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mae-vit-base-patch32-224-ct

This model is a fine-tuned version of google/vit-base-patch32-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3803

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: 0.00015
  • train_batch_size: 256
  • eval_batch_size: 256
  • seed: 1337
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 1200.0

Training results

Training Loss Epoch Step Validation Loss
1.1257 1.0 51 1.1119
1.0507 2.0 102 1.0434
1.0046 3.0 153 0.9988
0.9761 4.0 204 0.9725
0.9572 5.0 255 0.9529
0.9357 6.0 306 0.9304
0.9128 7.0 357 0.9100
0.9037 8.0 408 0.9004
0.8984 9.0 459 0.8941
0.8904 10.0 510 0.8896
0.8846 11.0 561 0.8802
0.8748 12.0 612 0.8775
0.8692 13.0 663 0.8685
0.8656 14.0 714 0.8665
0.8634 15.0 765 0.8607
0.8565 16.0 816 0.8561
0.8555 17.0 867 0.8548
0.8521 18.0 918 0.8464
0.8478 19.0 969 0.8449
0.847 20.0 1020 0.8455
0.842 21.0 1071 0.8378
0.8385 22.0 1122 0.8358
0.8319 23.0 1173 0.8332
0.8267 24.0 1224 0.8347
0.8266 25.0 1275 0.8247
0.8242 26.0 1326 0.8242
0.8215 27.0 1377 0.8192
0.8171 28.0 1428 0.8213
0.8176 29.0 1479 0.8160
0.8122 30.0 1530 0.8128
0.8107 31.0 1581 0.8036
0.8069 32.0 1632 0.8069
0.8081 33.0 1683 0.8023
0.8043 34.0 1734 0.8048
0.8071 35.0 1785 0.8082
0.8017 36.0 1836 0.7971
0.7965 37.0 1887 0.7953
0.7953 38.0 1938 0.8112
0.7979 39.0 1989 0.7955
0.7887 40.0 2040 0.7966
0.7866 41.0 2091 0.7879
0.7862 42.0 2142 0.7828
0.7836 43.0 2193 0.7865
0.7851 44.0 2244 0.7830
0.7813 45.0 2295 0.7840
0.78 46.0 2346 0.7749
0.779 47.0 2397 0.7825
0.7762 48.0 2448 0.7712
0.7676 49.0 2499 0.7675
0.7638 50.0 2550 0.7645
0.7826 51.0 2601 0.7879
0.7728 52.0 2652 0.7730
0.7629 53.0 2703 0.7606
0.7819 54.0 2754 0.7718
0.7802 55.0 2805 0.7809
0.7632 56.0 2856 0.7577
0.7567 57.0 2907 0.7654
0.7564 58.0 2958 0.7574
0.7535 59.0 3009 0.7555
0.75 60.0 3060 0.7484
0.7512 61.0 3111 0.7487
0.7493 62.0 3162 0.7462
0.742 63.0 3213 0.7450
0.7469 64.0 3264 0.7464
0.7449 65.0 3315 0.7393
0.7321 66.0 3366 0.7425
0.7411 67.0 3417 0.7391
0.7394 68.0 3468 0.7413
0.7301 69.0 3519 0.7344
0.7208 70.0 3570 0.7256
0.7211 71.0 3621 0.7225
0.7273 72.0 3672 0.7264
0.7267 73.0 3723 0.7221
0.7222 74.0 3774 0.7256
0.7175 75.0 3825 0.7202
0.7174 76.0 3876 0.7149
0.7143 77.0 3927 0.7127
0.7106 78.0 3978 0.7061
0.7188 79.0 4029 0.7153
0.7103 80.0 4080 0.7086
0.7055 81.0 4131 0.7098
0.7026 82.0 4182 0.7075
0.7191 83.0 4233 0.7127
0.7027 84.0 4284 0.7172
0.6981 85.0 4335 0.7070
0.7064 86.0 4386 0.7029
0.6943 87.0 4437 0.7046
0.7025 88.0 4488 0.7036
0.6959 89.0 4539 0.7094
0.6988 90.0 4590 0.6917
0.6912 91.0 4641 0.6926
0.689 92.0 4692 0.6881
0.687 93.0 4743 0.6866
0.6867 94.0 4794 0.6873
0.6832 95.0 4845 0.6820
0.6863 96.0 4896 0.6809
0.6908 97.0 4947 0.6792
0.6891 98.0 4998 0.6796
0.6803 99.0 5049 0.6793
0.6755 100.0 5100 0.6738
0.6735 101.0 5151 0.6750
0.6727 102.0 5202 0.6729
0.6695 103.0 5253 0.6734
0.6678 104.0 5304 0.6702
0.671 105.0 5355 0.6720
0.6654 106.0 5406 0.6686
0.669 107.0 5457 0.6683
0.6628 108.0 5508 0.6639
0.6655 109.0 5559 0.6663
0.6637 110.0 5610 0.6651
0.6643 111.0 5661 0.6639
0.6607 112.0 5712 0.6561
0.6598 113.0 5763 0.6591
0.6589 114.0 5814 0.6610
0.6566 115.0 5865 0.6566
0.6706 116.0 5916 0.6749
0.6688 117.0 5967 0.6670
0.6657 118.0 6018 0.6599
0.6611 119.0 6069 0.6567
0.6528 120.0 6120 0.6591
0.652 121.0 6171 0.6566
0.6488 122.0 6222 0.6528
0.6538 123.0 6273 0.6558
0.6457 124.0 6324 0.6509
0.643 125.0 6375 0.6462
0.6433 126.0 6426 0.6459
0.6451 127.0 6477 0.6454
0.6413 128.0 6528 0.6441
0.6407 129.0 6579 0.6409
0.6381 130.0 6630 0.6422
0.6408 131.0 6681 0.6432
0.6404 132.0 6732 0.6408
0.6412 133.0 6783 0.6354
0.6348 134.0 6834 0.6350
0.6307 135.0 6885 0.6389
0.639 136.0 6936 0.6417
0.6319 137.0 6987 0.6353
0.6306 138.0 7038 0.6385
0.6307 139.0 7089 0.6412
0.6343 140.0 7140 0.6308
0.6289 141.0 7191 0.6337
0.6298 142.0 7242 0.6342
0.6284 143.0 7293 0.6287
0.624 144.0 7344 0.6305
0.6266 145.0 7395 0.6338
0.6253 146.0 7446 0.6281
0.6204 147.0 7497 0.6241
0.6232 148.0 7548 0.6222
0.6213 149.0 7599 0.6201
0.6225 150.0 7650 0.6237
0.6228 151.0 7701 0.6193
0.6191 152.0 7752 0.6200
0.6198 153.0 7803 0.6229
0.6183 154.0 7854 0.6213
0.6181 155.0 7905 0.6213
0.6168 156.0 7956 0.6164
0.6156 157.0 8007 0.6160
0.6125 158.0 8058 0.6153
0.6126 159.0 8109 0.6151
0.6115 160.0 8160 0.6163
0.611 161.0 8211 0.6167
0.6099 162.0 8262 0.6083
0.6089 163.0 8313 0.6104
0.6091 164.0 8364 0.6140
0.6105 165.0 8415 0.6122
0.61 166.0 8466 0.6106
0.6104 167.0 8517 0.6062
0.6067 168.0 8568 0.6095
0.6056 169.0 8619 0.6067
0.607 170.0 8670 0.6091
0.6032 171.0 8721 0.6041
0.6038 172.0 8772 0.6104
0.605 173.0 8823 0.6068
0.6036 174.0 8874 0.6005
0.6035 175.0 8925 0.6055
0.6026 176.0 8976 0.6014
0.6012 177.0 9027 0.6029
0.5945 178.0 9078 0.5967
0.6011 179.0 9129 0.5921
0.5929 180.0 9180 0.5991
0.5981 181.0 9231 0.5954
0.6011 182.0 9282 0.6007
0.5977 183.0 9333 0.6013
0.5947 184.0 9384 0.6023
0.59 185.0 9435 0.5968
0.5924 186.0 9486 0.5987
0.5906 187.0 9537 0.5915
0.5928 188.0 9588 0.5877
0.5849 189.0 9639 0.5911
0.5913 190.0 9690 0.5954
0.5863 191.0 9741 0.5906
0.588 192.0 9792 0.5942
0.5906 193.0 9843 0.5924
0.5927 194.0 9894 0.5911
0.5857 195.0 9945 0.5852
0.5859 196.0 9996 0.5910
0.5775 197.0 10047 0.5853
0.586 198.0 10098 0.5877
0.5853 199.0 10149 0.5848
0.5824 200.0 10200 0.5854
0.5797 201.0 10251 0.5834
0.5857 202.0 10302 0.5792
0.5863 203.0 10353 0.5824
0.5826 204.0 10404 0.5838
0.579 205.0 10455 0.5808
0.5758 206.0 10506 0.5810
0.5798 207.0 10557 0.5782
0.576 208.0 10608 0.5818
0.5717 209.0 10659 0.5826
0.5774 210.0 10710 0.5800
0.5724 211.0 10761 0.5813
0.5706 212.0 10812 0.5755
0.5737 213.0 10863 0.5788
0.5791 214.0 10914 0.5769
0.5712 215.0 10965 0.5767
0.567 216.0 11016 0.5790
0.5671 217.0 11067 0.5734
0.5733 218.0 11118 0.5722
0.5673 219.0 11169 0.5806
0.5713 220.0 11220 0.5764
0.5669 221.0 11271 0.5694
0.5669 222.0 11322 0.5749
0.5665 223.0 11373 0.5732
0.5676 224.0 11424 0.5676
0.5621 225.0 11475 0.5677
0.5623 226.0 11526 0.5715
0.5695 227.0 11577 0.5676
0.5657 228.0 11628 0.5667
0.565 229.0 11679 0.5644
0.5617 230.0 11730 0.5650
0.5587 231.0 11781 0.5637
0.5591 232.0 11832 0.5652
0.5607 233.0 11883 0.5648
0.559 234.0 11934 0.5681
0.5601 235.0 11985 0.5637
0.5605 236.0 12036 0.5697
0.5555 237.0 12087 0.5593
0.5602 238.0 12138 0.5683
0.5647 239.0 12189 0.5629
0.5575 240.0 12240 0.5611
0.5577 241.0 12291 0.5588
0.5514 242.0 12342 0.5584
0.5581 243.0 12393 0.5566
0.555 244.0 12444 0.5563
0.5571 245.0 12495 0.5541
0.5549 246.0 12546 0.5541
0.5521 247.0 12597 0.5521
0.55 248.0 12648 0.5567
0.5518 249.0 12699 0.5559
0.5522 250.0 12750 0.5536
0.5481 251.0 12801 0.5504
0.5516 252.0 12852 0.5563
0.5524 253.0 12903 0.5503
0.5582 254.0 12954 0.5519
0.5514 255.0 13005 0.5504
0.5498 256.0 13056 0.5520
0.5481 257.0 13107 0.5540
0.551 258.0 13158 0.5503
0.5495 259.0 13209 0.5491
0.5483 260.0 13260 0.5461
0.5468 261.0 13311 0.5586
0.5454 262.0 13362 0.5495
0.5447 263.0 13413 0.5455
0.5475 264.0 13464 0.5511
0.5439 265.0 13515 0.5453
0.542 266.0 13566 0.5477
0.5437 267.0 13617 0.5502
0.5452 268.0 13668 0.5432
0.5397 269.0 13719 0.5443
0.5424 270.0 13770 0.5410
0.5391 271.0 13821 0.5420
0.5368 272.0 13872 0.5402
0.5387 273.0 13923 0.5401
0.5362 274.0 13974 0.5414
0.5374 275.0 14025 0.5418
0.5375 276.0 14076 0.5415
0.5427 277.0 14127 0.5436
0.5382 278.0 14178 0.5366
0.5341 279.0 14229 0.5411
0.5348 280.0 14280 0.5377
0.5339 281.0 14331 0.5393
0.5359 282.0 14382 0.5359
0.536 283.0 14433 0.5368
0.5362 284.0 14484 0.5384
0.532 285.0 14535 0.5346
0.5298 286.0 14586 0.5376
0.5352 287.0 14637 0.5373
0.5344 288.0 14688 0.5359
0.5399 289.0 14739 0.5427
0.5329 290.0 14790 0.5349
0.531 291.0 14841 0.5321
0.5317 292.0 14892 0.5361
0.5303 293.0 14943 0.5296
0.5291 294.0 14994 0.5312
0.5335 295.0 15045 0.5244
0.5309 296.0 15096 0.5252
0.5251 297.0 15147 0.5310
0.5266 298.0 15198 0.5301
0.5279 299.0 15249 0.5308
0.5261 300.0 15300 0.5250
0.5214 301.0 15351 0.5252
0.5269 302.0 15402 0.5306
0.5229 303.0 15453 0.5264
0.5234 304.0 15504 0.5263
0.5271 305.0 15555 0.5280
0.525 306.0 15606 0.5233
0.5216 307.0 15657 0.5211
0.5247 308.0 15708 0.5246
0.5203 309.0 15759 0.5279
0.5201 310.0 15810 0.5246
0.5254 311.0 15861 0.5306
0.5166 312.0 15912 0.5224
0.525 313.0 15963 0.5192
0.5224 314.0 16014 0.5247
0.5195 315.0 16065 0.5230
0.5189 316.0 16116 0.5239
0.5226 317.0 16167 0.5180
0.5166 318.0 16218 0.5197
0.5159 319.0 16269 0.5156
0.5156 320.0 16320 0.5204
0.5179 321.0 16371 0.5215
0.5194 322.0 16422 0.5211
0.519 323.0 16473 0.5212
0.5112 324.0 16524 0.5175
0.5163 325.0 16575 0.5225
0.5165 326.0 16626 0.5172
0.5104 327.0 16677 0.5200
0.51 328.0 16728 0.5156
0.5129 329.0 16779 0.5160
0.5084 330.0 16830 0.5207
0.5159 331.0 16881 0.5147
0.5126 332.0 16932 0.5159
0.5132 333.0 16983 0.5156
0.5092 334.0 17034 0.5151
0.5116 335.0 17085 0.5147
0.5113 336.0 17136 0.5121
0.5076 337.0 17187 0.5101
0.5106 338.0 17238 0.5111
0.5117 339.0 17289 0.5094
0.5086 340.0 17340 0.5132
0.5034 341.0 17391 0.5162
0.5061 342.0 17442 0.5142
0.5101 343.0 17493 0.5136
0.5042 344.0 17544 0.5135
0.5091 345.0 17595 0.5083
0.5095 346.0 17646 0.5112
0.5058 347.0 17697 0.5121
0.504 348.0 17748 0.5082
0.5016 349.0 17799 0.5075
0.5042 350.0 17850 0.5090
0.5036 351.0 17901 0.5089
0.5045 352.0 17952 0.5095
0.5067 353.0 18003 0.5087
0.5026 354.0 18054 0.5064
0.5001 355.0 18105 0.5055
0.5036 356.0 18156 0.5057
0.5012 357.0 18207 0.5083
0.5031 358.0 18258 0.5110
0.5021 359.0 18309 0.5128
0.4973 360.0 18360 0.5014
0.4988 361.0 18411 0.5028
0.5013 362.0 18462 0.5035
0.5001 363.0 18513 0.5040
0.4972 364.0 18564 0.5056
0.4994 365.0 18615 0.5070
0.5005 366.0 18666 0.5070
0.4993 367.0 18717 0.5053
0.4975 368.0 18768 0.5036
0.4967 369.0 18819 0.5026
0.4968 370.0 18870 0.5011
0.498 371.0 18921 0.4990
0.5022 372.0 18972 0.5032
0.4959 373.0 19023 0.4972
0.4921 374.0 19074 0.4967
0.4936 375.0 19125 0.4967
0.496 376.0 19176 0.5000
0.4941 377.0 19227 0.4980
0.4937 378.0 19278 0.4975
0.4979 379.0 19329 0.4975
0.4996 380.0 19380 0.4932
0.4961 381.0 19431 0.4983
0.4903 382.0 19482 0.4974
0.4899 383.0 19533 0.4953
0.4924 384.0 19584 0.4953
0.4895 385.0 19635 0.4964
0.4965 386.0 19686 0.5006
0.4896 387.0 19737 0.4938
0.497 388.0 19788 0.4956
0.4924 389.0 19839 0.4960
0.4904 390.0 19890 0.4972
0.5 391.0 19941 0.4958
0.4961 392.0 19992 0.4906
0.491 393.0 20043 0.4918
0.4878 394.0 20094 0.4954
0.4881 395.0 20145 0.4916
0.49 396.0 20196 0.4946
0.4881 397.0 20247 0.4924
0.4871 398.0 20298 0.4959
0.492 399.0 20349 0.4867
0.4883 400.0 20400 0.4891
0.4864 401.0 20451 0.4946
0.4898 402.0 20502 0.4922
0.4841 403.0 20553 0.4902
0.4879 404.0 20604 0.4921
0.4801 405.0 20655 0.4914
0.4877 406.0 20706 0.4882
0.4858 407.0 20757 0.4882
0.4856 408.0 20808 0.4872
0.4825 409.0 20859 0.4871
0.4865 410.0 20910 0.4853
0.4834 411.0 20961 0.4908
0.4815 412.0 21012 0.4847
0.4828 413.0 21063 0.4919
0.487 414.0 21114 0.4899
0.4842 415.0 21165 0.4876
0.4902 416.0 21216 0.4873
0.4809 417.0 21267 0.4913
0.4825 418.0 21318 0.4832
0.4797 419.0 21369 0.4872
0.4852 420.0 21420 0.4868
0.4879 421.0 21471 0.4833
0.4823 422.0 21522 0.4824
0.4729 423.0 21573 0.4793
0.4825 424.0 21624 0.4812
0.4739 425.0 21675 0.4831
0.4767 426.0 21726 0.4848
0.4806 427.0 21777 0.4858
0.4736 428.0 21828 0.4831
0.4857 429.0 21879 0.4785
0.4819 430.0 21930 0.4805
0.4767 431.0 21981 0.4845
0.4765 432.0 22032 0.4803
0.4785 433.0 22083 0.4826
0.4758 434.0 22134 0.4814
0.4677 435.0 22185 0.4815
0.4735 436.0 22236 0.4811
0.4764 437.0 22287 0.4749
0.4743 438.0 22338 0.4846
0.4736 439.0 22389 0.4825
0.4732 440.0 22440 0.4783
0.4706 441.0 22491 0.4810
0.4735 442.0 22542 0.4780
0.4796 443.0 22593 0.4881
0.4724 444.0 22644 0.4785
0.4701 445.0 22695 0.4753
0.4764 446.0 22746 0.4787
0.4729 447.0 22797 0.4824
0.4726 448.0 22848 0.4742
0.4736 449.0 22899 0.4775
0.4764 450.0 22950 0.4755
0.4701 451.0 23001 0.4755
0.4746 452.0 23052 0.4750
0.4727 453.0 23103 0.4731
0.4691 454.0 23154 0.4686
0.4673 455.0 23205 0.4761
0.4726 456.0 23256 0.4763
0.4726 457.0 23307 0.4807
0.4696 458.0 23358 0.4738
0.4689 459.0 23409 0.4727
0.4702 460.0 23460 0.4793
0.4692 461.0 23511 0.4696
0.4694 462.0 23562 0.4713
0.4628 463.0 23613 0.4747
0.4677 464.0 23664 0.4787
0.4673 465.0 23715 0.4682
0.4709 466.0 23766 0.4692
0.463 467.0 23817 0.4676
0.4654 468.0 23868 0.4696
0.4648 469.0 23919 0.4675
0.4642 470.0 23970 0.4700
0.4687 471.0 24021 0.4691
0.469 472.0 24072 0.4749
0.4692 473.0 24123 0.4672
0.4635 474.0 24174 0.4707
0.4635 475.0 24225 0.4696
0.4655 476.0 24276 0.4652
0.4633 477.0 24327 0.4702
0.4622 478.0 24378 0.4637
0.4571 479.0 24429 0.4678
0.4645 480.0 24480 0.4635
0.4654 481.0 24531 0.4655
0.4588 482.0 24582 0.4688
0.4608 483.0 24633 0.4639
0.4606 484.0 24684 0.4654
0.4624 485.0 24735 0.4661
0.4612 486.0 24786 0.4669
0.46 487.0 24837 0.4653
0.4623 488.0 24888 0.4688
0.4648 489.0 24939 0.4648
0.4602 490.0 24990 0.4620
0.4587 491.0 25041 0.4652
0.4627 492.0 25092 0.4694
0.4638 493.0 25143 0.4620
0.4565 494.0 25194 0.4653
0.4588 495.0 25245 0.4598
0.4568 496.0 25296 0.4617
0.4524 497.0 25347 0.4631
0.4635 498.0 25398 0.4640
0.4534 499.0 25449 0.4643
0.4599 500.0 25500 0.4663
0.4549 501.0 25551 0.4588
0.4595 502.0 25602 0.4661
0.46 503.0 25653 0.4626
0.4504 504.0 25704 0.4591
0.459 505.0 25755 0.4623
0.4582 506.0 25806 0.4617
0.4532 507.0 25857 0.4580
0.4555 508.0 25908 0.4615
0.4571 509.0 25959 0.4617
0.4561 510.0 26010 0.4579
0.4541 511.0 26061 0.4601
0.4534 512.0 26112 0.4627
0.4569 513.0 26163 0.4615
0.4583 514.0 26214 0.4527
0.4498 515.0 26265 0.4587
0.4511 516.0 26316 0.4552
0.4535 517.0 26367 0.4579
0.4551 518.0 26418 0.4543
0.4581 519.0 26469 0.4597
0.4573 520.0 26520 0.4540
0.4495 521.0 26571 0.4578
0.4532 522.0 26622 0.4605
0.4474 523.0 26673 0.4579
0.4504 524.0 26724 0.4563
0.4529 525.0 26775 0.4583
0.4475 526.0 26826 0.4616
0.4457 527.0 26877 0.4558
0.4532 528.0 26928 0.4584
0.4566 529.0 26979 0.4573
0.4546 530.0 27030 0.4563
0.4479 531.0 27081 0.4628
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Framework versions

  • Transformers 4.27.0.dev0
  • Pytorch 1.13.0
  • Datasets 2.8.0
  • Tokenizers 0.13.2
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