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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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@@ -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: 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
@@ -29,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # delivery_truck_classification
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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: 0.0261
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- - Accuracy: 1.0
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  ## Model description
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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 | 0.86 | 3 | 0.0261 | 1.0 |
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- | No log | 1.86 | 6 | 0.0246 | 1.0 |
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- | No log | 2.86 | 9 | 0.0350 | 0.9792 |
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- | No log | 3.86 | 12 | 0.0298 | 1.0 |
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- | No log | 4.86 | 15 | 0.0362 | 0.9792 |
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- | No log | 5.86 | 18 | 0.0541 | 0.9792 |
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- | 0.2214 | 6.86 | 21 | 0.0363 | 0.9792 |
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- | 0.2214 | 7.86 | 24 | 0.0221 | 1.0 |
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- | 0.2214 | 8.86 | 27 | 0.0366 | 0.9792 |
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- | 0.2214 | 9.86 | 30 | 0.0502 | 0.9792 |
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- | 0.2214 | 10.86 | 33 | 0.0355 | 0.9792 |
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- | 0.2214 | 11.86 | 36 | 0.0218 | 1.0 |
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- | 0.2214 | 12.86 | 39 | 0.0140 | 1.0 |
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- | 0.183 | 13.86 | 42 | 0.0172 | 1.0 |
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- | 0.183 | 14.86 | 45 | 0.0300 | 0.9792 |
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- | 0.183 | 15.86 | 48 | 0.0589 | 0.9792 |
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- | 0.183 | 16.86 | 51 | 0.0693 | 0.9792 |
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- | 0.183 | 17.86 | 54 | 0.0496 | 0.9792 |
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- | 0.183 | 18.86 | 57 | 0.0316 | 0.9792 |
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- | 0.1706 | 19.86 | 60 | 0.0341 | 0.9792 |
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- | 0.1706 | 20.86 | 63 | 0.0348 | 0.9792 |
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- | 0.1706 | 21.86 | 66 | 0.0344 | 0.9792 |
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- | 0.1706 | 22.86 | 69 | 0.0469 | 0.9792 |
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- | 0.1706 | 23.86 | 72 | 0.0597 | 0.9792 |
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- | 0.1706 | 24.86 | 75 | 0.0530 | 0.9792 |
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- | 0.1706 | 25.86 | 78 | 0.0402 | 0.9792 |
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- | 0.1644 | 26.86 | 81 | 0.0362 | 0.9792 |
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- | 0.1644 | 27.86 | 84 | 0.0384 | 0.9792 |
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- | 0.1644 | 28.86 | 87 | 0.0310 | 0.9792 |
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- | 0.1644 | 29.86 | 90 | 0.0293 | 0.9792 |
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- | 0.1644 | 30.86 | 93 | 0.0375 | 0.9792 |
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- | 0.1644 | 31.86 | 96 | 0.0460 | 0.9792 |
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- | 0.1644 | 32.86 | 99 | 0.0522 | 0.9792 |
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- | 0.1539 | 33.86 | 102 | 0.0551 | 0.9792 |
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- | 0.1539 | 34.86 | 105 | 0.0552 | 0.9792 |
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- | 0.1539 | 35.86 | 108 | 0.0544 | 0.9792 |
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- | 0.1539 | 36.86 | 111 | 0.0552 | 0.9792 |
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- | 0.1539 | 37.86 | 114 | 0.0541 | 0.9792 |
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- | 0.1539 | 38.86 | 117 | 0.0526 | 0.9792 |
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- | 0.1401 | 39.86 | 120 | 0.0515 | 0.9792 |
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9591836734693877
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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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  # delivery_truck_classification
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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: 0.0684
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+ - Accuracy: 0.9592
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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 | 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