generated_from_trainer

<!-- 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. -->

cdip-small_rvl_cdip-NK1000_kd_CEKD_t2.5_a0.5

This model is a fine-tuned version of WinKawaks/vit-small-patch16-224 on the None dataset. It achieves the following results on the evaluation set:

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:

Training results

Training Loss Epoch Step Validation Loss Accuracy Brier Loss Nll F1 Micro F1 Macro Ece Aurc
No log 1.0 167 1.6705 0.6378 0.4837 2.4248 0.6378 0.6323 0.0655 0.1457
No log 2.0 334 1.1423 0.7322 0.3740 1.9847 0.7322 0.7285 0.0695 0.0846
1.7909 3.0 501 0.9082 0.7682 0.3248 1.7674 0.7682 0.7676 0.0620 0.0642
1.7909 4.0 668 0.8494 0.7865 0.3082 1.7306 0.7865 0.7904 0.0665 0.0560
1.7909 5.0 835 0.7837 0.798 0.2988 1.6072 0.798 0.7953 0.0729 0.0553
0.4994 6.0 1002 0.6867 0.804 0.2862 1.5014 0.804 0.8059 0.0794 0.0471
0.4994 7.0 1169 0.7037 0.8157 0.2797 1.5533 0.8157 0.8178 0.0807 0.0478
0.4994 8.0 1336 0.6709 0.8163 0.2756 1.5297 0.8163 0.8166 0.0728 0.0478
0.2478 9.0 1503 0.6132 0.825 0.2576 1.4349 0.825 0.8247 0.0728 0.0398
0.2478 10.0 1670 0.6389 0.8235 0.2671 1.4455 0.8235 0.8266 0.0746 0.0419
0.2478 11.0 1837 0.6043 0.8257 0.2585 1.4609 0.8257 0.8293 0.0752 0.0403
0.1683 12.0 2004 0.5639 0.8327 0.2457 1.4470 0.8327 0.8350 0.0676 0.0375
0.1683 13.0 2171 0.5665 0.8317 0.2508 1.4054 0.8317 0.8324 0.0731 0.0388
0.1683 14.0 2338 0.5505 0.8403 0.2427 1.4059 0.8403 0.8408 0.0649 0.0377
0.131 15.0 2505 0.5321 0.836 0.2428 1.4078 0.836 0.8372 0.0684 0.0365
0.131 16.0 2672 0.5161 0.8373 0.2383 1.3900 0.8373 0.8373 0.0711 0.0368
0.131 17.0 2839 0.5177 0.8403 0.2371 1.3828 0.8403 0.8413 0.0633 0.0354
0.1071 18.0 3006 0.5113 0.8407 0.2377 1.3832 0.8407 0.8432 0.0718 0.0343
0.1071 19.0 3173 0.4949 0.8415 0.2332 1.3767 0.8415 0.8428 0.0667 0.0338
0.1071 20.0 3340 0.4857 0.848 0.2271 1.3664 0.848 0.8492 0.0615 0.0338
0.0877 21.0 3507 0.4812 0.847 0.2283 1.3360 0.847 0.8478 0.0602 0.0346
0.0877 22.0 3674 0.4715 0.8495 0.2243 1.3761 0.8495 0.8506 0.0560 0.0320
0.0877 23.0 3841 0.4622 0.8508 0.2206 1.3584 0.8508 0.8515 0.0557 0.0323
0.0694 24.0 4008 0.4432 0.8515 0.2167 1.3653 0.8515 0.8531 0.0555 0.0309
0.0694 25.0 4175 0.4467 0.8498 0.2193 1.3499 0.8498 0.8512 0.0581 0.0309
0.0694 26.0 4342 0.4412 0.8545 0.2162 1.3535 0.8545 0.8560 0.0534 0.0306
0.0586 27.0 4509 0.4402 0.8498 0.2180 1.3390 0.8498 0.8510 0.0597 0.0309
0.0586 28.0 4676 0.4408 0.8522 0.2174 1.3568 0.8522 0.8536 0.0576 0.0306
0.0586 29.0 4843 0.4391 0.851 0.2168 1.3429 0.851 0.8523 0.0585 0.0305
0.0549 30.0 5010 0.4371 0.853 0.2160 1.3389 0.853 0.8543 0.0573 0.0303
0.0549 31.0 5177 0.4382 0.8498 0.2168 1.3486 0.8498 0.8513 0.0602 0.0304
0.0549 32.0 5344 0.4372 0.853 0.2166 1.3501 0.853 0.8540 0.0591 0.0306
0.0527 33.0 5511 0.4379 0.852 0.2156 1.3546 0.852 0.8531 0.0576 0.0304
0.0527 34.0 5678 0.4353 0.8532 0.2154 1.3381 0.8532 0.8543 0.0574 0.0302
0.0527 35.0 5845 0.4347 0.8525 0.2148 1.3550 0.8525 0.8535 0.0591 0.0304
0.0511 36.0 6012 0.4311 0.8542 0.2141 1.3233 0.8542 0.8552 0.0572 0.0299
0.0511 37.0 6179 0.4323 0.852 0.2150 1.3332 0.852 0.8532 0.0586 0.0302
0.0511 38.0 6346 0.4321 0.8515 0.2152 1.3382 0.8515 0.8527 0.0583 0.0299
0.0494 39.0 6513 0.4335 0.8495 0.2152 1.3385 0.8495 0.8511 0.0593 0.0303
0.0494 40.0 6680 0.4323 0.852 0.2146 1.3603 0.852 0.8533 0.0576 0.0299
0.0494 41.0 6847 0.4309 0.8512 0.2143 1.3448 0.8512 0.8525 0.0570 0.0299
0.0477 42.0 7014 0.4327 0.8525 0.2149 1.3439 0.8525 0.8539 0.0580 0.0299
0.0477 43.0 7181 0.4309 0.8532 0.2140 1.3406 0.8532 0.8544 0.0560 0.0299
0.0477 44.0 7348 0.4308 0.8528 0.2141 1.3404 0.8528 0.8540 0.0573 0.0299
0.0466 45.0 7515 0.4317 0.8525 0.2147 1.3402 0.8525 0.8538 0.0580 0.0299
0.0466 46.0 7682 0.4317 0.8535 0.2144 1.3475 0.8535 0.8547 0.0553 0.0298
0.0466 47.0 7849 0.4314 0.8525 0.2143 1.3479 0.8525 0.8537 0.0559 0.0299
0.0465 48.0 8016 0.4314 0.8525 0.2143 1.3479 0.8525 0.8538 0.0559 0.0299
0.0465 49.0 8183 0.4316 0.8528 0.2145 1.3471 0.8528 0.8540 0.0573 0.0299
0.0465 50.0 8350 0.4315 0.8522 0.2145 1.3474 0.8522 0.8535 0.0573 0.0300

Framework versions