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JEdward7777
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delivery_truck_classification

Image Classification
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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9555555555555556
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [JEdward7777/delivery_truck_classification](https://huggingface.co/JEdward7777/delivery_truck_classification) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2060
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- - Accuracy: 0.9556
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  ## Model description
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@@ -66,51 +66,51 @@ 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 | 0.92 | 3 | 0.3269 | 0.9111 |
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- | No log | 1.92 | 6 | 0.2814 | 0.9333 |
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- | No log | 2.92 | 9 | 0.2625 | 0.9333 |
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- | No log | 3.92 | 12 | 0.2771 | 0.9333 |
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- | No log | 4.92 | 15 | 0.2419 | 0.9333 |
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- | No log | 5.92 | 18 | 0.2264 | 0.9111 |
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- | 0.3207 | 6.92 | 21 | 0.2530 | 0.9333 |
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- | 0.3207 | 7.92 | 24 | 0.2242 | 0.9333 |
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- | 0.3207 | 8.92 | 27 | 0.2060 | 0.9556 |
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- | 0.3207 | 9.92 | 30 | 0.1809 | 0.9556 |
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- | 0.3207 | 10.92 | 33 | 0.2070 | 0.9556 |
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- | 0.3207 | 11.92 | 36 | 0.1999 | 0.9556 |
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- | 0.3207 | 12.92 | 39 | 0.2013 | 0.9556 |
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- | 0.2066 | 13.92 | 42 | 0.2027 | 0.9556 |
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- | 0.2066 | 14.92 | 45 | 0.1809 | 0.9556 |
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- | 0.2066 | 15.92 | 48 | 0.1657 | 0.9556 |
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- | 0.2066 | 16.92 | 51 | 0.1728 | 0.9556 |
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- | 0.2066 | 17.92 | 54 | 0.2013 | 0.9556 |
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- | 0.2066 | 18.92 | 57 | 0.2226 | 0.9556 |
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- | 0.1894 | 19.92 | 60 | 0.2091 | 0.9556 |
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- | 0.1894 | 20.92 | 63 | 0.1940 | 0.9556 |
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- | 0.1894 | 21.92 | 66 | 0.1976 | 0.9556 |
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- | 0.1894 | 22.92 | 69 | 0.2232 | 0.9556 |
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- | 0.1894 | 23.92 | 72 | 0.2381 | 0.9556 |
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- | 0.1894 | 24.92 | 75 | 0.2405 | 0.9556 |
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- | 0.1894 | 25.92 | 78 | 0.2247 | 0.9556 |
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- | 0.1713 | 26.92 | 81 | 0.1895 | 0.9556 |
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- | 0.1713 | 27.92 | 84 | 0.1836 | 0.9556 |
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- | 0.1713 | 28.92 | 87 | 0.1985 | 0.9556 |
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- | 0.1713 | 29.92 | 90 | 0.2127 | 0.9556 |
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- | 0.1713 | 30.92 | 93 | 0.2098 | 0.9556 |
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- | 0.1713 | 31.92 | 96 | 0.2003 | 0.9556 |
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- | 0.1713 | 32.92 | 99 | 0.1849 | 0.9556 |
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- | 0.1428 | 33.92 | 102 | 0.1843 | 0.9556 |
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- | 0.1428 | 34.92 | 105 | 0.1900 | 0.9556 |
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- | 0.1428 | 35.92 | 108 | 0.1972 | 0.9556 |
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- | 0.1428 | 36.92 | 111 | 0.2023 | 0.9556 |
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- | 0.1428 | 37.92 | 114 | 0.2060 | 0.9556 |
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- | 0.1428 | 38.92 | 117 | 0.2093 | 0.9556 |
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- | 0.1443 | 39.92 | 120 | 0.2106 | 0.9556 |
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  ### Framework versions
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- - Transformers 4.22.2
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  - Pytorch 1.12.1+cu113
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- - Datasets 2.5.2
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- - Tokenizers 0.12.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 1.0
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  This model is a fine-tuned version of [JEdward7777/delivery_truck_classification](https://huggingface.co/JEdward7777/delivery_truck_classification) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0188
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+ - Accuracy: 1.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.86 | 3 | 0.1456 | 0.9574 |
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+ | No log | 1.86 | 6 | 0.0900 | 0.9787 |
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+ | No log | 2.86 | 9 | 0.0621 | 1.0 |
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+ | No log | 3.86 | 12 | 0.0635 | 0.9787 |
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+ | No log | 4.86 | 15 | 0.0535 | 0.9787 |
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+ | No log | 5.86 | 18 | 0.0663 | 0.9574 |
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+ | 0.3029 | 6.86 | 21 | 0.0492 | 0.9787 |
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+ | 0.3029 | 7.86 | 24 | 0.0559 | 0.9787 |
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+ | 0.3029 | 8.86 | 27 | 0.0664 | 0.9787 |
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+ | 0.3029 | 9.86 | 30 | 0.0643 | 0.9787 |
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+ | 0.3029 | 10.86 | 33 | 0.0558 | 0.9787 |
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+ | 0.3029 | 11.86 | 36 | 0.0365 | 1.0 |
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+ | 0.3029 | 12.86 | 39 | 0.0438 | 0.9787 |
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+ | 0.2212 | 13.86 | 42 | 0.0456 | 0.9787 |
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+ | 0.2212 | 14.86 | 45 | 0.0402 | 0.9787 |
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+ | 0.2212 | 15.86 | 48 | 0.0351 | 0.9787 |
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+ | 0.2212 | 16.86 | 51 | 0.0359 | 0.9787 |
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+ | 0.2212 | 17.86 | 54 | 0.0427 | 0.9787 |
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+ | 0.2212 | 18.86 | 57 | 0.0490 | 0.9574 |
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+ | 0.186 | 19.86 | 60 | 0.0396 | 0.9787 |
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+ | 0.186 | 20.86 | 63 | 0.0291 | 0.9787 |
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+ | 0.186 | 21.86 | 66 | 0.0152 | 1.0 |
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+ | 0.186 | 22.86 | 69 | 0.0142 | 1.0 |
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+ | 0.186 | 23.86 | 72 | 0.0178 | 1.0 |
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+ | 0.186 | 24.86 | 75 | 0.0176 | 1.0 |
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+ | 0.186 | 25.86 | 78 | 0.0151 | 1.0 |
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+ | 0.1751 | 26.86 | 81 | 0.0110 | 1.0 |
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+ | 0.1751 | 27.86 | 84 | 0.0121 | 1.0 |
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+ | 0.1751 | 28.86 | 87 | 0.0158 | 1.0 |
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+ | 0.1751 | 29.86 | 90 | 0.0250 | 1.0 |
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+ | 0.1751 | 30.86 | 93 | 0.0292 | 1.0 |
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+ | 0.1751 | 31.86 | 96 | 0.0260 | 1.0 |
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+ | 0.1751 | 32.86 | 99 | 0.0206 | 1.0 |
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+ | 0.1614 | 33.86 | 102 | 0.0181 | 1.0 |
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+ | 0.1614 | 34.86 | 105 | 0.0170 | 1.0 |
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+ | 0.1614 | 35.86 | 108 | 0.0170 | 1.0 |
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+ | 0.1614 | 36.86 | 111 | 0.0177 | 1.0 |
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+ | 0.1614 | 37.86 | 114 | 0.0188 | 1.0 |
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+ | 0.1614 | 38.86 | 117 | 0.0189 | 1.0 |
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+ | 0.1483 | 39.86 | 120 | 0.0188 | 1.0 |
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  ### Framework versions
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+ - Transformers 4.23.1
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  - Pytorch 1.12.1+cu113
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+ - Datasets 2.6.0
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+ - Tokenizers 0.13.1