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vit-pretraining-2024_03_14

This model is a fine-tuned version of google/vit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3360

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: 4.6875e-06
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 800.0

Training results

Training Loss Epoch Step Validation Loss
1.0249 1.0 3583 1.0248
0.9939 2.0 7166 0.9940
0.9684 3.0 10749 0.9675
0.9411 4.0 14332 0.9439
0.9385 5.0 17915 0.9319
0.9105 6.0 21498 0.9036
0.87 7.0 25081 0.8847
0.8103 8.0 28664 0.8216
0.7776 9.0 32247 0.7917
0.772 10.0 35830 0.7733
0.7577 11.0 39413 0.7593
0.7543 12.0 42996 0.7469
0.7229 13.0 46579 0.7348
0.7367 14.0 50162 0.7231
0.7186 15.0 53745 0.7162
0.6945 16.0 57328 0.7074
0.6966 17.0 60911 0.6957
0.6699 18.0 64494 0.6815
0.6837 19.0 68077 0.6737
0.6981 20.0 71660 0.6679
0.6692 21.0 75243 0.6618
0.6542 22.0 78826 0.6589
0.6692 23.0 82409 0.6433
0.6409 24.0 85992 0.6381
0.6417 25.0 89575 0.6330
0.6184 26.0 93158 0.6277
0.6111 27.0 96741 0.6211
0.6445 28.0 100324 0.6169
0.6258 29.0 103907 0.6131
0.592 30.0 107490 0.6102
0.6087 31.0 111073 0.6094
0.5809 32.0 114656 0.6021
0.5883 33.0 118239 0.6023
0.5945 34.0 121822 0.5976
0.6055 35.0 125405 0.5937
0.5927 36.0 128988 0.5887
0.5596 37.0 132571 0.5854
0.5683 38.0 136154 0.5787
0.5639 39.0 139737 0.5796
0.5931 40.0 143320 0.5734
0.5773 41.0 146903 0.5735
0.5794 42.0 150486 0.5701
0.558 43.0 154069 0.5638
0.5822 44.0 157652 0.5647
0.5671 45.0 161235 0.5636
0.5509 46.0 164818 0.5666
0.563 47.0 168401 0.5586
0.5645 48.0 171984 0.5540
0.5417 49.0 175567 0.5491
0.5516 50.0 179150 0.5476
0.5508 51.0 182733 0.5487
0.5309 52.0 186316 0.5420
0.5274 53.0 189899 0.5401
0.5349 54.0 193482 0.5388
0.5375 55.0 197065 0.5346
0.5127 56.0 200648 0.5337
0.5168 57.0 204231 0.5338
0.5292 58.0 207814 0.5336
0.526 59.0 211397 0.5278
0.5335 60.0 214980 0.5240
0.5343 61.0 218563 0.5236
0.5121 62.0 222146 0.5226
0.5293 63.0 225729 0.5189
0.5213 64.0 229312 0.5178
0.5063 65.0 232895 0.5164
0.5037 66.0 236478 0.5134
0.5159 67.0 240061 0.5096
0.5112 68.0 243644 0.5094
0.5056 69.0 247227 0.5046
0.5004 70.0 250810 0.5031
0.5031 71.0 254393 0.5024
0.4931 72.0 257976 0.4983
0.4887 73.0 261559 0.4947
0.4888 74.0 265142 0.4901
0.4668 75.0 268725 0.4890
0.4804 76.0 272308 0.4833
0.4662 77.0 275891 0.4789
0.4969 78.0 279474 0.4745
0.4552 79.0 283057 0.4715
0.4553 80.0 286640 0.4707
0.4716 81.0 290223 0.4681
0.4643 82.0 293806 0.4631
0.4596 83.0 297389 0.4621
0.4429 84.0 300972 0.4611
0.4684 85.0 304555 0.4600
0.4461 86.0 308138 0.4553
0.451 87.0 311721 0.4513
0.4675 88.0 315304 0.4512
0.4433 89.0 318887 0.4488
0.4708 90.0 322470 0.4450
0.4523 91.0 326053 0.4434
0.4395 92.0 329636 0.4421
0.4746 93.0 333219 0.4427
0.4537 94.0 336802 0.4382
0.4287 95.0 340385 0.4366
0.4256 96.0 343968 0.4365
0.4406 97.0 347551 0.4374
0.4301 98.0 351134 0.4327
0.4107 99.0 354717 0.4338
0.4337 100.0 358300 0.4310
0.4117 101.0 361883 0.4291
0.4468 102.0 365466 0.4289
0.4124 103.0 369049 0.4263
0.4338 104.0 372632 0.4240
0.4232 105.0 376215 0.4246
0.4122 106.0 379798 0.4225
0.4242 107.0 383381 0.4228
0.4372 108.0 386964 0.4206
0.4163 109.0 390547 0.4199
0.4347 110.0 394130 0.4208
0.4046 111.0 397713 0.4181
0.444 112.0 401296 0.4176
0.4057 113.0 404879 0.4155
0.4195 114.0 408462 0.4159
0.4376 115.0 412045 0.4172
0.4197 116.0 415628 0.4142
0.4286 117.0 419211 0.4116
0.4222 118.0 422794 0.4108
0.4152 119.0 426377 0.4137
0.4141 120.0 429960 0.4105
0.419 121.0 433543 0.4089
0.4205 122.0 437126 0.4083
0.4187 123.0 440709 0.4087
0.39 124.0 444292 0.4065
0.3914 125.0 447875 0.4069
0.4077 126.0 451458 0.4068
0.3943 127.0 455041 0.4045
0.4167 128.0 458624 0.4049
0.4162 129.0 462207 0.4044
0.3902 130.0 465790 0.4036
0.398 131.0 469373 0.4014
0.4082 132.0 472956 0.3995
0.4093 133.0 476539 0.4011
0.3893 134.0 480122 0.4016
0.3961 135.0 483705 0.4000
0.4075 136.0 487288 0.3982
0.4007 137.0 490871 0.4006
0.3961 138.0 494454 0.3973
0.3775 139.0 498037 0.3981
0.4088 140.0 501620 0.3977
0.4036 141.0 505203 0.3962
0.4006 142.0 508786 0.3950
0.3895 143.0 512369 0.3964
0.3908 144.0 515952 0.3959
0.3933 145.0 519535 0.3959
0.4021 146.0 523118 0.3946
0.3912 147.0 526701 0.3944
0.3881 148.0 530284 0.3925
0.3984 149.0 533867 0.3923
0.3925 150.0 537450 0.3920
0.3896 151.0 541033 0.3906
0.3925 152.0 544616 0.3916
0.3975 153.0 548199 0.3911
0.3925 154.0 551782 0.3909
0.3857 155.0 555365 0.3891
0.4006 156.0 558948 0.3900
0.3961 157.0 562531 0.3890
0.389 158.0 566114 0.3903
0.3923 159.0 569697 0.3874
0.4047 160.0 573280 0.3873
0.3928 161.0 576863 0.3868
0.3862 162.0 580446 0.3860
0.3931 163.0 584029 0.3870
0.3882 164.0 587612 0.3872
0.3806 165.0 591195 0.3870
0.372 166.0 594778 0.3845
0.3758 167.0 598361 0.3852
0.3904 168.0 601944 0.3833
0.3891 169.0 605527 0.3843
0.3965 170.0 609110 0.3835
0.3798 171.0 612693 0.3828
0.3864 172.0 616276 0.3824
0.3909 173.0 619859 0.3841
0.3771 174.0 623442 0.3826
0.376 175.0 627025 0.3820
0.3747 176.0 630608 0.3825
0.3785 177.0 634191 0.3815
0.3871 178.0 637774 0.3795
0.3829 179.0 641357 0.3819
0.3862 180.0 644940 0.3817
0.3798 181.0 648523 0.3817
0.3867 182.0 652106 0.3814
0.3661 183.0 655689 0.3795
0.3707 184.0 659272 0.3798
0.3798 185.0 662855 0.3797
0.3891 186.0 666438 0.3797
0.3577 187.0 670021 0.3783
0.3846 188.0 673604 0.3782
0.3647 189.0 677187 0.3771
0.384 190.0 680770 0.3773
0.3717 191.0 684353 0.3778
0.3756 192.0 687936 0.3763
0.4 193.0 691519 0.3768
0.3507 194.0 695102 0.3746
0.3719 195.0 698685 0.3755
0.3659 196.0 702268 0.3753
0.3753 197.0 705851 0.3753
0.372 198.0 709434 0.3744
0.3973 199.0 713017 0.3749
0.3622 200.0 716600 0.3743
0.3691 201.0 720183 0.3727
0.3741 202.0 723766 0.3743
0.3893 203.0 727349 0.3733
0.3743 204.0 730932 0.3727
0.3701 205.0 734515 0.3721
0.3743 206.0 738098 0.3736
0.3746 207.0 741681 0.3723
0.3985 208.0 745264 0.3738
0.3583 209.0 748847 0.3715
0.3706 210.0 752430 0.3714
0.3782 211.0 756013 0.3723
0.3724 212.0 759596 0.3721
0.3716 213.0 763179 0.3710
0.3764 214.0 766762 0.3722
0.3698 215.0 770345 0.3714
0.3613 216.0 773928 0.3695
0.3646 217.0 777511 0.3699
0.364 218.0 781094 0.3687
0.366 219.0 784677 0.3704
0.3603 220.0 788260 0.3702
0.3565 221.0 791843 0.3691
0.3784 222.0 795426 0.3692
0.3761 223.0 799009 0.3685
0.3607 224.0 802592 0.3674
0.3471 225.0 806175 0.3682
0.3669 226.0 809758 0.3687
0.3864 227.0 813341 0.3695
0.3667 228.0 816924 0.3682
0.3782 229.0 820507 0.3667
0.3841 230.0 824090 0.3664
0.3698 231.0 827673 0.3660
0.3579 232.0 831256 0.3661
0.3754 233.0 834839 0.3679
0.3711 234.0 838422 0.3672
0.3768 235.0 842005 0.3672
0.3796 236.0 845588 0.3656
0.3701 237.0 849171 0.3658
0.3691 238.0 852754 0.3675
0.3695 239.0 856337 0.3651
0.3703 240.0 859920 0.3646
0.3562 241.0 863503 0.3635
0.3663 242.0 867086 0.3646
0.3667 243.0 870669 0.3655
0.3753 244.0 874252 0.3662
0.372 245.0 877835 0.3648
0.3764 246.0 881418 0.3654
0.381 247.0 885001 0.3643
0.3695 248.0 888584 0.3639
0.3463 249.0 892167 0.3657
0.3567 250.0 895750 0.3638
0.3733 251.0 899333 0.3621
0.3547 252.0 902916 0.3627
0.3428 253.0 906499 0.3642
0.3646 254.0 910082 0.3628
0.361 255.0 913665 0.3629
0.3672 256.0 917248 0.3624
0.3573 257.0 920831 0.3608
0.3662 258.0 924414 0.3623
0.3729 259.0 927997 0.3640
0.3601 260.0 931580 0.3630
0.3754 261.0 935163 0.3617
0.3672 262.0 938746 0.3625
0.3384 263.0 942329 0.3618
0.3625 264.0 945912 0.3619
0.3662 265.0 949495 0.3614
0.3492 266.0 953078 0.3621
0.3586 267.0 956661 0.3608
0.3636 268.0 960244 0.3619
0.3435 269.0 963827 0.3606
0.3787 270.0 967410 0.3614
0.353 271.0 970993 0.3613
0.3549 272.0 974576 0.3610
0.3638 273.0 978159 0.3612
0.3732 274.0 981742 0.3610
0.376 275.0 985325 0.3603
0.3719 276.0 988908 0.3608
0.3405 277.0 992491 0.3579
0.3693 278.0 996074 0.3597
0.3657 279.0 999657 0.3580
0.3693 280.0 1003240 0.3596
0.3684 281.0 1006823 0.3600
0.3725 282.0 1010406 0.3595
0.3565 283.0 1013989 0.3596
0.3648 284.0 1017572 0.3579
0.3598 285.0 1021155 0.3581
0.3486 286.0 1024738 0.3593
0.3453 287.0 1028321 0.3588
0.3479 288.0 1031904 0.3599
0.3547 289.0 1035487 0.3572
0.3628 290.0 1039070 0.3575
0.3545 291.0 1042653 0.3583
0.3391 292.0 1046236 0.3588
0.354 293.0 1049819 0.3575
0.3559 294.0 1053402 0.3579
0.3547 295.0 1056985 0.3576
0.3509 296.0 1060568 0.3576
0.3564 297.0 1064151 0.3583
0.3504 298.0 1067734 0.3577
0.3582 299.0 1071317 0.3577
0.3511 300.0 1074900 0.3565
0.3532 301.0 1078483 0.3575
0.3612 302.0 1082066 0.3571
0.3653 303.0 1085649 0.3558
0.3623 304.0 1089232 0.3565
0.3515 305.0 1092815 0.3565
0.3513 306.0 1096398 0.3565
0.3584 307.0 1099981 0.3569
0.3454 308.0 1103564 0.3551
0.3565 309.0 1107147 0.3559
0.3845 310.0 1110730 0.3541
0.358 311.0 1114313 0.3551
0.3388 312.0 1117896 0.3556
0.3494 313.0 1121479 0.3551
0.3643 314.0 1125062 0.3556
0.3457 315.0 1128645 0.3562
0.3603 316.0 1132228 0.3552
0.3628 317.0 1135811 0.3544
0.3491 318.0 1139394 0.3540
0.3482 319.0 1142977 0.3540
0.3506 320.0 1146560 0.3553
0.3559 321.0 1150143 0.3559
0.3478 322.0 1153726 0.3549
0.3469 323.0 1157309 0.3538
0.3482 324.0 1160892 0.3555
0.3605 325.0 1164475 0.3534
0.3545 326.0 1168058 0.3544
0.3521 327.0 1171641 0.3554
0.3577 328.0 1175224 0.3534
0.3429 329.0 1178807 0.3526
0.3522 330.0 1182390 0.3534
0.3632 331.0 1185973 0.3557
0.349 332.0 1189556 0.3526
0.3601 333.0 1193139 0.3530
0.3548 334.0 1196722 0.3536
0.3554 335.0 1200305 0.3515
0.3589 336.0 1203888 0.3533
0.3624 337.0 1207471 0.3512
0.3312 338.0 1211054 0.3520
0.3441 339.0 1214637 0.3516
0.3558 340.0 1218220 0.3534
0.3553 341.0 1221803 0.3519
0.3367 342.0 1225386 0.3525
0.3516 343.0 1228969 0.3533
0.3627 344.0 1232552 0.3548
0.3501 345.0 1236135 0.3515
0.3609 346.0 1239718 0.3518
0.3424 347.0 1243301 0.3520
0.3463 348.0 1246884 0.3520
0.3358 349.0 1250467 0.3529
0.3457 350.0 1254050 0.3521
0.3479 351.0 1257633 0.3506
0.3352 352.0 1261216 0.3516
0.3592 353.0 1264799 0.3517
0.363 354.0 1268382 0.3510
0.3553 355.0 1271965 0.3511
0.3553 356.0 1275548 0.3507
0.3413 357.0 1279131 0.3510
0.3707 358.0 1282714 0.3500
0.3654 359.0 1286297 0.3506
0.336 360.0 1289880 0.3496
0.3354 361.0 1293463 0.3514
0.3598 362.0 1297046 0.3505
0.3632 363.0 1300629 0.3487
0.3464 364.0 1304212 0.3508
0.3375 365.0 1307795 0.3508
0.3568 366.0 1311378 0.3506
0.3419 367.0 1314961 0.3514
0.3385 368.0 1318544 0.3487
0.3503 369.0 1322127 0.3499
0.3643 370.0 1325710 0.3504
0.3379 371.0 1329293 0.3481
0.3577 372.0 1332876 0.3488
0.3506 373.0 1336459 0.3501
0.3429 374.0 1340042 0.3481
0.3633 375.0 1343625 0.3483
0.3505 376.0 1347208 0.3490
0.3399 377.0 1350791 0.3487
0.3547 378.0 1354374 0.3485
0.3553 379.0 1357957 0.3486
0.3727 380.0 1361540 0.3484
0.3466 381.0 1365123 0.3488
0.363 382.0 1368706 0.3490
0.3565 383.0 1372289 0.3487
0.3457 384.0 1375872 0.3486
0.3375 385.0 1379455 0.3483
0.3677 386.0 1383038 0.3493
0.3623 387.0 1386621 0.3484
0.3345 388.0 1390204 0.3500
0.3564 389.0 1393787 0.3475
0.3608 390.0 1397370 0.3488
0.3335 391.0 1400953 0.3487
0.3453 392.0 1404536 0.3490
0.3528 393.0 1408119 0.3463
0.3534 394.0 1411702 0.3484
0.3304 395.0 1415285 0.3478
0.346 396.0 1418868 0.3481
0.3547 397.0 1422451 0.3481
0.3446 398.0 1426034 0.3490
0.352 399.0 1429617 0.3485
0.3537 400.0 1433200 0.3478
0.3629 401.0 1436783 0.3456
0.3307 402.0 1440366 0.3476
0.3532 403.0 1443949 0.3470
0.3372 404.0 1447532 0.3475
0.3483 405.0 1451115 0.3476
0.3352 406.0 1454698 0.3482
0.3611 407.0 1458281 0.3475
0.3593 408.0 1461864 0.3473
0.3603 409.0 1465447 0.3470
0.3393 410.0 1469030 0.3462
0.3497 411.0 1472613 0.3461
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0.3462 413.0 1479779 0.3465
0.3351 414.0 1483362 0.3466
0.3534 415.0 1486945 0.3453
0.3355 416.0 1490528 0.3480
0.3475 417.0 1494111 0.3463
0.36 418.0 1497694 0.3471
0.3579 419.0 1501277 0.3473
0.3323 420.0 1504860 0.3466
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0.346 426.0 1526358 0.3461
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0.3397 437.0 1565771 0.3453
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0.3551 439.0 1572937 0.3461
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0.3491 441.0 1580103 0.3457
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0.3328 444.0 1590852 0.3467
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0.3327 447.0 1601601 0.3453
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0.3409 450.0 1612350 0.3455
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0.3468 452.0 1619516 0.3430
0.3376 453.0 1623099 0.3442
0.3394 454.0 1626682 0.3437
0.3401 455.0 1630265 0.3440
0.3535 456.0 1633848 0.3441
0.3299 457.0 1637431 0.3455
0.3409 458.0 1641014 0.3445
0.3342 459.0 1644597 0.3459
0.3402 460.0 1648180 0.3448
0.3466 461.0 1651763 0.3447
0.3521 462.0 1655346 0.3435
0.3541 463.0 1658929 0.3448
0.3528 464.0 1662512 0.3435
0.3559 465.0 1666095 0.3436
0.3608 466.0 1669678 0.3434
0.3406 467.0 1673261 0.3441
0.3276 468.0 1676844 0.3453
0.35 469.0 1680427 0.3438
0.3627 470.0 1684010 0.3432
0.3119 471.0 1687593 0.3431
0.3451 472.0 1691176 0.3441
0.3588 473.0 1694759 0.3436
0.3383 474.0 1698342 0.3439
0.342 475.0 1701925 0.3453
0.3234 476.0 1705508 0.3444
0.3628 477.0 1709091 0.3441
0.3223 478.0 1712674 0.3419
0.3474 479.0 1716257 0.3449
0.3275 480.0 1719840 0.3439
0.323 481.0 1723423 0.3433
0.3465 482.0 1727006 0.3434
0.3464 483.0 1730589 0.3431
0.3415 484.0 1734172 0.3431
0.3333 485.0 1737755 0.3425
0.3373 486.0 1741338 0.3423
0.3471 487.0 1744921 0.3435
0.3384 488.0 1748504 0.3434
0.3419 489.0 1752087 0.3443
0.3234 490.0 1755670 0.3432
0.3238 491.0 1759253 0.3425
0.356 492.0 1762836 0.3430
0.3509 493.0 1766419 0.3436
0.3381 494.0 1770002 0.3431
0.3555 495.0 1773585 0.3431
0.3312 496.0 1777168 0.3435
0.3396 497.0 1780751 0.3446
0.3404 498.0 1784334 0.3421
0.3293 499.0 1787917 0.3421
0.3224 500.0 1791500 0.3434
0.3653 501.0 1795083 0.3424
0.3567 502.0 1798666 0.3424
0.3341 503.0 1802249 0.3435
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Framework versions

  • Transformers 4.39.0.dev0
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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