.0490 |
3.192 | 77.0 | 1001 | 4.2538 | 0.815 | 0.3053 | 1.8273 | 0.815 | 0.8049 | 0.1542 | 0.0490 |
3.192 | 78.0 | 1014 | 4.2573 | 0.815 | 0.3055 | 1.8281 | 0.815 | 0.8049 | 0.1541 | 0.0491 |
3.192 | 79.0 | 1027 | 4.2603 | 0.815 | 0.3054 | 1.8275 | 0.815 | 0.8049 | 0.1544 | 0.0490 |
3.192 | 80.0 | 1040 | 4.2673 | 0.815 | 0.3060 | 1.8277 | 0.815 | 0.8049 | 0.1544 | 0.0489 |
3.192 | 81.0 | 1053 | 4.2697 | 0.815 | 0.3060 | 1.8272 | 0.815 | 0.8049 | 0.1500 | 0.0489 |
3.192 | 82.0 | 1066 | 4.2747 | 0.815 | 0.3064 | 1.7765 | 0.815 | 0.8049 | 0.1544 | 0.0489 |
3.192 | 83.0 | 1079 | 4.2769 | 0.815 | 0.3063 | 1.8273 | 0.815 | 0.8049 | 0.1503 | 0.0489 |
3.192 | 84.0 | 1092 | 4.2824 | 0.815 | 0.3066 | 1.8278 | 0.815 | 0.8049 | 0.1548 | 0.0491 |
3.192 | 85.0 | 1105 | 4.2842 | 0.815 | 0.3066 | 1.8276 | 0.815 | 0.8049 | 0.1506 | 0.0489 |
3.192 | 86.0 | 1118 | 4.2883 | 0.815 | 0.3070 | 1.8281 | 0.815 | 0.8049 | 0.1508 | 0.0488 |
3.192 | 87.0 | 1131 | 4.2907 | 0.815 | 0.3071 | 1.7730 | 0.815 | 0.8049 | 0.1548 | 0.0489 |
3.192 | 88.0 | 1144 | 4.2919 | 0.815 | 0.3070 | 1.7739 | 0.815 | 0.8049 | 0.1513 | 0.0489 |
3.192 | 89.0 | 1157 | 4.2943 | 0.815 | 0.3071 | 1.8281 | 0.815 | 0.8049 | 0.1514 | 0.0489 |
3.192 | 90.0 | 1170 | 4.2954 | 0.815 | 0.3070 | 1.8280 | 0.815 | 0.8049 | 0.1508 | 0.0489 |
3.192 | 91.0 | 1183 | 4.2976 | 0.815 | 0.3071 | 1.8282 | 0.815 | 0.8049 | 0.1514 | 0.0489 |
3.192 | 92.0 | 1196 | 4.2985 | 0.815 | 0.3070 | 1.7799 | 0.815 | 0.8049 | 0.1509 | 0.0489 |
3.192 | 93.0 | 1209 | 4.3000 | 0.815 | 0.3072 | 1.7832 | 0.815 | 0.8049 | 0.1514 | 0.0489 |
3.192 | 94.0 | 1222 | 4.3016 | 0.815 | 0.3073 | 1.7775 | 0.815 | 0.8049 | 0.1516 | 0.0489 |
3.192 | 95.0 | 1235 | 4.3025 | 0.815 | 0.3072 | 1.8282 | 0.815 | 0.8049 | 0.1510 | 0.0489 |
3.192 | 96.0 | 1248 | 4.3030 | 0.815 | 0.3073 | 1.7778 | 0.815 | 0.8049 | 0.1510 | 0.0489 |
3.192 | 97.0 | 1261 | 4.3042 | 0.815 | 0.3073 | 1.7770 | 0.815 | 0.8049 | 0.1516 | 0.0489 |
3.192 | 98.0 | 1274 | 4.3047 | 0.815 | 0.3074 | 1.7826 | 0.815 | 0.8049 | 0.1516 | 0.0489 |
3.192 | 99.0 | 1287 | 4.3051 | 0.815 | 0.3074 | 1.7777 | 0.815 | 0.8049 | 0.1516 | 0.0489 |
3.192 | 100.0 | 1300 | 4.3051 | 0.815 | 0.3074 | 1.7785 | 0.815 | 0.8049 | 0.1516 | 0.0489 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2