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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-small_tobacco3482_og_simkd_
results: []
---
<!-- 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. -->
# vit-small_tobacco3482_og_simkd_
This model is a fine-tuned version of [WinKawaks/vit-small-patch16-224](https://huggingface.co/WinKawaks/vit-small-patch16-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 212.9178
- Accuracy: 0.855
- Brier Loss: 0.2563
- Nll: 1.4722
- F1 Micro: 0.855
- F1 Macro: 0.8333
- Ece: 0.1253
- Aurc: 0.0422
## 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 | 219.2297 | 0.145 | 0.8895 | 6.5562 | 0.145 | 0.0567 | 0.2109 | 0.7661 |
| No log | 2.0 | 50 | 217.9786 | 0.49 | 0.6839 | 2.2035 | 0.49 | 0.4113 | 0.3237 | 0.3097 |
| No log | 3.0 | 75 | 216.6085 | 0.565 | 0.5671 | 1.7658 | 0.565 | 0.4471 | 0.2471 | 0.2239 |
| No log | 4.0 | 100 | 216.0210 | 0.68 | 0.4722 | 1.8682 | 0.68 | 0.5586 | 0.2322 | 0.1557 |
| No log | 5.0 | 125 | 215.5695 | 0.68 | 0.4668 | 1.9385 | 0.68 | 0.5570 | 0.2289 | 0.1440 |
| No log | 6.0 | 150 | 215.3762 | 0.745 | 0.3963 | 2.1043 | 0.745 | 0.6608 | 0.1949 | 0.0976 |
| No log | 7.0 | 175 | 214.8964 | 0.745 | 0.3675 | 1.7226 | 0.745 | 0.6693 | 0.1765 | 0.0949 |
| No log | 8.0 | 200 | 215.0440 | 0.735 | 0.3838 | 1.9180 | 0.735 | 0.6935 | 0.2056 | 0.0958 |
| No log | 9.0 | 225 | 214.7017 | 0.775 | 0.3466 | 1.5816 | 0.775 | 0.6897 | 0.1756 | 0.0661 |
| No log | 10.0 | 250 | 214.6309 | 0.775 | 0.3505 | 1.6245 | 0.775 | 0.7604 | 0.1828 | 0.0763 |
| No log | 11.0 | 275 | 214.6275 | 0.735 | 0.4314 | 2.3367 | 0.735 | 0.7342 | 0.2234 | 0.1203 |
| No log | 12.0 | 300 | 214.5664 | 0.75 | 0.3769 | 1.7889 | 0.75 | 0.7420 | 0.1873 | 0.1070 |
| No log | 13.0 | 325 | 214.6764 | 0.735 | 0.4425 | 2.3533 | 0.735 | 0.7404 | 0.2267 | 0.1508 |
| No log | 14.0 | 350 | 214.5261 | 0.805 | 0.3093 | 1.8504 | 0.805 | 0.7870 | 0.1732 | 0.0580 |
| No log | 15.0 | 375 | 214.4932 | 0.79 | 0.3255 | 1.4649 | 0.79 | 0.7575 | 0.1796 | 0.0543 |
| No log | 16.0 | 400 | 214.3134 | 0.85 | 0.2467 | 1.4769 | 0.85 | 0.8388 | 0.1149 | 0.0513 |
| No log | 17.0 | 425 | 214.3825 | 0.82 | 0.2845 | 1.4858 | 0.82 | 0.8014 | 0.1445 | 0.0540 |
| No log | 18.0 | 450 | 214.2077 | 0.85 | 0.2681 | 1.4891 | 0.85 | 0.8406 | 0.1462 | 0.0684 |
| No log | 19.0 | 475 | 214.1675 | 0.845 | 0.2623 | 1.5311 | 0.845 | 0.8329 | 0.1414 | 0.0485 |
| 220.0633 | 20.0 | 500 | 214.1433 | 0.84 | 0.2663 | 1.5269 | 0.8400 | 0.8182 | 0.1302 | 0.0562 |
| 220.0633 | 21.0 | 525 | 214.0829 | 0.805 | 0.3293 | 2.0021 | 0.805 | 0.8019 | 0.1710 | 0.0833 |
| 220.0633 | 22.0 | 550 | 213.9282 | 0.84 | 0.2586 | 1.5127 | 0.8400 | 0.8205 | 0.1397 | 0.0453 |
| 220.0633 | 23.0 | 575 | 213.9303 | 0.87 | 0.2260 | 1.4450 | 0.87 | 0.8552 | 0.1205 | 0.0365 |
| 220.0633 | 24.0 | 600 | 213.9140 | 0.84 | 0.2620 | 1.5244 | 0.8400 | 0.8161 | 0.1462 | 0.0490 |
| 220.0633 | 25.0 | 625 | 213.7616 | 0.86 | 0.2306 | 1.5288 | 0.8600 | 0.8409 | 0.1215 | 0.0361 |
| 220.0633 | 26.0 | 650 | 213.7738 | 0.845 | 0.2431 | 1.5303 | 0.845 | 0.8271 | 0.1335 | 0.0443 |
| 220.0633 | 27.0 | 675 | 213.8470 | 0.85 | 0.2427 | 1.3459 | 0.85 | 0.8275 | 0.1296 | 0.0445 |
| 220.0633 | 28.0 | 700 | 213.7198 | 0.85 | 0.2381 | 1.3868 | 0.85 | 0.8328 | 0.1267 | 0.0424 |
| 220.0633 | 29.0 | 725 | 213.6302 | 0.855 | 0.2293 | 1.4191 | 0.855 | 0.8361 | 0.1157 | 0.0394 |
| 220.0633 | 30.0 | 750 | 213.6385 | 0.85 | 0.2424 | 1.5410 | 0.85 | 0.8334 | 0.1339 | 0.0464 |
| 220.0633 | 31.0 | 775 | 213.6397 | 0.865 | 0.2234 | 1.4012 | 0.865 | 0.8464 | 0.1226 | 0.0402 |
| 220.0633 | 32.0 | 800 | 213.6658 | 0.86 | 0.2271 | 1.3863 | 0.8600 | 0.8470 | 0.1164 | 0.0354 |
| 220.0633 | 33.0 | 825 | 213.6526 | 0.85 | 0.2448 | 1.5357 | 0.85 | 0.8292 | 0.1214 | 0.0397 |
| 220.0633 | 34.0 | 850 | 213.5407 | 0.855 | 0.2282 | 1.3470 | 0.855 | 0.8405 | 0.1245 | 0.0393 |
| 220.0633 | 35.0 | 875 | 213.6166 | 0.83 | 0.2624 | 1.4288 | 0.83 | 0.8102 | 0.1415 | 0.0458 |
| 220.0633 | 36.0 | 900 | 213.5887 | 0.84 | 0.2613 | 1.3928 | 0.8400 | 0.8135 | 0.1298 | 0.0442 |
| 220.0633 | 37.0 | 925 | 213.4976 | 0.845 | 0.2338 | 1.3784 | 0.845 | 0.8244 | 0.1319 | 0.0355 |
| 220.0633 | 38.0 | 950 | 213.4554 | 0.85 | 0.2374 | 1.3680 | 0.85 | 0.8323 | 0.1192 | 0.0385 |
| 220.0633 | 39.0 | 975 | 213.4758 | 0.845 | 0.2319 | 1.4895 | 0.845 | 0.8274 | 0.1185 | 0.0385 |
| 217.7609 | 40.0 | 1000 | 213.4440 | 0.845 | 0.2432 | 1.3737 | 0.845 | 0.8265 | 0.1310 | 0.0415 |
| 217.7609 | 41.0 | 1025 | 213.4492 | 0.845 | 0.2385 | 1.4970 | 0.845 | 0.8297 | 0.1207 | 0.0373 |
| 217.7609 | 42.0 | 1050 | 213.4319 | 0.85 | 0.2384 | 1.3580 | 0.85 | 0.8276 | 0.1250 | 0.0383 |
| 217.7609 | 43.0 | 1075 | 213.3094 | 0.855 | 0.2287 | 1.4375 | 0.855 | 0.8334 | 0.1188 | 0.0353 |
| 217.7609 | 44.0 | 1100 | 213.3809 | 0.845 | 0.2514 | 1.4969 | 0.845 | 0.8250 | 0.1318 | 0.0435 |
| 217.7609 | 45.0 | 1125 | 213.3981 | 0.85 | 0.2478 | 1.6052 | 0.85 | 0.8287 | 0.1268 | 0.0408 |
| 217.7609 | 46.0 | 1150 | 213.3004 | 0.86 | 0.2292 | 1.3632 | 0.8600 | 0.8430 | 0.1180 | 0.0355 |
| 217.7609 | 47.0 | 1175 | 213.3041 | 0.86 | 0.2363 | 1.3407 | 0.8600 | 0.8444 | 0.1235 | 0.0359 |
| 217.7609 | 48.0 | 1200 | 213.2955 | 0.845 | 0.2462 | 1.5071 | 0.845 | 0.8179 | 0.1253 | 0.0396 |
| 217.7609 | 49.0 | 1225 | 213.2531 | 0.85 | 0.2433 | 1.2946 | 0.85 | 0.8277 | 0.1270 | 0.0392 |
| 217.7609 | 50.0 | 1250 | 213.2612 | 0.845 | 0.2378 | 1.2852 | 0.845 | 0.8193 | 0.1281 | 0.0361 |
| 217.7609 | 51.0 | 1275 | 213.2246 | 0.855 | 0.2370 | 1.5829 | 0.855 | 0.8393 | 0.1234 | 0.0357 |
| 217.7609 | 52.0 | 1300 | 213.1795 | 0.845 | 0.2431 | 1.4923 | 0.845 | 0.8300 | 0.1280 | 0.0372 |
| 217.7609 | 53.0 | 1325 | 213.2721 | 0.855 | 0.2467 | 1.5096 | 0.855 | 0.8333 | 0.1248 | 0.0385 |
| 217.7609 | 54.0 | 1350 | 213.1976 | 0.85 | 0.2453 | 1.4167 | 0.85 | 0.8275 | 0.1240 | 0.0384 |
| 217.7609 | 55.0 | 1375 | 213.2822 | 0.845 | 0.2430 | 1.4438 | 0.845 | 0.8193 | 0.1283 | 0.0396 |
| 217.7609 | 56.0 | 1400 | 213.1443 | 0.85 | 0.2479 | 1.5246 | 0.85 | 0.8277 | 0.1304 | 0.0389 |
| 217.7609 | 57.0 | 1425 | 213.1679 | 0.85 | 0.2455 | 1.4468 | 0.85 | 0.8291 | 0.1224 | 0.0387 |
| 217.7609 | 58.0 | 1450 | 213.1116 | 0.85 | 0.2467 | 1.4372 | 0.85 | 0.8287 | 0.1269 | 0.0378 |
| 217.7609 | 59.0 | 1475 | 213.1005 | 0.85 | 0.2490 | 1.4214 | 0.85 | 0.8271 | 0.1316 | 0.0392 |
| 217.1217 | 60.0 | 1500 | 213.1516 | 0.855 | 0.2425 | 1.4600 | 0.855 | 0.8343 | 0.1316 | 0.0369 |
| 217.1217 | 61.0 | 1525 | 213.1205 | 0.855 | 0.2458 | 1.4436 | 0.855 | 0.8303 | 0.1197 | 0.0409 |
| 217.1217 | 62.0 | 1550 | 213.1318 | 0.85 | 0.2488 | 1.4405 | 0.85 | 0.8275 | 0.1304 | 0.0378 |
| 217.1217 | 63.0 | 1575 | 213.0243 | 0.855 | 0.2521 | 1.5810 | 0.855 | 0.8328 | 0.1341 | 0.0447 |
| 217.1217 | 64.0 | 1600 | 213.1191 | 0.84 | 0.2567 | 1.4478 | 0.8400 | 0.8185 | 0.1292 | 0.0436 |
| 217.1217 | 65.0 | 1625 | 213.0329 | 0.855 | 0.2528 | 1.3910 | 0.855 | 0.8333 | 0.1311 | 0.0404 |
| 217.1217 | 66.0 | 1650 | 212.9868 | 0.85 | 0.2525 | 1.4652 | 0.85 | 0.8275 | 0.1226 | 0.0408 |
| 217.1217 | 67.0 | 1675 | 213.0856 | 0.84 | 0.2561 | 1.4601 | 0.8400 | 0.8178 | 0.1367 | 0.0419 |
| 217.1217 | 68.0 | 1700 | 213.0379 | 0.845 | 0.2544 | 1.5222 | 0.845 | 0.8216 | 0.1362 | 0.0426 |
| 217.1217 | 69.0 | 1725 | 213.0535 | 0.835 | 0.2606 | 1.5085 | 0.835 | 0.8093 | 0.1346 | 0.0445 |
| 217.1217 | 70.0 | 1750 | 213.0247 | 0.85 | 0.2530 | 1.4349 | 0.85 | 0.8274 | 0.1373 | 0.0427 |
| 217.1217 | 71.0 | 1775 | 213.0161 | 0.855 | 0.2510 | 1.4529 | 0.855 | 0.8333 | 0.1212 | 0.0411 |
| 217.1217 | 72.0 | 1800 | 213.0249 | 0.845 | 0.2494 | 1.4511 | 0.845 | 0.8229 | 0.1358 | 0.0412 |
| 217.1217 | 73.0 | 1825 | 213.0014 | 0.85 | 0.2548 | 1.4435 | 0.85 | 0.8264 | 0.1277 | 0.0390 |
| 217.1217 | 74.0 | 1850 | 213.0011 | 0.845 | 0.2527 | 1.3719 | 0.845 | 0.8206 | 0.1360 | 0.0379 |
| 217.1217 | 75.0 | 1875 | 213.0240 | 0.845 | 0.2576 | 1.4072 | 0.845 | 0.8221 | 0.1284 | 0.0425 |
| 217.1217 | 76.0 | 1900 | 212.9793 | 0.845 | 0.2534 | 1.4026 | 0.845 | 0.8212 | 0.1241 | 0.0404 |
| 217.1217 | 77.0 | 1925 | 212.9800 | 0.85 | 0.2514 | 1.5023 | 0.85 | 0.8271 | 0.1279 | 0.0407 |
| 217.1217 | 78.0 | 1950 | 212.9125 | 0.845 | 0.2564 | 1.4258 | 0.845 | 0.8211 | 0.1298 | 0.0427 |
| 217.1217 | 79.0 | 1975 | 212.9454 | 0.85 | 0.2527 | 1.5227 | 0.85 | 0.8271 | 0.1279 | 0.0423 |
| 216.765 | 80.0 | 2000 | 212.9475 | 0.845 | 0.2551 | 1.5025 | 0.845 | 0.8206 | 0.1311 | 0.0423 |
| 216.765 | 81.0 | 2025 | 212.9739 | 0.84 | 0.2567 | 1.5305 | 0.8400 | 0.8162 | 0.1294 | 0.0431 |
| 216.765 | 82.0 | 2050 | 212.9351 | 0.855 | 0.2526 | 1.5373 | 0.855 | 0.8339 | 0.1277 | 0.0401 |
| 216.765 | 83.0 | 2075 | 213.0053 | 0.845 | 0.2560 | 1.4724 | 0.845 | 0.8228 | 0.1341 | 0.0417 |
| 216.765 | 84.0 | 2100 | 212.9326 | 0.845 | 0.2568 | 1.5217 | 0.845 | 0.8206 | 0.1303 | 0.0472 |
| 216.765 | 85.0 | 2125 | 212.9555 | 0.855 | 0.2537 | 1.5265 | 0.855 | 0.8339 | 0.1233 | 0.0416 |
| 216.765 | 86.0 | 2150 | 212.9121 | 0.85 | 0.2534 | 1.5224 | 0.85 | 0.8280 | 0.1283 | 0.0398 |
| 216.765 | 87.0 | 2175 | 212.8850 | 0.845 | 0.2551 | 1.4480 | 0.845 | 0.8221 | 0.1328 | 0.0412 |
| 216.765 | 88.0 | 2200 | 212.9121 | 0.855 | 0.2518 | 1.5069 | 0.855 | 0.8339 | 0.1234 | 0.0404 |
| 216.765 | 89.0 | 2225 | 212.9327 | 0.845 | 0.2517 | 1.4532 | 0.845 | 0.8206 | 0.1231 | 0.0401 |
| 216.765 | 90.0 | 2250 | 212.9305 | 0.85 | 0.2542 | 1.4506 | 0.85 | 0.8271 | 0.1374 | 0.0398 |
| 216.765 | 91.0 | 2275 | 212.9274 | 0.85 | 0.2567 | 1.5045 | 0.85 | 0.8280 | 0.1297 | 0.0419 |
| 216.765 | 92.0 | 2300 | 212.8962 | 0.85 | 0.2545 | 1.4956 | 0.85 | 0.8280 | 0.1261 | 0.0405 |
| 216.765 | 93.0 | 2325 | 212.9133 | 0.845 | 0.2567 | 1.5274 | 0.845 | 0.8212 | 0.1291 | 0.0431 |
| 216.765 | 94.0 | 2350 | 212.8708 | 0.85 | 0.2576 | 1.4410 | 0.85 | 0.8280 | 0.1302 | 0.0410 |
| 216.765 | 95.0 | 2375 | 212.9661 | 0.855 | 0.2546 | 1.3988 | 0.855 | 0.8339 | 0.1248 | 0.0404 |
| 216.765 | 96.0 | 2400 | 212.9099 | 0.855 | 0.2547 | 1.5096 | 0.855 | 0.8333 | 0.1256 | 0.0402 |
| 216.765 | 97.0 | 2425 | 212.9668 | 0.85 | 0.2549 | 1.5337 | 0.85 | 0.8271 | 0.1289 | 0.0390 |
| 216.765 | 98.0 | 2450 | 212.9587 | 0.845 | 0.2545 | 1.5161 | 0.845 | 0.8215 | 0.1304 | 0.0412 |
| 216.765 | 99.0 | 2475 | 212.9395 | 0.855 | 0.2554 | 1.4606 | 0.855 | 0.8333 | 0.1253 | 0.0410 |
| 216.6085 | 100.0 | 2500 | 212.9178 | 0.855 | 0.2563 | 1.4722 | 0.855 | 0.8333 | 0.1253 | 0.0422 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2
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