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JEdward7777
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delivery_truck_classification

Image Classification
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PyTorch
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swin
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update model card README.md

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  1. README.md +44 -14
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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: 0.8
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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 [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: 1.0377
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- - Accuracy: 0.8
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  ## Model description
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@@ -60,22 +60,52 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 10
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 1 | 1.6117 | 0.6 |
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- | No log | 2.0 | 2 | 1.5290 | 0.6 |
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- | No log | 3.0 | 3 | 1.4318 | 0.8 |
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- | No log | 4.0 | 4 | 1.3328 | 0.8 |
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- | No log | 5.0 | 5 | 1.2356 | 0.8 |
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- | No log | 6.0 | 6 | 1.1691 | 0.8 |
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- | No log | 7.0 | 7 | 1.1160 | 0.8 |
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- | No log | 8.0 | 8 | 1.0754 | 0.8 |
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- | No log | 9.0 | 9 | 1.0506 | 0.8 |
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- | No log | 10.0 | 10 | 1.0377 | 0.8 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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: 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
 
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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: 0.0600
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+ - Accuracy: 1.0
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 40
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 1 | 1.4318 | 0.8 |
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+ | No log | 2.0 | 2 | 1.3863 | 0.8 |
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+ | No log | 3.0 | 3 | 1.2880 | 0.8 |
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+ | No log | 4.0 | 4 | 1.1589 | 0.8 |
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+ | No log | 5.0 | 5 | 0.9954 | 0.8 |
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+ | No log | 6.0 | 6 | 0.8942 | 0.8 |
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+ | No log | 7.0 | 7 | 0.8269 | 0.8 |
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+ | No log | 8.0 | 8 | 0.7702 | 0.8 |
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+ | No log | 9.0 | 9 | 0.7138 | 1.0 |
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+ | No log | 10.0 | 10 | 0.6602 | 1.0 |
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+ | No log | 11.0 | 11 | 0.6255 | 1.0 |
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+ | No log | 12.0 | 12 | 0.5900 | 1.0 |
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+ | No log | 13.0 | 13 | 0.5367 | 1.0 |
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+ | No log | 14.0 | 14 | 0.4790 | 1.0 |
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+ | No log | 15.0 | 15 | 0.4158 | 1.0 |
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+ | No log | 16.0 | 16 | 0.3573 | 1.0 |
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+ | No log | 17.0 | 17 | 0.2964 | 1.0 |
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+ | No log | 18.0 | 18 | 0.2439 | 1.0 |
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+ | No log | 19.0 | 19 | 0.2028 | 1.0 |
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+ | 0.5248 | 20.0 | 20 | 0.1671 | 1.0 |
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+ | 0.5248 | 21.0 | 21 | 0.1399 | 1.0 |
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+ | 0.5248 | 22.0 | 22 | 0.1182 | 1.0 |
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+ | 0.5248 | 23.0 | 23 | 0.1013 | 1.0 |
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+ | 0.5248 | 24.0 | 24 | 0.0897 | 1.0 |
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+ | 0.5248 | 25.0 | 25 | 0.0824 | 1.0 |
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+ | 0.5248 | 26.0 | 26 | 0.0769 | 1.0 |
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+ | 0.5248 | 27.0 | 27 | 0.0721 | 1.0 |
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+ | 0.5248 | 28.0 | 28 | 0.0701 | 1.0 |
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+ | 0.5248 | 29.0 | 29 | 0.0697 | 1.0 |
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+ | 0.5248 | 30.0 | 30 | 0.0693 | 1.0 |
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+ | 0.5248 | 31.0 | 31 | 0.0672 | 1.0 |
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+ | 0.5248 | 32.0 | 32 | 0.0646 | 1.0 |
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+ | 0.5248 | 33.0 | 33 | 0.0633 | 1.0 |
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+ | 0.5248 | 34.0 | 34 | 0.0628 | 1.0 |
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+ | 0.5248 | 35.0 | 35 | 0.0626 | 1.0 |
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+ | 0.5248 | 36.0 | 36 | 0.0626 | 1.0 |
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+ | 0.5248 | 37.0 | 37 | 0.0617 | 1.0 |
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+ | 0.5248 | 38.0 | 38 | 0.0608 | 1.0 |
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+ | 0.5248 | 39.0 | 39 | 0.0603 | 1.0 |
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+ | 0.2241 | 40.0 | 40 | 0.0600 | 1.0 |
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  ### Framework versions