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JEdward7777
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delivery_truck_classification

Image Classification
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swin
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update model card README.md

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@@ -66,46 +66,46 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.8 | 3 | 1.7556 | 0.2037 |
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- | No log | 1.8 | 6 | 1.5833 | 0.3704 |
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- | No log | 2.8 | 9 | 1.3483 | 0.5926 |
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- | No log | 3.8 | 12 | 1.1101 | 0.6667 |
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- | No log | 4.8 | 15 | 0.9116 | 0.7222 |
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- | No log | 5.8 | 18 | 0.7632 | 0.7407 |
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- | 1.7322 | 6.8 | 21 | 0.6118 | 0.7963 |
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- | 1.7322 | 7.8 | 24 | 0.5017 | 0.8519 |
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- | 1.7322 | 8.8 | 27 | 0.4241 | 0.8889 |
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- | 1.7322 | 9.8 | 30 | 0.3522 | 0.8704 |
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- | 1.7322 | 10.8 | 33 | 0.2918 | 0.9259 |
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- | 1.7322 | 11.8 | 36 | 0.2659 | 0.9259 |
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- | 1.7322 | 12.8 | 39 | 0.2587 | 0.9444 |
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- | 0.7462 | 13.8 | 42 | 0.2063 | 0.9259 |
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- | 0.7462 | 14.8 | 45 | 0.1870 | 0.9259 |
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- | 0.7462 | 15.8 | 48 | 0.1739 | 0.9630 |
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- | 0.7462 | 16.8 | 51 | 0.2043 | 0.9259 |
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- | 0.7462 | 17.8 | 54 | 0.1897 | 0.9259 |
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- | 0.7462 | 18.8 | 57 | 0.1764 | 0.9444 |
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- | 0.4232 | 19.8 | 60 | 0.1587 | 0.9444 |
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- | 0.4232 | 20.8 | 63 | 0.1556 | 0.9630 |
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- | 0.4232 | 21.8 | 66 | 0.1516 | 0.9630 |
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- | 0.4232 | 22.8 | 69 | 0.1264 | 0.9630 |
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- | 0.4232 | 23.8 | 72 | 0.1180 | 0.9630 |
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- | 0.4232 | 24.8 | 75 | 0.1110 | 0.9630 |
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- | 0.4232 | 25.8 | 78 | 0.1232 | 0.9630 |
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- | 0.3571 | 26.8 | 81 | 0.1169 | 0.9815 |
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- | 0.3571 | 27.8 | 84 | 0.1051 | 0.9815 |
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- | 0.3571 | 28.8 | 87 | 0.0986 | 0.9630 |
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- | 0.3571 | 29.8 | 90 | 0.0937 | 0.9630 |
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- | 0.3571 | 30.8 | 93 | 0.0931 | 0.9630 |
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- | 0.3571 | 31.8 | 96 | 0.0932 | 0.9630 |
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- | 0.3571 | 32.8 | 99 | 0.0941 | 0.9630 |
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- | 0.3239 | 33.8 | 102 | 0.0920 | 0.9630 |
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- | 0.3239 | 34.8 | 105 | 0.0851 | 0.9630 |
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- | 0.3239 | 35.8 | 108 | 0.0828 | 0.9630 |
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- | 0.3239 | 36.8 | 111 | 0.0810 | 0.9630 |
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- | 0.3239 | 37.8 | 114 | 0.0801 | 0.9630 |
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- | 0.3239 | 38.8 | 117 | 0.0804 | 0.9630 |
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- | 0.3111 | 39.8 | 120 | 0.0807 | 0.9630 |
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  ### Framework versions
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.8 | 3 | 0.1169 | 0.9815 |
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+ | No log | 1.8 | 6 | 0.1169 | 0.9815 |
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+ | No log | 2.8 | 9 | 0.1169 | 0.9815 |
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+ | No log | 3.8 | 12 | 0.1169 | 0.9815 |
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+ | No log | 4.8 | 15 | 0.1169 | 0.9815 |
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+ | No log | 5.8 | 18 | 0.1169 | 0.9815 |
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+ | 0.3448 | 6.8 | 21 | 0.1169 | 0.9815 |
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+ | 0.3448 | 7.8 | 24 | 0.1169 | 0.9815 |
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+ | 0.3448 | 8.8 | 27 | 0.1169 | 0.9815 |
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+ | 0.3448 | 9.8 | 30 | 0.1169 | 0.9815 |
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+ | 0.3448 | 10.8 | 33 | 0.1169 | 0.9815 |
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+ | 0.3448 | 11.8 | 36 | 0.1169 | 0.9815 |
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+ | 0.3448 | 12.8 | 39 | 0.1169 | 0.9815 |
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+ | 0.3344 | 13.8 | 42 | 0.1169 | 0.9815 |
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+ | 0.3344 | 14.8 | 45 | 0.1169 | 0.9815 |
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+ | 0.3344 | 15.8 | 48 | 0.1169 | 0.9815 |
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+ | 0.3344 | 16.8 | 51 | 0.1169 | 0.9815 |
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+ | 0.3344 | 17.8 | 54 | 0.1169 | 0.9815 |
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+ | 0.3344 | 18.8 | 57 | 0.1169 | 0.9815 |
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+ | 0.3274 | 19.8 | 60 | 0.1169 | 0.9815 |
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+ | 0.3274 | 20.8 | 63 | 0.1169 | 0.9815 |
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+ | 0.3274 | 21.8 | 66 | 0.1169 | 0.9815 |
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+ | 0.3274 | 22.8 | 69 | 0.1169 | 0.9815 |
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+ | 0.3274 | 23.8 | 72 | 0.1169 | 0.9815 |
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+ | 0.3274 | 24.8 | 75 | 0.1169 | 0.9815 |
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+ | 0.3274 | 25.8 | 78 | 0.1169 | 0.9815 |
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+ | 0.3426 | 26.8 | 81 | 0.1169 | 0.9815 |
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+ | 0.3426 | 27.8 | 84 | 0.1169 | 0.9815 |
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+ | 0.3426 | 28.8 | 87 | 0.1169 | 0.9815 |
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+ | 0.3426 | 29.8 | 90 | 0.1169 | 0.9815 |
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+ | 0.3426 | 30.8 | 93 | 0.1169 | 0.9815 |
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+ | 0.3426 | 31.8 | 96 | 0.1169 | 0.9815 |
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+ | 0.3426 | 32.8 | 99 | 0.1169 | 0.9815 |
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+ | 0.3436 | 33.8 | 102 | 0.1169 | 0.9815 |
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+ | 0.3436 | 34.8 | 105 | 0.1169 | 0.9815 |
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+ | 0.3436 | 35.8 | 108 | 0.1169 | 0.9815 |
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+ | 0.3436 | 36.8 | 111 | 0.1169 | 0.9815 |
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+ | 0.3436 | 37.8 | 114 | 0.1169 | 0.9815 |
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+ | 0.3436 | 38.8 | 117 | 0.1169 | 0.9815 |
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+ | 0.3243 | 39.8 | 120 | 0.1169 | 0.9815 |
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  ### Framework versions