<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
60-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: 230.9055
- Accuracy: 0.855
- Brier Loss: 0.2199
- Nll: 1.0336
- F1 Micro: 0.855
- F1 Macro: 0.8458
- Ece: 0.1335
- Aurc: 0.0336
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 | 238.9631 | 0.285 | 0.8828 | 6.5847 | 0.285 | 0.1874 | 0.2964 | 0.5019 |
| No log | 2.0 | 100 | 237.5668 | 0.385 | 0.7452 | 3.0464 | 0.3850 | 0.2403 | 0.2776 | 0.4072 |
| No log | 3.0 | 150 | 236.0767 | 0.615 | 0.5834 | 2.4900 | 0.615 | 0.4713 | 0.2629 | 0.2189 |
| No log | 4.0 | 200 | 235.7085 | 0.635 | 0.5104 | 2.9259 | 0.635 | 0.4933 | 0.2605 | 0.1700 |
| No log | 5.0 | 250 | 234.8680 | 0.66 | 0.4494 | 2.2358 | 0.66 | 0.4974 | 0.2021 | 0.1292 |
| No log | 6.0 | 300 | 235.0645 | 0.68 | 0.4615 | 2.3164 | 0.68 | 0.5568 | 0.2601 | 0.1346 |
| No log | 7.0 | 350 | 234.3820 | 0.735 | 0.3741 | 1.8624 | 0.735 | 0.6245 | 0.2265 | 0.0894 |
| No log | 8.0 | 400 | 233.9906 | 0.72 | 0.3954 | 1.7623 | 0.72 | 0.6479 | 0.1779 | 0.0980 |
| No log | 9.0 | 450 | 234.0194 | 0.755 | 0.3410 | 1.6963 | 0.755 | 0.6965 | 0.1730 | 0.0718 |
| 234.3621 | 10.0 | 500 | 234.2365 | 0.705 | 0.3859 | 2.4174 | 0.705 | 0.6957 | 0.1759 | 0.0944 |
| 234.3621 | 11.0 | 550 | 233.5580 | 0.76 | 0.3331 | 1.5730 | 0.76 | 0.7135 | 0.1817 | 0.0709 |
| 234.3621 | 12.0 | 600 | 233.3485 | 0.815 | 0.2725 | 1.6179 | 0.815 | 0.7769 | 0.1835 | 0.0497 |
| 234.3621 | 13.0 | 650 | 233.6395 | 0.805 | 0.3038 | 1.7563 | 0.805 | 0.7813 | 0.1976 | 0.0698 |
| 234.3621 | 14.0 | 700 | 233.1443 | 0.805 | 0.2928 | 1.4722 | 0.805 | 0.7779 | 0.1513 | 0.0546 |
| 234.3621 | 15.0 | 750 | 233.1237 | 0.83 | 0.2569 | 1.7889 | 0.83 | 0.8231 | 0.1361 | 0.0460 |
| 234.3621 | 16.0 | 800 | 232.9007 | 0.825 | 0.2675 | 1.7492 | 0.825 | 0.8125 | 0.1742 | 0.0558 |
| 234.3621 | 17.0 | 850 | 233.0284 | 0.79 | 0.2861 | 1.4243 | 0.79 | 0.7698 | 0.1418 | 0.0520 |
| 234.3621 | 18.0 | 900 | 232.9831 | 0.79 | 0.3009 | 1.4085 | 0.79 | 0.7440 | 0.1962 | 0.0643 |
| 234.3621 | 19.0 | 950 | 232.9837 | 0.825 | 0.2618 | 1.4839 | 0.825 | 0.7949 | 0.1444 | 0.0457 |
| 231.5126 | 20.0 | 1000 | 232.9143 | 0.825 | 0.2599 | 1.5299 | 0.825 | 0.8086 | 0.1570 | 0.0463 |
| 231.5126 | 21.0 | 1050 | 232.5251 | 0.835 | 0.2495 | 1.2311 | 0.835 | 0.8279 | 0.1511 | 0.0472 |
| 231.5126 | 22.0 | 1100 | 232.6748 | 0.855 | 0.2165 | 1.2547 | 0.855 | 0.8448 | 0.1450 | 0.0299 |
| 231.5126 | 23.0 | 1150 | 232.6610 | 0.83 | 0.2450 | 1.2944 | 0.83 | 0.8113 | 0.1545 | 0.0403 |
| 231.5126 | 24.0 | 1200 | 232.7660 | 0.83 | 0.2480 | 1.4783 | 0.83 | 0.8101 | 0.1645 | 0.0397 |
| 231.5126 | 25.0 | 1250 | 232.5843 | 0.855 | 0.2336 | 1.1227 | 0.855 | 0.8303 | 0.1672 | 0.0397 |
| 231.5126 | 26.0 | 1300 | 232.3482 | 0.84 | 0.2321 | 1.1720 | 0.8400 | 0.8346 | 0.1527 | 0.0380 |
| 231.5126 | 27.0 | 1350 | 232.3758 | 0.84 | 0.2353 | 1.1684 | 0.8400 | 0.8327 | 0.1520 | 0.0372 |
| 231.5126 | 28.0 | 1400 | 232.3022 | 0.82 | 0.2460 | 1.0888 | 0.82 | 0.7920 | 0.1746 | 0.0392 |
| 231.5126 | 29.0 | 1450 | 232.1077 | 0.845 | 0.2355 | 1.3720 | 0.845 | 0.8306 | 0.1314 | 0.0372 |
| 230.5624 | 30.0 | 1500 | 232.3631 | 0.825 | 0.2443 | 1.3202 | 0.825 | 0.7971 | 0.1404 | 0.0373 |
| 230.5624 | 31.0 | 1550 | 232.1099 | 0.84 | 0.2509 | 1.2935 | 0.8400 | 0.8199 | 0.1552 | 0.0453 |
| 230.5624 | 32.0 | 1600 | 232.1548 | 0.855 | 0.2275 | 1.0948 | 0.855 | 0.8360 | 0.1428 | 0.0347 |
| 230.5624 | 33.0 | 1650 | 232.0168 | 0.84 | 0.2284 | 1.1303 | 0.8400 | 0.8260 | 0.1460 | 0.0374 |
| 230.5624 | 34.0 | 1700 | 232.1122 | 0.875 | 0.2154 | 1.3044 | 0.875 | 0.8612 | 0.1410 | 0.0307 |
| 230.5624 | 35.0 | 1750 | 232.0452 | 0.84 | 0.2382 | 1.1732 | 0.8400 | 0.8199 | 0.1218 | 0.0376 |
| 230.5624 | 36.0 | 1800 | 231.8549 | 0.835 | 0.2390 | 1.1322 | 0.835 | 0.8227 | 0.1478 | 0.0375 |
| 230.5624 | 37.0 | 1850 | 231.8938 | 0.845 | 0.2558 | 1.0115 | 0.845 | 0.8261 | 0.1730 | 0.0447 |
| 230.5624 | 38.0 | 1900 | 231.8979 | 0.85 | 0.2292 | 1.1142 | 0.85 | 0.8361 | 0.1359 | 0.0348 |
| 230.5624 | 39.0 | 1950 | 231.7455 | 0.84 | 0.2217 | 1.0746 | 0.8400 | 0.8185 | 0.1294 | 0.0309 |
| 229.9089 | 40.0 | 2000 | 231.8694 | 0.85 | 0.2200 | 1.0529 | 0.85 | 0.8334 | 0.1435 | 0.0343 |
| 229.9089 | 41.0 | 2050 | 231.8044 | 0.84 | 0.2317 | 0.9332 | 0.8400 | 0.8204 | 0.1432 | 0.0337 |
| 229.9089 | 42.0 | 2100 | 231.6414 | 0.855 | 0.2165 | 1.1356 | 0.855 | 0.8393 | 0.1357 | 0.0321 |
| 229.9089 | 43.0 | 2150 | 231.5806 | 0.835 | 0.2378 | 1.0314 | 0.835 | 0.8124 | 0.1443 | 0.0382 |
| 229.9089 | 44.0 | 2200 | 231.6199 | 0.855 | 0.2287 | 1.0907 | 0.855 | 0.8463 | 0.1196 | 0.0362 |
| 229.9089 | 45.0 | 2250 | 231.5991 | 0.85 | 0.2208 | 1.0967 | 0.85 | 0.8350 | 0.1321 | 0.0339 |
| 229.9089 | 46.0 | 2300 | 231.5103 | 0.85 | 0.2249 | 1.0330 | 0.85 | 0.8270 | 0.1239 | 0.0332 |
| 229.9089 | 47.0 | 2350 | 231.4252 | 0.87 | 0.2126 | 1.1054 | 0.87 | 0.8618 | 0.1230 | 0.0312 |
| 229.9089 | 48.0 | 2400 | 231.4696 | 0.86 | 0.2136 | 1.0952 | 0.8600 | 0.8503 | 0.1304 | 0.0302 |
| 229.9089 | 49.0 | 2450 | 231.5416 | 0.84 | 0.2329 | 1.0155 | 0.8400 | 0.8256 | 0.1381 | 0.0356 |
| 229.4364 | 50.0 | 2500 | 231.4932 | 0.84 | 0.2215 | 1.1382 | 0.8400 | 0.8177 | 0.1557 | 0.0319 |
| 229.4364 | 51.0 | 2550 | 231.4270 | 0.84 | 0.2312 | 1.0191 | 0.8400 | 0.8253 | 0.1376 | 0.0371 |
| 229.4364 | 52.0 | 2600 | 231.3520 | 0.85 | 0.2233 | 1.2815 | 0.85 | 0.8289 | 0.1444 | 0.0334 |
| 229.4364 | 53.0 | 2650 | 231.3922 | 0.86 | 0.2223 | 1.0950 | 0.8600 | 0.8423 | 0.1309 | 0.0334 |
| 229.4364 | 54.0 | 2700 | 231.3504 | 0.855 | 0.2171 | 1.0165 | 0.855 | 0.8422 | 0.1304 | 0.0313 |
| 229.4364 | 55.0 | 2750 | 231.2676 | 0.87 | 0.2129 | 1.0704 | 0.87 | 0.8598 | 0.1334 | 0.0320 |
| 229.4364 | 56.0 | 2800 | 231.2823 | 0.84 | 0.2390 | 1.0982 | 0.8400 | 0.8226 | 0.1187 | 0.0372 |
| 229.4364 | 57.0 | 2850 | 231.2740 | 0.85 | 0.2251 | 0.9521 | 0.85 | 0.8271 | 0.1388 | 0.0320 |
| 229.4364 | 58.0 | 2900 | 231.2784 | 0.85 | 0.2284 | 1.0194 | 0.85 | 0.8320 | 0.1306 | 0.0360 |
| 229.4364 | 59.0 | 2950 | 231.2078 | 0.84 | 0.2265 | 1.0036 | 0.8400 | 0.8253 | 0.1359 | 0.0366 |
| 229.043 | 60.0 | 3000 | 231.2086 | 0.85 | 0.2380 | 1.0247 | 0.85 | 0.8391 | 0.1395 | 0.0374 |
| 229.043 | 61.0 | 3050 | 231.2673 | 0.845 | 0.2410 | 1.0205 | 0.845 | 0.8272 | 0.1466 | 0.0389 |
| 229.043 | 62.0 | 3100 | 231.1900 | 0.855 | 0.2219 | 1.0835 | 0.855 | 0.8449 | 0.1351 | 0.0346 |
| 229.043 | 63.0 | 3150 | 231.0561 | 0.845 | 0.2417 | 0.9740 | 0.845 | 0.8332 | 0.1503 | 0.0405 |
| 229.043 | 64.0 | 3200 | 231.1282 | 0.845 | 0.2387 | 1.1105 | 0.845 | 0.8270 | 0.1198 | 0.0379 |
| 229.043 | 65.0 | 3250 | 231.0782 | 0.85 | 0.2334 | 0.9838 | 0.85 | 0.8403 | 0.1282 | 0.0356 |
| 229.043 | 66.0 | 3300 | 231.0704 | 0.84 | 0.2442 | 1.0380 | 0.8400 | 0.8275 | 0.1543 | 0.0410 |
| 229.043 | 67.0 | 3350 | 231.0450 | 0.85 | 0.2246 | 1.0023 | 0.85 | 0.8394 | 0.1212 | 0.0353 |
| 229.043 | 68.0 | 3400 | 231.1017 | 0.85 | 0.2257 | 1.0437 | 0.85 | 0.8334 | 0.1232 | 0.0350 |
| 229.043 | 69.0 | 3450 | 231.0068 | 0.85 | 0.2321 | 1.0075 | 0.85 | 0.8445 | 0.1271 | 0.0361 |
| 228.7748 | 70.0 | 3500 | 231.0666 | 0.85 | 0.2274 | 1.0133 | 0.85 | 0.8382 | 0.1334 | 0.0361 |
| 228.7748 | 71.0 | 3550 | 230.9450 | 0.85 | 0.2417 | 1.0738 | 0.85 | 0.8356 | 0.1294 | 0.0380 |
| 228.7748 | 72.0 | 3600 | 230.7952 | 0.85 | 0.2379 | 0.9779 | 0.85 | 0.8391 | 0.1309 | 0.0393 |
| 228.7748 | 73.0 | 3650 | 231.0920 | 0.86 | 0.2188 | 1.0154 | 0.8600 | 0.8538 | 0.1230 | 0.0335 |
| 228.7748 | 74.0 | 3700 | 230.9152 | 0.855 | 0.2408 | 1.1637 | 0.855 | 0.8486 | 0.1490 | 0.0400 |
| 228.7748 | 75.0 | 3750 | 230.9537 | 0.85 | 0.2195 | 1.0135 | 0.85 | 0.8301 | 0.1131 | 0.0321 |
| 228.7748 | 76.0 | 3800 | 230.9977 | 0.855 | 0.2208 | 1.0136 | 0.855 | 0.8484 | 0.1296 | 0.0334 |
| 228.7748 | 77.0 | 3850 | 230.9619 | 0.855 | 0.2348 | 1.0158 | 0.855 | 0.8526 | 0.1346 | 0.0371 |
| 228.7748 | 78.0 | 3900 | 230.9416 | 0.84 | 0.2315 | 1.0372 | 0.8400 | 0.8219 | 0.1290 | 0.0353 |
| 228.7748 | 79.0 | 3950 | 231.0093 | 0.85 | 0.2196 | 1.0981 | 0.85 | 0.8318 | 0.1380 | 0.0335 |
| 228.5779 | 80.0 | 4000 | 230.9455 | 0.845 | 0.2290 | 1.0193 | 0.845 | 0.8332 | 0.1459 | 0.0350 |
| 228.5779 | 81.0 | 4050 | 230.8672 | 0.845 | 0.2184 | 1.0164 | 0.845 | 0.8309 | 0.1560 | 0.0322 |
| 228.5779 | 82.0 | 4100 | 230.9410 | 0.855 | 0.2282 | 1.0116 | 0.855 | 0.8486 | 0.1309 | 0.0349 |
| 228.5779 | 83.0 | 4150 | 230.9393 | 0.855 | 0.2258 | 1.0168 | 0.855 | 0.8498 | 0.1227 | 0.0355 |
| 228.5779 | 84.0 | 4200 | 230.8770 | 0.845 | 0.2204 | 1.0105 | 0.845 | 0.8303 | 0.1259 | 0.0315 |
| 228.5779 | 85.0 | 4250 | 230.9236 | 0.845 | 0.2271 | 1.0079 | 0.845 | 0.8332 | 0.1274 | 0.0353 |
| 228.5779 | 86.0 | 4300 | 230.9332 | 0.845 | 0.2237 | 1.0410 | 0.845 | 0.8288 | 0.1480 | 0.0340 |
| 228.5779 | 87.0 | 4350 | 230.8607 | 0.845 | 0.2273 | 1.0343 | 0.845 | 0.8313 | 0.1070 | 0.0338 |
| 228.5779 | 88.0 | 4400 | 230.7832 | 0.85 | 0.2434 | 1.1399 | 0.85 | 0.8432 | 0.1483 | 0.0407 |
| 228.5779 | 89.0 | 4450 | 230.8136 | 0.85 | 0.2263 | 1.0002 | 0.85 | 0.8367 | 0.1283 | 0.0343 |
| 228.4285 | 90.0 | 4500 | 230.9154 | 0.86 | 0.2243 | 1.0189 | 0.8600 | 0.8552 | 0.1319 | 0.0332 |
| 228.4285 | 91.0 | 4550 | 230.8125 | 0.86 | 0.2320 | 0.9955 | 0.8600 | 0.8552 | 0.1437 | 0.0361 |
| 228.4285 | 92.0 | 4600 | 230.8634 | 0.855 | 0.2238 | 1.0341 | 0.855 | 0.8477 | 0.1252 | 0.0329 |
| 228.4285 | 93.0 | 4650 | 230.8527 | 0.84 | 0.2326 | 0.9819 | 0.8400 | 0.8242 | 0.1248 | 0.0362 |
| 228.4285 | 94.0 | 4700 | 230.8176 | 0.845 | 0.2347 | 1.0080 | 0.845 | 0.8332 | 0.1356 | 0.0369 |
| 228.4285 | 95.0 | 4750 | 230.7853 | 0.85 | 0.2286 | 1.0163 | 0.85 | 0.8445 | 0.1176 | 0.0356 |
| 228.4285 | 96.0 | 4800 | 230.9345 | 0.855 | 0.2218 | 1.0151 | 0.855 | 0.8458 | 0.1252 | 0.0328 |
| 228.4285 | 97.0 | 4850 | 230.8020 | 0.855 | 0.2300 | 1.0166 | 0.855 | 0.8462 | 0.1424 | 0.0349 |
| 228.4285 | 98.0 | 4900 | 230.8873 | 0.855 | 0.2240 | 1.0244 | 0.855 | 0.8477 | 0.1309 | 0.0343 |
| 228.4285 | 99.0 | 4950 | 230.8796 | 0.855 | 0.2276 | 1.0084 | 0.855 | 0.8498 | 0.1254 | 0.0344 |
| 228.3542 | 100.0 | 5000 | 230.9055 | 0.855 | 0.2199 | 1.0336 | 0.855 | 0.8458 | 0.1335 | 0.0336 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
