generated_from_keras_callback

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AhamadShaik/SegFormer_RESIZE_LM

This model is a fine-tuned version of nvidia/mit-b0 on an unknown 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

Train Loss Train Dice Coef Train Iou Validation Loss Validation Dice Coef Validation Iou Train Lr Epoch
0.3496 0.3697 0.2435 0.2697 0.1141 0.0635 1e-04 0
0.1591 0.5600 0.4126 0.1768 0.3601 0.2345 1e-04 1
0.1295 0.6470 0.5014 0.1637 0.4628 0.3163 1e-04 2
0.1109 0.6903 0.5511 0.1319 0.5634 0.4072 1e-04 3
0.1018 0.7226 0.5858 0.0932 0.7480 0.6051 1e-04 4
0.0930 0.7373 0.6042 0.1618 0.5048 0.3614 1e-04 5
0.0878 0.7534 0.6255 0.1023 0.7076 0.5637 1e-04 6
0.0842 0.7585 0.6310 0.0878 0.7726 0.6384 1e-04 7
0.0798 0.7733 0.6475 0.0966 0.7434 0.5996 1e-04 8
0.0765 0.7716 0.6487 0.1073 0.7157 0.5657 1e-04 9
0.0701 0.7974 0.6794 0.1049 0.7190 0.5811 1e-04 10
0.0675 0.8020 0.6854 0.1319 0.6935 0.5427 1e-04 11
0.0662 0.8108 0.6957 0.1593 0.6269 0.4826 1e-04 12
0.0679 0.7980 0.6817 0.0483 0.8809 0.7881 5e-06 13
0.0613 0.8173 0.7069 0.0467 0.8827 0.7910 5e-06 14
0.0595 0.8160 0.7064 0.0475 0.8810 0.7883 5e-06 15
0.0589 0.8197 0.7115 0.0460 0.8835 0.7922 5e-06 16
0.0576 0.8214 0.7134 0.0459 0.8838 0.7927 5e-06 17
0.0577 0.8161 0.7082 0.0458 0.8838 0.7927 5e-06 18
0.0564 0.8310 0.7242 0.0461 0.8830 0.7915 5e-06 19
0.0567 0.8330 0.7271 0.0455 0.8828 0.7910 5e-06 20
0.0562 0.8252 0.7182 0.0455 0.8850 0.7947 5e-06 21
0.0560 0.8245 0.7188 0.0461 0.8830 0.7916 5e-06 22
0.0554 0.8259 0.7208 0.0463 0.8811 0.7885 5e-06 23
0.0548 0.8254 0.7212 0.0459 0.8832 0.7919 5e-06 24
0.0552 0.8331 0.7281 0.0452 0.8833 0.7920 5e-06 25
0.0534 0.8391 0.7355 0.0438 0.8872 0.7982 5e-06 26
0.0538 0.8350 0.7310 0.0447 0.8846 0.7941 5e-06 27
0.0543 0.8443 0.7406 0.0468 0.8803 0.7877 5e-06 28
0.0535 0.8350 0.7324 0.0459 0.8833 0.7919 5e-06 29
0.0529 0.8404 0.7376 0.0460 0.8820 0.7900 5e-06 30
0.0525 0.8396 0.7379 0.0444 0.8855 0.7954 5e-06 31
0.0525 0.8347 0.7322 0.0458 0.8833 0.7921 2.5e-07 32
0.0524 0.8414 0.7376 0.0453 0.8840 0.7930 2.5e-07 33
0.0524 0.8406 0.7372 0.0446 0.8842 0.7935 2.5e-07 34
0.0522 0.8408 0.7385 0.0456 0.8838 0.7927 2.5e-07 35
0.0521 0.8484 0.7454 0.0453 0.8839 0.7929 2.5e-07 36
0.0521 0.8503 0.7481 0.0459 0.8832 0.7919 1.25e-08 37
0.0521 0.8370 0.7344 0.0451 0.8845 0.7939 1.25e-08 38
0.0524 0.8484 0.7452 0.0456 0.8837 0.7927 1.25e-08 39
0.0529 0.8410 0.7388 0.0448 0.8848 0.7944 1.25e-08 40
0.0519 0.8402 0.7391 0.0444 0.8852 0.7951 1.25e-08 41
0.0518 0.8349 0.7331 0.0448 0.8850 0.7948 6.25e-10 42
0.0523 0.8406 0.7381 0.0452 0.8835 0.7922 6.25e-10 43
0.0519 0.8427 0.7402 0.0449 0.8854 0.7952 6.25e-10 44
0.0523 0.8445 0.7413 0.0453 0.8839 0.7930 6.25e-10 45
0.0519 0.8445 0.7434 0.0446 0.8858 0.7959 6.25e-10 46
0.0519 0.8388 0.7368 0.0447 0.8839 0.7929 1e-10 47
0.0518 0.8456 0.7438 0.0448 0.8847 0.7943 1e-10 48
0.0521 0.8447 0.7433 0.0442 0.8859 0.7961 1e-10 49
0.0520 0.8382 0.7359 0.0453 0.8838 0.7929 1e-10 50
0.0523 0.8469 0.7463 0.0448 0.8852 0.7951 1e-10 51
0.0515 0.8375 0.7362 0.0459 0.8825 0.7909 1e-10 52
0.0520 0.8447 0.7432 0.0443 0.8854 0.7954 1e-10 53
0.0523 0.8359 0.7337 0.0442 0.8860 0.7962 1e-10 54
0.0523 0.8352 0.7333 0.0440 0.8867 0.7974 1e-10 55
0.0523 0.8376 0.7347 0.0456 0.8846 0.7940 1e-10 56
0.0520 0.8466 0.7441 0.0448 0.8856 0.7956 1e-10 57
0.0524 0.8382 0.7357 0.0433 0.8875 0.7987 1e-10 58
0.0521 0.8431 0.7403 0.0450 0.8853 0.7951 1e-10 59
0.0524 0.8415 0.7389 0.0453 0.8846 0.7940 1e-10 60
0.0517 0.8436 0.7423 0.0444 0.8853 0.7951 1e-10 61
0.0523 0.8467 0.7443 0.0455 0.8840 0.7932 1e-10 62
0.0522 0.8470 0.7434 0.0445 0.8859 0.7961 1e-10 63
0.0520 0.8375 0.7356 0.0446 0.8857 0.7958 1e-10 64
0.0515 0.8416 0.7396 0.0440 0.8862 0.7966 1e-10 65
0.0526 0.8364 0.7346 0.0449 0.8848 0.7944 1e-10 66
0.0524 0.8461 0.7438 0.0452 0.8838 0.7928 1e-10 67
0.0523 0.8374 0.7361 0.0453 0.8849 0.7947 1e-10 68
0.0520 0.8370 0.7355 0.0446 0.8852 0.7950 1e-10 69
0.0522 0.8487 0.7473 0.0455 0.8835 0.7923 1e-10 70
0.0520 0.8446 0.7429 0.0463 0.8828 0.7911 1e-10 71
0.0520 0.8364 0.7345 0.0454 0.8841 0.7933 1e-10 72
0.0528 0.8468 0.7431 0.0452 0.8846 0.7939 1e-10 73
0.0518 0.8455 0.7441 0.0449 0.8846 0.7940 1e-10 74
0.0519 0.8351 0.7330 0.0445 0.8852 0.7948 1e-10 75
0.0521 0.8423 0.7406 0.0453 0.8849 0.7945 1e-10 76
0.0525 0.8467 0.7449 0.0456 0.8836 0.7925 1e-10 77
0.0522 0.8436 0.7397 0.0445 0.8847 0.7942 1e-10 78
0.0521 0.8423 0.7393 0.0443 0.8855 0.7954 1e-10 79
0.0513 0.8439 0.7415 0.0454 0.8837 0.7926 1e-10 80
0.0520 0.8433 0.7422 0.0445 0.8843 0.7937 1e-10 81
0.0522 0.8417 0.7396 0.0451 0.8844 0.7939 1e-10 82
0.0520 0.8492 0.7471 0.0449 0.8847 0.7943 1e-10 83
0.0526 0.8384 0.7360 0.0445 0.8862 0.7968 1e-10 84
0.0520 0.8477 0.7457 0.0447 0.8844 0.7938 1e-10 85
0.0518 0.8410 0.7387 0.0452 0.8848 0.7944 1e-10 86
0.0523 0.8443 0.7421 0.0443 0.8865 0.7971 1e-10 87
0.0519 0.8429 0.7402 0.0465 0.8813 0.7891 1e-10 88
0.0526 0.8328 0.7291 0.0446 0.8853 0.7952 1e-10 89
0.0528 0.8435 0.7408 0.0449 0.8855 0.7954 1e-10 90
0.0521 0.8417 0.7399 0.0441 0.8859 0.7961 1e-10 91
0.0516 0.8430 0.7422 0.0455 0.8830 0.7915 1e-10 92
0.0523 0.8499 0.7491 0.0457 0.8832 0.7919 1e-10 93
0.0525 0.8399 0.7371 0.0452 0.8846 0.7940 1e-10 94
0.0517 0.8433 0.7401 0.0455 0.8835 0.7924 1e-10 95
0.0524 0.8417 0.7398 0.0453 0.8831 0.7917 1e-10 96
0.0517 0.8410 0.7390 0.0440 0.8870 0.7979 1e-10 97
0.0525 0.8394 0.7373 0.0451 0.8846 0.7941 1e-10 98
0.0520 0.8435 0.7409 0.0454 0.8836 0.7926 1e-10 99

Framework versions