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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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@@ -31,7 +31,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0447
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  - Accuracy: 1.0
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  ## Model description
@@ -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 | 0.86 | 3 | 1.7166 | 0.2245 |
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- | No log | 1.86 | 6 | 1.5816 | 0.4082 |
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- | No log | 2.86 | 9 | 1.4084 | 0.5510 |
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- | No log | 3.86 | 12 | 1.1761 | 0.6327 |
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- | No log | 4.86 | 15 | 0.9245 | 0.7347 |
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- | No log | 5.86 | 18 | 0.6986 | 0.7959 |
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- | 1.608 | 6.86 | 21 | 0.5158 | 0.8367 |
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- | 1.608 | 7.86 | 24 | 0.3753 | 0.8776 |
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- | 1.608 | 8.86 | 27 | 0.3092 | 0.8980 |
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- | 1.608 | 9.86 | 30 | 0.2584 | 0.9388 |
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- | 1.608 | 10.86 | 33 | 0.2159 | 0.9184 |
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- | 1.608 | 11.86 | 36 | 0.1908 | 0.9592 |
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- | 1.608 | 12.86 | 39 | 0.1802 | 0.9592 |
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- | 0.6473 | 13.86 | 42 | 0.1682 | 0.9592 |
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- | 0.6473 | 14.86 | 45 | 0.1560 | 0.9592 |
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- | 0.6473 | 15.86 | 48 | 0.1322 | 0.9592 |
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- | 0.6473 | 16.86 | 51 | 0.1101 | 0.9592 |
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- | 0.6473 | 17.86 | 54 | 0.0938 | 0.9592 |
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- | 0.6473 | 18.86 | 57 | 0.0889 | 0.9796 |
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- | 0.3855 | 19.86 | 60 | 0.1025 | 0.9796 |
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- | 0.3855 | 20.86 | 63 | 0.0984 | 0.9796 |
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- | 0.3855 | 21.86 | 66 | 0.0867 | 0.9592 |
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- | 0.3855 | 22.86 | 69 | 0.0813 | 0.9592 |
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- | 0.3855 | 23.86 | 72 | 0.0768 | 0.9592 |
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- | 0.3855 | 24.86 | 75 | 0.0734 | 0.9796 |
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- | 0.3855 | 25.86 | 78 | 0.0698 | 0.9796 |
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- | 0.306 | 26.86 | 81 | 0.0618 | 0.9592 |
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- | 0.306 | 27.86 | 84 | 0.0547 | 0.9796 |
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- | 0.306 | 28.86 | 87 | 0.0538 | 0.9592 |
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- | 0.306 | 29.86 | 90 | 0.0487 | 0.9796 |
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- | 0.306 | 30.86 | 93 | 0.0447 | 1.0 |
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- | 0.306 | 31.86 | 96 | 0.0425 | 1.0 |
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- | 0.306 | 32.86 | 99 | 0.0451 | 1.0 |
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- | 0.2966 | 33.86 | 102 | 0.0497 | 1.0 |
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- | 0.2966 | 34.86 | 105 | 0.0558 | 1.0 |
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- | 0.2966 | 35.86 | 108 | 0.0582 | 0.9796 |
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- | 0.2966 | 36.86 | 111 | 0.0616 | 0.9592 |
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- | 0.2966 | 37.86 | 114 | 0.0657 | 0.9592 |
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- | 0.2966 | 38.86 | 117 | 0.0679 | 0.9592 |
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- | 0.2535 | 39.86 | 120 | 0.0684 | 0.9592 |
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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 2.6.1
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- - Tokenizers 0.13.1
 
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  This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0274
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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 | 0.8 | 3 | 1.8912 | 0.0392 |
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+ | No log | 1.8 | 6 | 1.7519 | 0.2745 |
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+ | No log | 2.8 | 9 | 1.5549 | 0.4706 |
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+ | No log | 3.8 | 12 | 1.2851 | 0.6667 |
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+ | No log | 4.8 | 15 | 0.9968 | 0.7647 |
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+ | No log | 5.8 | 18 | 0.7826 | 0.7843 |
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+ | 1.787 | 6.8 | 21 | 0.6010 | 0.8824 |
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+ | 1.787 | 7.8 | 24 | 0.4301 | 0.9020 |
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+ | 1.787 | 8.8 | 27 | 0.3233 | 0.8824 |
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+ | 1.787 | 9.8 | 30 | 0.2303 | 0.9412 |
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+ | 1.787 | 10.8 | 33 | 0.1871 | 1.0 |
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+ | 1.787 | 11.8 | 36 | 0.1600 | 0.9608 |
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+ | 1.787 | 12.8 | 39 | 0.1334 | 0.9804 |
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+ | 0.7554 | 13.8 | 42 | 0.1025 | 1.0 |
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+ | 0.7554 | 14.8 | 45 | 0.0909 | 1.0 |
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+ | 0.7554 | 15.8 | 48 | 0.0733 | 1.0 |
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+ | 0.7554 | 16.8 | 51 | 0.0625 | 1.0 |
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+ | 0.7554 | 17.8 | 54 | 0.0602 | 1.0 |
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+ | 0.7554 | 18.8 | 57 | 0.0613 | 1.0 |
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+ | 0.4731 | 19.8 | 60 | 0.0506 | 1.0 |
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+ | 0.4731 | 20.8 | 63 | 0.0588 | 1.0 |
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+ | 0.4731 | 21.8 | 66 | 0.0655 | 0.9804 |
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+ | 0.4731 | 22.8 | 69 | 0.0517 | 1.0 |
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+ | 0.4731 | 23.8 | 72 | 0.0414 | 1.0 |
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+ | 0.4731 | 24.8 | 75 | 0.0408 | 1.0 |
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+ | 0.4731 | 25.8 | 78 | 0.0417 | 1.0 |
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+ | 0.4248 | 26.8 | 81 | 0.0389 | 1.0 |
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+ | 0.4248 | 27.8 | 84 | 0.0376 | 1.0 |
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+ | 0.4248 | 28.8 | 87 | 0.0361 | 1.0 |
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+ | 0.4248 | 29.8 | 90 | 0.0351 | 1.0 |
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+ | 0.4248 | 30.8 | 93 | 0.0299 | 1.0 |
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+ | 0.4248 | 31.8 | 96 | 0.0284 | 1.0 |
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+ | 0.4248 | 32.8 | 99 | 0.0279 | 1.0 |
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+ | 0.3657 | 33.8 | 102 | 0.0275 | 1.0 |
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+ | 0.3657 | 34.8 | 105 | 0.0279 | 1.0 |
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+ | 0.3657 | 35.8 | 108 | 0.0279 | 1.0 |
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+ | 0.3657 | 36.8 | 111 | 0.0278 | 1.0 |
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+ | 0.3657 | 37.8 | 114 | 0.0276 | 1.0 |
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+ | 0.3657 | 38.8 | 117 | 0.0274 | 1.0 |
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+ | 0.3115 | 39.8 | 120 | 0.0274 | 1.0 |
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  ### Framework versions
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+ - Transformers 4.24.0
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  - Pytorch 1.12.1+cu113
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  - Datasets 2.6.1
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+ - Tokenizers 0.13.2