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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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  1. README.md +44 -44
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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: 0.9767441860465116
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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: 0.1403
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- - Accuracy: 0.9767
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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 | 1.0 | 3 | 0.1491 | 0.9535 |
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- | No log | 2.0 | 6 | 0.1462 | 0.9535 |
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- | No log | 3.0 | 9 | 0.1403 | 0.9767 |
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- | No log | 4.0 | 12 | 0.1431 | 0.9767 |
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- | No log | 5.0 | 15 | 0.1761 | 0.9535 |
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- | No log | 6.0 | 18 | 0.1930 | 0.9535 |
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- | 0.2637 | 7.0 | 21 | 0.1677 | 0.9535 |
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- | 0.2637 | 8.0 | 24 | 0.1835 | 0.9767 |
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- | 0.2637 | 9.0 | 27 | 0.1804 | 0.9535 |
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- | 0.2637 | 10.0 | 30 | 0.1856 | 0.9535 |
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- | 0.2637 | 11.0 | 33 | 0.1719 | 0.9535 |
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- | 0.2637 | 12.0 | 36 | 0.1680 | 0.9535 |
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- | 0.2637 | 13.0 | 39 | 0.1571 | 0.9535 |
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- | 0.1687 | 14.0 | 42 | 0.1333 | 0.9535 |
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- | 0.1687 | 15.0 | 45 | 0.1285 | 0.9535 |
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- | 0.1687 | 16.0 | 48 | 0.1293 | 0.9535 |
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- | 0.1687 | 17.0 | 51 | 0.1208 | 0.9767 |
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- | 0.1687 | 18.0 | 54 | 0.1061 | 0.9767 |
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- | 0.1687 | 19.0 | 57 | 0.0978 | 0.9767 |
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- | 0.1435 | 20.0 | 60 | 0.1100 | 0.9535 |
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- | 0.1435 | 21.0 | 63 | 0.1205 | 0.9535 |
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- | 0.1435 | 22.0 | 66 | 0.1027 | 0.9767 |
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- | 0.1435 | 23.0 | 69 | 0.1041 | 0.9767 |
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- | 0.1435 | 24.0 | 72 | 0.1021 | 0.9767 |
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- | 0.1435 | 25.0 | 75 | 0.0974 | 0.9767 |
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- | 0.1435 | 26.0 | 78 | 0.1006 | 0.9535 |
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- | 0.1361 | 27.0 | 81 | 0.1011 | 0.9535 |
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- | 0.1361 | 28.0 | 84 | 0.0993 | 0.9767 |
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- | 0.1361 | 29.0 | 87 | 0.0951 | 0.9767 |
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- | 0.1361 | 30.0 | 90 | 0.0971 | 0.9767 |
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- | 0.1361 | 31.0 | 93 | 0.1036 | 0.9767 |
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- | 0.1361 | 32.0 | 96 | 0.1085 | 0.9767 |
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- | 0.1361 | 33.0 | 99 | 0.1099 | 0.9767 |
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- | 0.1221 | 34.0 | 102 | 0.1115 | 0.9767 |
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- | 0.1221 | 35.0 | 105 | 0.1133 | 0.9767 |
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- | 0.1221 | 36.0 | 108 | 0.1184 | 0.9535 |
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- | 0.1221 | 37.0 | 111 | 0.1215 | 0.9535 |
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- | 0.1221 | 38.0 | 114 | 0.1224 | 0.9535 |
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- | 0.1221 | 39.0 | 117 | 0.1222 | 0.9535 |
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- | 0.1135 | 40.0 | 120 | 0.1217 | 0.9535 |
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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 2.5.1
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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: 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
 
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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: 0.2106
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+ - Accuracy: 0.9556
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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 | 0.92 | 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