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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: 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
@@ -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: 0.0621
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- - Accuracy: 1.0
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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 | 0.86 | 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
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9791666666666666
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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: 0.0515
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+ - Accuracy: 0.9792
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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 | 0.0261 | 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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  - 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