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segformer-class-classWeights-augmentation

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update model card README.md

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@@ -44,11 +44,12 @@ 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: 0.1453
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  - Accuracy: 0.9655
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  - F1: 0.9647
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  - Precision: 0.9674
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  - Recall: 0.9655
 
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  ## Model description
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@@ -80,17 +81,17 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | No log | 0.89 | 6 | 0.0454 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.1558 | 1.93 | 13 | 0.0816 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1727 | 2.96 | 20 | 0.0775 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1727 | 4.0 | 27 | 0.0443 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1299 | 4.89 | 33 | 0.0535 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1808 | 5.93 | 40 | 0.0298 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1808 | 6.96 | 47 | 0.0195 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.1406 | 8.0 | 54 | 0.0526 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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- | 0.1193 | 8.89 | 60 | 0.1453 | 0.9655 | 0.9647 | 0.9674 | 0.9655 |
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  ### Framework versions
 
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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: 0.1855
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  - Accuracy: 0.9655
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  - F1: 0.9647
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  - Precision: 0.9674
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  - Recall: 0.9655
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+ - Learning Rate: 0.0000
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Rate |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
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+ | No log | 0.89 | 6 | 0.1113 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1153 | 1.93 | 13 | 0.0929 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.2246 | 2.96 | 20 | 0.1026 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.2246 | 4.0 | 27 | 0.0391 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1433 | 4.89 | 33 | 0.0673 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1816 | 5.93 | 40 | 0.0794 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1816 | 6.96 | 47 | 0.0687 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1448 | 8.0 | 54 | 0.1123 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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+ | 0.1124 | 8.89 | 60 | 0.1855 | 0.9655 | 0.9647 | 0.9674 | 0.9655 | 0.0000 |
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  ### Framework versions