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18-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: 269.3729
- Accuracy: 0.36
- Brier Loss: 0.8320
- Nll: 4.3971
- F1 Micro: 0.36
- F1 Macro: 0.2725
- Ece: 0.3539
- Aurc: 0.6748
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 | 278.3639 | 0.075 | 0.8950 | 9.1030 | 0.075 | 0.0452 | 0.1624 | 0.8470 |
| No log | 2.0 | 100 | 276.7339 | 0.095 | 0.8890 | 8.6785 | 0.095 | 0.0820 | 0.1806 | 0.9095 |
| No log | 3.0 | 150 | 275.0460 | 0.16 | 0.8755 | 6.5857 | 0.16 | 0.0866 | 0.2296 | 0.8951 |
| No log | 4.0 | 200 | 274.4719 | 0.33 | 0.8662 | 6.6801 | 0.33 | 0.1980 | 0.3166 | 0.5931 |
| No log | 5.0 | 250 | 273.5627 | 0.23 | 0.8660 | 6.4504 | 0.23 | 0.1193 | 0.2606 | 0.7477 |
| No log | 6.0 | 300 | 273.5152 | 0.22 | 0.8622 | 6.1576 | 0.22 | 0.1323 | 0.2578 | 0.6395 |
| No log | 7.0 | 350 | 273.0874 | 0.2 | 0.8584 | 5.8986 | 0.2000 | 0.1249 | 0.2508 | 0.8129 |
| No log | 8.0 | 400 | 273.7433 | 0.19 | 0.8764 | 6.0516 | 0.19 | 0.1554 | 0.2550 | 0.8545 |
| No log | 9.0 | 450 | 272.4757 | 0.185 | 0.8533 | 5.9072 | 0.185 | 0.1340 | 0.2529 | 0.7360 |
| 273.9531 | 10.0 | 500 | 272.7899 | 0.14 | 0.8669 | 6.3132 | 0.14 | 0.1080 | 0.2373 | 0.8882 |
| 273.9531 | 11.0 | 550 | 271.7198 | 0.245 | 0.8484 | 4.7561 | 0.245 | 0.1370 | 0.2741 | 0.7203 |
| 273.9531 | 12.0 | 600 | 272.7391 | 0.095 | 0.8761 | 6.3636 | 0.095 | 0.0930 | 0.2120 | 0.9142 |
| 273.9531 | 13.0 | 650 | 271.8800 | 0.24 | 0.8566 | 4.9415 | 0.24 | 0.1926 | 0.2825 | 0.7850 |
| 273.9531 | 14.0 | 700 | 271.4349 | 0.305 | 0.8408 | 4.6971 | 0.305 | 0.1935 | 0.3087 | 0.7274 |
| 273.9531 | 15.0 | 750 | 271.7440 | 0.24 | 0.8476 | 3.9346 | 0.24 | 0.1835 | 0.2902 | 0.8098 |
| 273.9531 | 16.0 | 800 | 271.1944 | 0.28 | 0.8464 | 4.1470 | 0.28 | 0.2074 | 0.3074 | 0.7919 |
| 273.9531 | 17.0 | 850 | 271.2062 | 0.34 | 0.8363 | 4.8972 | 0.34 | 0.2136 | 0.3237 | 0.6403 |
| 273.9531 | 18.0 | 900 | 271.6591 | 0.295 | 0.8548 | 4.7423 | 0.295 | 0.1990 | 0.3066 | 0.7590 |
| 273.9531 | 19.0 | 950 | 271.5129 | 0.255 | 0.8571 | 4.8864 | 0.255 | 0.1898 | 0.2901 | 0.7929 |
| 270.6992 | 20.0 | 1000 | 271.4151 | 0.265 | 0.8543 | 5.2793 | 0.265 | 0.1924 | 0.2928 | 0.7842 |
| 270.6992 | 21.0 | 1050 | 271.0936 | 0.35 | 0.8449 | 4.4171 | 0.35 | 0.2347 | 0.3389 | 0.7230 |
| 270.6992 | 22.0 | 1100 | 271.2365 | 0.285 | 0.8504 | 4.7910 | 0.285 | 0.2020 | 0.3147 | 0.7840 |
| 270.6992 | 23.0 | 1150 | 271.3472 | 0.26 | 0.8496 | 4.1785 | 0.26 | 0.1800 | 0.2922 | 0.7983 |
| 270.6992 | 24.0 | 1200 | 271.1550 | 0.335 | 0.8466 | 4.8743 | 0.335 | 0.2518 | 0.3381 | 0.7148 |
| 270.6992 | 25.0 | 1250 | 270.7837 | 0.34 | 0.8455 | 4.7405 | 0.34 | 0.2392 | 0.3420 | 0.7592 |
| 270.6992 | 26.0 | 1300 | 271.2034 | 0.325 | 0.8485 | 5.0231 | 0.325 | 0.2418 | 0.3302 | 0.7411 |
| 270.6992 | 27.0 | 1350 | 270.5752 | 0.385 | 0.8334 | 4.5239 | 0.3850 | 0.2866 | 0.3535 | 0.6197 |
| 270.6992 | 28.0 | 1400 | 270.6892 | 0.35 | 0.8407 | 4.5651 | 0.35 | 0.2593 | 0.3428 | 0.6812 |
| 270.6992 | 29.0 | 1450 | 270.7246 | 0.36 | 0.8411 | 4.6054 | 0.36 | 0.2699 | 0.3365 | 0.6772 |
| 269.5806 | 30.0 | 1500 | 270.6962 | 0.32 | 0.8453 | 4.3997 | 0.32 | 0.2170 | 0.3145 | 0.7129 |
| 269.5806 | 31.0 | 1550 | 270.8489 | 0.325 | 0.8478 | 4.8399 | 0.325 | 0.2367 | 0.3180 | 0.6999 |
| 269.5806 | 32.0 | 1600 | 270.5093 | 0.36 | 0.8370 | 4.6472 | 0.36 | 0.2765 | 0.3456 | 0.6472 |
| 269.5806 | 33.0 | 1650 | 270.5440 | 0.35 | 0.8407 | 4.6948 | 0.35 | 0.2532 | 0.3292 | 0.6436 |
| 269.5806 | 34.0 | 1700 | 270.6743 | 0.395 | 0.8387 | 4.1379 | 0.395 | 0.2872 | 0.3730 | 0.6805 |
| 269.5806 | 35.0 | 1750 | 270.6282 | 0.33 | 0.8415 | 4.2499 | 0.33 | 0.2445 | 0.3410 | 0.7220 |
| 269.5806 | 36.0 | 1800 | 270.5709 | 0.31 | 0.8478 | 4.8275 | 0.31 | 0.2295 | 0.3063 | 0.7223 |
| 269.5806 | 37.0 | 1850 | 270.4933 | 0.33 | 0.8449 | 4.7300 | 0.33 | 0.2415 | 0.3157 | 0.6997 |
| 269.5806 | 38.0 | 1900 | 270.4860 | 0.355 | 0.8360 | 4.4343 | 0.3550 | 0.2598 | 0.3373 | 0.6545 |
| 269.5806 | 39.0 | 1950 | 269.9668 | 0.37 | 0.8306 | 4.4080 | 0.37 | 0.2602 | 0.3349 | 0.6056 |
| 268.8099 | 40.0 | 2000 | 270.3401 | 0.385 | 0.8389 | 5.0506 | 0.3850 | 0.2777 | 0.3567 | 0.6686 |
| 268.8099 | 41.0 | 2050 | 270.0377 | 0.365 | 0.8320 | 4.6238 | 0.3650 | 0.2466 | 0.3429 | 0.6167 |
| 268.8099 | 42.0 | 2100 | 270.2510 | 0.355 | 0.8363 | 4.7053 | 0.3550 | 0.2498 | 0.3352 | 0.6564 |
| 268.8099 | 43.0 | 2150 | 270.0252 | 0.38 | 0.8275 | 4.2261 | 0.38 | 0.2690 | 0.3557 | 0.5995 |
| 268.8099 | 44.0 | 2200 | 269.9756 | 0.36 | 0.8251 | 4.2336 | 0.36 | 0.2516 | 0.3226 | 0.6005 |
| 268.8099 | 45.0 | 2250 | 270.1610 | 0.34 | 0.8383 | 4.5052 | 0.34 | 0.2593 | 0.3164 | 0.6854 |
| 268.8099 | 46.0 | 2300 | 270.0320 | 0.33 | 0.8396 | 4.4659 | 0.33 | 0.2458 | 0.3114 | 0.7070 |
| 268.8099 | 47.0 | 2350 | 269.9535 | 0.335 | 0.8316 | 4.6707 | 0.335 | 0.2419 | 0.3203 | 0.6503 |
| 268.8099 | 48.0 | 2400 | 270.0645 | 0.365 | 0.8320 | 4.4182 | 0.3650 | 0.2517 | 0.3230 | 0.6360 |
| 268.8099 | 49.0 | 2450 | 270.0541 | 0.375 | 0.8348 | 4.4803 | 0.375 | 0.2717 | 0.3504 | 0.6444 |
| 268.2443 | 50.0 | 2500 | 269.8891 | 0.33 | 0.8374 | 4.7223 | 0.33 | 0.2365 | 0.3223 | 0.6716 |
| 268.2443 | 51.0 | 2550 | 269.8773 | 0.39 | 0.8355 | 4.4693 | 0.39 | 0.2637 | 0.3547 | 0.6525 |
| 268.2443 | 52.0 | 2600 | 269.6983 | 0.39 | 0.8298 | 4.5670 | 0.39 | 0.2716 | 0.3624 | 0.6230 |
| 268.2443 | 53.0 | 2650 | 270.0016 | 0.35 | 0.8327 | 4.3052 | 0.35 | 0.2402 | 0.3367 | 0.6602 |
| 268.2443 | 54.0 | 2700 | 269.7764 | 0.35 | 0.8318 | 4.3783 | 0.35 | 0.2432 | 0.3189 | 0.6373 |
| 268.2443 | 55.0 | 2750 | 269.7582 | 0.36 | 0.8272 | 4.4652 | 0.36 | 0.2535 | 0.3130 | 0.6197 |
| 268.2443 | 56.0 | 2800 | 269.7654 | 0.385 | 0.8253 | 4.4241 | 0.3850 | 0.2751 | 0.3375 | 0.6019 |
| 268.2443 | 57.0 | 2850 | 269.7094 | 0.375 | 0.8331 | 4.5019 | 0.375 | 0.2691 | 0.3413 | 0.6391 |
| 268.2443 | 58.0 | 2900 | 269.7442 | 0.37 | 0.8323 | 4.5422 | 0.37 | 0.2813 | 0.3311 | 0.6468 |
| 268.2443 | 59.0 | 2950 | 269.7930 | 0.385 | 0.8265 | 4.4502 | 0.3850 | 0.2820 | 0.3331 | 0.6032 |
| 267.7843 | 60.0 | 3000 | 269.6804 | 0.375 | 0.8270 | 4.3152 | 0.375 | 0.2723 | 0.3221 | 0.6005 |
| 267.7843 | 61.0 | 3050 | 269.7132 | 0.36 | 0.8355 | 4.4928 | 0.36 | 0.2625 | 0.3464 | 0.6679 |
| 267.7843 | 62.0 | 3100 | 269.6766 | 0.375 | 0.8308 | 4.5392 | 0.375 | 0.2644 | 0.3272 | 0.6307 |
| 267.7843 | 63.0 | 3150 | 269.5538 | 0.32 | 0.8345 | 4.4571 | 0.32 | 0.2299 | 0.3160 | 0.6791 |
| 267.7843 | 64.0 | 3200 | 269.5080 | 0.375 | 0.8262 | 4.1608 | 0.375 | 0.2581 | 0.3323 | 0.6357 |
| 267.7843 | 65.0 | 3250 | 269.6766 | 0.355 | 0.8362 | 4.4220 | 0.3550 | 0.2647 | 0.3250 | 0.6591 |
| 267.7843 | 66.0 | 3300 | 269.4889 | 0.38 | 0.8249 | 4.3636 | 0.38 | 0.2786 | 0.3452 | 0.6364 |
| 267.7843 | 67.0 | 3350 | 269.4171 | 0.4 | 0.8246 | 4.2888 | 0.4000 | 0.2877 | 0.3479 | 0.6114 |
| 267.7843 | 68.0 | 3400 | 269.6962 | 0.37 | 0.8286 | 4.3171 | 0.37 | 0.2614 | 0.3376 | 0.6369 |
| 267.7843 | 69.0 | 3450 | 269.3859 | 0.425 | 0.8225 | 4.2805 | 0.425 | 0.3053 | 0.3649 | 0.5751 |
| 267.4508 | 70.0 | 3500 | 269.5482 | 0.345 | 0.8377 | 4.7547 | 0.345 | 0.2559 | 0.3341 | 0.6728 |
| 267.4508 | 71.0 | 3550 | 269.3435 | 0.4 | 0.8216 | 4.3030 | 0.4000 | 0.2858 | 0.3391 | 0.6045 |
| 267.4508 | 72.0 | 3600 | 269.2284 | 0.405 | 0.8198 | 4.3223 | 0.405 | 0.3006 | 0.3598 | 0.5984 |
| 267.4508 | 73.0 | 3650 | 269.5614 | 0.37 | 0.8300 | 4.3579 | 0.37 | 0.2645 | 0.3515 | 0.6597 |
| 267.4508 | 74.0 | 3700 | 269.2826 | 0.39 | 0.8217 | 4.3413 | 0.39 | 0.2738 | 0.3317 | 0.5869 |
| 267.4508 | 75.0 | 3750 | 269.3375 | 0.39 | 0.8226 | 4.2796 | 0.39 | 0.2712 | 0.3485 | 0.6140 |
| 267.4508 | 76.0 | 3800 | 269.2377 | 0.39 | 0.8198 | 4.4825 | 0.39 | 0.2771 | 0.3450 | 0.5936 |
| 267.4508 | 77.0 | 3850 | 269.4238 | 0.375 | 0.8278 | 4.5048 | 0.375 | 0.2736 | 0.3349 | 0.6386 |
| 267.4508 | 78.0 | 3900 | 269.4522 | 0.4 | 0.8283 | 4.5498 | 0.4000 | 0.2870 | 0.3318 | 0.6187 |
| 267.4508 | 79.0 | 3950 | 269.4372 | 0.355 | 0.8316 | 4.5034 | 0.3550 | 0.2621 | 0.3182 | 0.6581 |
| 267.2267 | 80.0 | 4000 | 269.4058 | 0.38 | 0.8262 | 4.4096 | 0.38 | 0.2834 | 0.3453 | 0.6197 |
| 267.2267 | 81.0 | 4050 | 269.2977 | 0.37 | 0.8251 | 4.4666 | 0.37 | 0.2669 | 0.3374 | 0.6406 |
| 267.2267 | 82.0 | 4100 | 269.3194 | 0.37 | 0.8286 | 4.4947 | 0.37 | 0.2751 | 0.3332 | 0.6326 |
| 267.2267 | 83.0 | 4150 | 269.2936 | 0.365 | 0.8301 | 4.3184 | 0.3650 | 0.2725 | 0.3358 | 0.6815 |
| 267.2267 | 84.0 | 4200 | 269.2045 | 0.4 | 0.8242 | 4.2851 | 0.4000 | 0.2947 | 0.3526 | 0.6133 |
| 267.2267 | 85.0 | 4250 | 269.2916 | 0.38 | 0.8256 | 4.4965 | 0.38 | 0.2872 | 0.3190 | 0.6079 |
| 267.2267 | 86.0 | 4300 | 269.3817 | 0.35 | 0.8327 | 4.3865 | 0.35 | 0.2686 | 0.3341 | 0.6660 |
| 267.2267 | 87.0 | 4350 | 269.2809 | 0.36 | 0.8296 | 4.4521 | 0.36 | 0.2664 | 0.3367 | 0.6620 |
| 267.2267 | 88.0 | 4400 | 269.1650 | 0.405 | 0.8181 | 4.2997 | 0.405 | 0.2857 | 0.3527 | 0.5624 |
| 267.2267 | 89.0 | 4450 | 269.1071 | 0.375 | 0.8297 | 4.3559 | 0.375 | 0.2737 | 0.3386 | 0.6423 |
| 267.0481 | 90.0 | 4500 | 269.3120 | 0.385 | 0.8268 | 4.4102 | 0.3850 | 0.2833 | 0.3438 | 0.6264 |
| 267.0481 | 91.0 | 4550 | 269.1590 | 0.4 | 0.8243 | 4.2495 | 0.4000 | 0.2964 | 0.3382 | 0.5986 |
| 267.0481 | 92.0 | 4600 | 269.1963 | 0.4 | 0.8230 | 4.4469 | 0.4000 | 0.3070 | 0.3521 | 0.5969 |
| 267.0481 | 93.0 | 4650 | 269.1320 | 0.39 | 0.8256 | 4.2528 | 0.39 | 0.2856 | 0.3355 | 0.6072 |
| 267.0481 | 94.0 | 4700 | 269.2391 | 0.4 | 0.8222 | 4.3351 | 0.4000 | 0.2891 | 0.3392 | 0.6019 |
| 267.0481 | 95.0 | 4750 | 269.2017 | 0.395 | 0.8243 | 4.3717 | 0.395 | 0.2931 | 0.3435 | 0.6271 |
| 267.0481 | 96.0 | 4800 | 269.4085 | 0.37 | 0.8290 | 4.3941 | 0.37 | 0.2817 | 0.3255 | 0.6242 |
| 267.0481 | 97.0 | 4850 | 269.2195 | 0.4 | 0.8231 | 4.4454 | 0.4000 | 0.2889 | 0.3452 | 0.5916 |
| 267.0481 | 98.0 | 4900 | 269.3515 | 0.375 | 0.8296 | 4.3291 | 0.375 | 0.2754 | 0.3370 | 0.6380 |
| 267.0481 | 99.0 | 4950 | 269.3496 | 0.395 | 0.8244 | 4.4743 | 0.395 | 0.2989 | 0.3432 | 0.6100 |
| 266.9625 | 100.0 | 5000 | 269.3729 | 0.36 | 0.8320 | 4.3971 | 0.36 | 0.2725 | 0.3539 | 0.6748 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
