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swinv2-tiny-patch4-window8-256-DMAE-ex

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swinv2
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  1. README.md +37 -37
  2. model.safetensors +1 -1
  3. runs/Dec02_15-16-55_DESKTOP-SKBE9FB/events.out.tfevents.1733174216.DESKTOP-SKBE9FB.11568.0 +2 -2
README.md CHANGED
@@ -32,7 +32,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3785
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  - Accuracy: 0.4565
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  ## Model description
@@ -52,7 +52,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 0.02
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
@@ -66,41 +66,41 @@ 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 | 26.2016 | 0.1739 |
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- | No log | 2.0 | 7 | 1.3785 | 0.4565 |
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- | 12.975 | 2.86 | 10 | 2.2855 | 0.4565 |
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- | 12.975 | 4.0 | 14 | 1.5437 | 0.4565 |
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- | 12.975 | 4.86 | 17 | 1.5017 | 0.3261 |
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- | 2.1282 | 6.0 | 21 | 1.5409 | 0.1087 |
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- | 2.1282 | 6.86 | 24 | 1.4040 | 0.4565 |
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- | 2.1282 | 8.0 | 28 | 1.2780 | 0.4565 |
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- | 1.554 | 8.86 | 31 | 1.2300 | 0.3261 |
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- | 1.554 | 10.0 | 35 | 1.3228 | 0.3261 |
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- | 1.554 | 10.86 | 38 | 1.2745 | 0.4565 |
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- | 1.3748 | 12.0 | 42 | 1.3724 | 0.3261 |
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- | 1.3748 | 12.86 | 45 | 1.3726 | 0.4565 |
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- | 1.3748 | 14.0 | 49 | 1.2891 | 0.3261 |
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- | 1.5315 | 14.86 | 52 | 1.2979 | 0.4565 |
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- | 1.5315 | 16.0 | 56 | 1.2272 | 0.4565 |
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- | 1.5315 | 16.86 | 59 | 1.2749 | 0.3261 |
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- | 1.351 | 18.0 | 63 | 1.2219 | 0.4565 |
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- | 1.351 | 18.86 | 66 | 1.2200 | 0.4565 |
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- | 1.2678 | 20.0 | 70 | 1.2278 | 0.3261 |
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- | 1.2678 | 20.86 | 73 | 1.2318 | 0.4565 |
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- | 1.2678 | 22.0 | 77 | 1.2102 | 0.4565 |
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- | 1.244 | 22.86 | 80 | 1.2466 | 0.3261 |
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- | 1.244 | 24.0 | 84 | 1.2103 | 0.4565 |
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- | 1.244 | 24.86 | 87 | 1.2067 | 0.4565 |
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- | 1.2585 | 26.0 | 91 | 1.2129 | 0.4565 |
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- | 1.2585 | 26.86 | 94 | 1.2110 | 0.4565 |
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- | 1.2585 | 28.0 | 98 | 1.2131 | 0.4565 |
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- | 1.2405 | 28.86 | 101 | 1.2072 | 0.4565 |
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- | 1.2405 | 30.0 | 105 | 1.2099 | 0.4565 |
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- | 1.2405 | 30.86 | 108 | 1.2115 | 0.4565 |
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- | 1.2134 | 32.0 | 112 | 1.2138 | 0.4565 |
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- | 1.2134 | 32.86 | 115 | 1.2095 | 0.4565 |
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- | 1.2134 | 34.0 | 119 | 1.2081 | 0.4565 |
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- | 1.1982 | 34.29 | 120 | 1.2080 | 0.4565 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2067
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  - Accuracy: 0.4565
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  ## Model description
 
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 0.1
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.86 | 3 | 45.5320 | 0.3261 |
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+ | No log | 2.0 | 7 | 11.3982 | 0.4565 |
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+ | 37.3882 | 2.86 | 10 | 14.6592 | 0.3261 |
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+ | 37.3882 | 4.0 | 14 | 5.4321 | 0.4565 |
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+ | 37.3882 | 4.86 | 17 | 2.1913 | 0.1087 |
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+ | 7.8109 | 6.0 | 21 | 7.5738 | 0.1087 |
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+ | 7.8109 | 6.86 | 24 | 8.5702 | 0.4565 |
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+ | 7.8109 | 8.0 | 28 | 5.5301 | 0.1087 |
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+ | 6.7711 | 8.86 | 31 | 2.6876 | 0.4565 |
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+ | 6.7711 | 10.0 | 35 | 1.8742 | 0.1087 |
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+ | 6.7711 | 10.86 | 38 | 1.5266 | 0.4565 |
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+ | 1.7995 | 12.0 | 42 | 1.5311 | 0.1087 |
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+ | 1.7995 | 12.86 | 45 | 1.4439 | 0.4565 |
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+ | 1.7995 | 14.0 | 49 | 1.2218 | 0.4565 |
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+ | 1.5366 | 14.86 | 52 | 1.3226 | 0.4565 |
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+ | 1.5366 | 16.0 | 56 | 1.6288 | 0.1087 |
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+ | 1.5366 | 16.86 | 59 | 1.7526 | 0.4565 |
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+ | 1.5748 | 18.0 | 63 | 1.3699 | 0.3261 |
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+ | 1.5748 | 18.86 | 66 | 1.2663 | 0.4565 |
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+ | 1.3933 | 20.0 | 70 | 1.2222 | 0.4565 |
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+ | 1.3933 | 20.86 | 73 | 1.2388 | 0.3261 |
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+ | 1.3933 | 22.0 | 77 | 1.2831 | 0.4565 |
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+ | 1.2788 | 22.86 | 80 | 1.2515 | 0.3261 |
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+ | 1.2788 | 24.0 | 84 | 1.2105 | 0.4565 |
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+ | 1.2788 | 24.86 | 87 | 1.2141 | 0.4565 |
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+ | 1.2218 | 26.0 | 91 | 1.2215 | 0.4565 |
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+ | 1.2218 | 26.86 | 94 | 1.2189 | 0.4565 |
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+ | 1.2218 | 28.0 | 98 | 1.2102 | 0.4565 |
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+ | 1.2039 | 28.86 | 101 | 1.2094 | 0.4565 |
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+ | 1.2039 | 30.0 | 105 | 1.2065 | 0.4565 |
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+ | 1.2039 | 30.86 | 108 | 1.2125 | 0.4565 |
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+ | 1.2131 | 32.0 | 112 | 1.2107 | 0.4565 |
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+ | 1.2131 | 32.86 | 115 | 1.2078 | 0.4565 |
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+ | 1.2131 | 34.0 | 119 | 1.2068 | 0.4565 |
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+ | 1.211 | 34.29 | 120 | 1.2067 | 0.4565 |
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  ### Framework versions
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