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swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08

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update model card README.md

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@@ -22,10 +22,10 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9591516103692066
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  - name: Precision
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  type: precision
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- value: 0.9627515459909033
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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
@@ -35,10 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1210
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- - Accuracy: 0.9592
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- - F1 Score: 0.9600
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- - Precision: 0.9628
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
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- | 1.2882 | 0.99 | 19 | 0.5469 | 0.7962 | 0.7863 | 0.8077 |
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- | 0.3491 | 1.97 | 38 | 0.3030 | 0.8861 | 0.8878 | 0.8981 |
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- | 0.1791 | 2.96 | 57 | 0.2077 | 0.9211 | 0.9229 | 0.9307 |
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- | 0.122 | 4.0 | 77 | 0.2007 | 0.9254 | 0.9272 | 0.9369 |
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- | 0.0671 | 4.99 | 96 | 0.2073 | 0.9269 | 0.9294 | 0.9401 |
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- | 0.0474 | 5.97 | 115 | 0.1384 | 0.9482 | 0.9494 | 0.9547 |
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- | 0.032 | 6.96 | 134 | 0.1683 | 0.9430 | 0.9447 | 0.9511 |
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- | 0.0225 | 8.0 | 154 | 0.1101 | 0.9650 | 0.9657 | 0.9671 |
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- | 0.0193 | 8.99 | 173 | 0.1372 | 0.9533 | 0.9544 | 0.9585 |
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- | 0.0193 | 9.87 | 190 | 0.1210 | 0.9592 | 0.9600 | 0.9628 |
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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: 0.9512961508248232
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  - name: Precision
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  type: precision
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+ value: 0.9549628106843154
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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-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1474
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+ - Accuracy: 0.9513
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+ - F1 Score: 0.9527
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+ - Precision: 0.9550
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
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+ | 1.3618 | 0.99 | 19 | 0.6238 | 0.7541 | 0.7431 | 0.7821 |
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+ | 0.3833 | 1.97 | 38 | 0.3097 | 0.8865 | 0.8884 | 0.8970 |
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+ | 0.2011 | 2.96 | 57 | 0.2600 | 0.9053 | 0.9078 | 0.9171 |
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+ | 0.1124 | 4.0 | 77 | 0.1793 | 0.9328 | 0.9342 | 0.9381 |
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+ | 0.0711 | 4.99 | 96 | 0.1385 | 0.9497 | 0.9509 | 0.9522 |
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+ | 0.0518 | 5.97 | 115 | 0.1506 | 0.9485 | 0.9501 | 0.9523 |
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+ | 0.0393 | 6.96 | 134 | 0.1422 | 0.9537 | 0.9549 | 0.9564 |
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+ | 0.0361 | 8.0 | 154 | 0.1545 | 0.9482 | 0.9497 | 0.9522 |
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+ | 0.025 | 8.99 | 173 | 0.1482 | 0.9501 | 0.9516 | 0.9541 |
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+ | 0.0204 | 9.87 | 190 | 0.1474 | 0.9513 | 0.9527 | 0.9550 |
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  ### Framework versions