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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: 0.9714285714285714
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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: 0.1383
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- - Accuracy: 0.9714
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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 | 0.8 | 2 | 0.1919 | 0.9429 |
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- | No log | 1.8 | 4 | 0.1383 | 0.9714 |
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- | No log | 2.8 | 6 | 0.1930 | 0.9143 |
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- | No log | 3.8 | 8 | 0.1463 | 0.9714 |
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- | No log | 4.8 | 10 | 0.1735 | 0.9714 |
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- | No log | 5.8 | 12 | 0.1692 | 0.9714 |
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- | No log | 6.8 | 14 | 0.1626 | 0.9714 |
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- | No log | 7.8 | 16 | 0.1659 | 0.9714 |
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- | No log | 8.8 | 18 | 0.1622 | 0.9714 |
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- | 0.2046 | 9.8 | 20 | 0.1598 | 0.9714 |
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- | 0.2046 | 10.8 | 22 | 0.1668 | 0.9714 |
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- | 0.2046 | 11.8 | 24 | 0.1747 | 0.9714 |
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- | 0.2046 | 12.8 | 26 | 0.1804 | 0.9714 |
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- | 0.2046 | 13.8 | 28 | 0.1837 | 0.9714 |
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- | 0.2046 | 14.8 | 30 | 0.1837 | 0.9714 |
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- | 0.2046 | 15.8 | 32 | 0.1811 | 0.9714 |
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- | 0.2046 | 16.8 | 34 | 0.1801 | 0.9714 |
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- | 0.2046 | 17.8 | 36 | 0.1841 | 0.9714 |
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- | 0.2046 | 18.8 | 38 | 0.1899 | 0.9714 |
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- | 0.1657 | 19.8 | 40 | 0.1960 | 0.9714 |
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- | 0.1657 | 20.8 | 42 | 0.1993 | 0.9714 |
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- | 0.1657 | 21.8 | 44 | 0.2017 | 0.9714 |
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- | 0.1657 | 22.8 | 46 | 0.2004 | 0.9714 |
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- | 0.1657 | 23.8 | 48 | 0.1922 | 0.9714 |
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- | 0.1657 | 24.8 | 50 | 0.1856 | 0.9714 |
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- | 0.1657 | 25.8 | 52 | 0.1834 | 0.9714 |
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- | 0.1657 | 26.8 | 54 | 0.1846 | 0.9714 |
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- | 0.1657 | 27.8 | 56 | 0.1898 | 0.9714 |
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- | 0.1657 | 28.8 | 58 | 0.1951 | 0.9714 |
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- | 0.1308 | 29.8 | 60 | 0.2019 | 0.9714 |
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- | 0.1308 | 30.8 | 62 | 0.2095 | 0.9714 |
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- | 0.1308 | 31.8 | 64 | 0.2145 | 0.9714 |
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- | 0.1308 | 32.8 | 66 | 0.2154 | 0.9714 |
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- | 0.1308 | 33.8 | 68 | 0.2137 | 0.9714 |
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- | 0.1308 | 34.8 | 70 | 0.2116 | 0.9714 |
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- | 0.1308 | 35.8 | 72 | 0.2096 | 0.9714 |
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- | 0.1308 | 36.8 | 74 | 0.2084 | 0.9714 |
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- | 0.1308 | 37.8 | 76 | 0.2078 | 0.9714 |
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- | 0.1308 | 38.8 | 78 | 0.2075 | 0.9714 |
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- | 0.1053 | 39.8 | 80 | 0.2074 | 0.9714 |
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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: 0.972972972972973
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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: 0.0493
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+ - Accuracy: 0.9730
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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 | 0.73 | 2 | 0.0416 | 1.0 |
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+ | No log | 1.73 | 4 | 0.0346 | 1.0 |
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+ | No log | 2.73 | 6 | 0.0293 | 1.0 |
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+ | No log | 3.73 | 8 | 0.0186 | 1.0 |
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+ | No log | 4.73 | 10 | 0.0205 | 1.0 |
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+ | No log | 5.73 | 12 | 0.0604 | 0.9730 |
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+ | No log | 6.73 | 14 | 0.0332 | 1.0 |
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+ | No log | 7.73 | 16 | 0.0250 | 1.0 |
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+ | No log | 8.73 | 18 | 0.0386 | 1.0 |
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+ | 0.2483 | 9.73 | 20 | 0.0438 | 1.0 |
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+ | 0.2483 | 10.73 | 22 | 0.0447 | 1.0 |
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+ | 0.2483 | 11.73 | 24 | 0.0676 | 0.9730 |
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+ | 0.2483 | 12.73 | 26 | 0.0786 | 0.9730 |
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+ | 0.2483 | 13.73 | 28 | 0.0389 | 1.0 |
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+ | 0.2483 | 14.73 | 30 | 0.0278 | 1.0 |
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+ | 0.2483 | 15.73 | 32 | 0.0250 | 1.0 |
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+ | 0.2483 | 16.73 | 34 | 0.0283 | 1.0 |
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+ | 0.2483 | 17.73 | 36 | 0.0502 | 0.9730 |
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+ | 0.2483 | 18.73 | 38 | 0.0711 | 0.9730 |
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+ | 0.1759 | 19.73 | 40 | 0.0637 | 0.9730 |
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+ | 0.1759 | 20.73 | 42 | 0.0459 | 1.0 |
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+ | 0.1759 | 21.73 | 44 | 0.0394 | 1.0 |
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+ | 0.1759 | 22.73 | 46 | 0.0419 | 1.0 |
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+ | 0.1759 | 23.73 | 48 | 0.0423 | 1.0 |
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+ | 0.1759 | 24.73 | 50 | 0.0463 | 0.9730 |
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+ | 0.1759 | 25.73 | 52 | 0.0503 | 0.9730 |
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+ | 0.1759 | 26.73 | 54 | 0.0616 | 0.9730 |
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+ | 0.1759 | 27.73 | 56 | 0.0641 | 0.9730 |
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+ | 0.1759 | 28.73 | 58 | 0.0529 | 0.9730 |
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+ | 0.1669 | 29.73 | 60 | 0.0485 | 0.9730 |
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+ | 0.1669 | 30.73 | 62 | 0.0465 | 0.9730 |
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+ | 0.1669 | 31.73 | 64 | 0.0456 | 0.9730 |
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+ | 0.1669 | 32.73 | 66 | 0.0478 | 0.9730 |
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+ | 0.1669 | 33.73 | 68 | 0.0467 | 0.9730 |
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+ | 0.1669 | 34.73 | 70 | 0.0473 | 0.9730 |
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+ | 0.1669 | 35.73 | 72 | 0.0486 | 0.9730 |
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+ | 0.1669 | 36.73 | 74 | 0.0500 | 0.9730 |
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+ | 0.1669 | 37.73 | 76 | 0.0502 | 0.9730 |
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+ | 0.1669 | 38.73 | 78 | 0.0500 | 0.9730 |
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+ | 0.1589 | 39.73 | 80 | 0.0493 | 0.9730 |
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  ### Framework versions