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swin-tiny-patch4-window7-224-finetuned-lungs-disease

Image Classification
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swin
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@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9075907590759076
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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
@@ -32,13 +32,12 @@ 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: 0.2434
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- - Accuracy: 0.9076
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  ## Model description
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- Utilizand modelul pre-antrenat, am facut urmatorul cod utilizand google-colab: https://colab.research.google.com/drive/1OvIDRB79KsnBbxU6yPXJnV8t1M5bI3rL#scrollTo=oD74VCH_kzbn
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-
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  ## Intended uses & limitations
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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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- | 0.814 | 0.98 | 21 | 0.5313 | 0.7492 |
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- | 0.4444 | 2.0 | 43 | 0.3200 | 0.8911 |
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- | 0.3322 | 2.98 | 64 | 0.3148 | 0.8911 |
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- | 0.2975 | 4.0 | 86 | 0.2836 | 0.8977 |
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- | 0.254 | 4.88 | 105 | 0.2434 | 0.9076 |
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  ### Framework versions
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- - Transformers 4.38.2
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- - Pytorch 2.2.1+cu121
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- - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9108910891089109
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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: 0.2546
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+ - Accuracy: 0.9109
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  ## Model description
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+ More information needed
 
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  ## Intended uses & limitations
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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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+ | 0.9133 | 0.9767 | 21 | 0.6896 | 0.7327 |
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+ | 0.4397 | 2.0 | 43 | 0.3190 | 0.8779 |
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+ | 0.3235 | 2.9767 | 64 | 0.2864 | 0.8944 |
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+ | 0.2945 | 4.0 | 86 | 0.2758 | 0.8977 |
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+ | 0.2804 | 4.8837 | 105 | 0.2546 | 0.9109 |
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  ### Framework versions
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+ - Transformers 4.41.0
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1