update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- precision
+model-index:
+- name: swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9591516103692066
+    - name: Precision
+      type: precision
+      value: 0.9627515459909033
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# swin-base-patch4-window7-224-in22k-finetuned-brain-tumor-final_08
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.1210
+- Accuracy: 0.9592
+- F1 Score: 0.9600
+- Precision: 0.9628
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 100
+- eval_batch_size: 100
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 400
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
+| 1.2882        | 0.99  | 19   | 0.5469          | 0.7962   | 0.7863   | 0.8077    |
+| 0.3491        | 1.97  | 38   | 0.3030          | 0.8861   | 0.8878   | 0.8981    |
+| 0.1791        | 2.96  | 57   | 0.2077          | 0.9211   | 0.9229   | 0.9307    |
+| 0.122         | 4.0   | 77   | 0.2007          | 0.9254   | 0.9272   | 0.9369    |
+| 0.0671        | 4.99  | 96   | 0.2073          | 0.9269   | 0.9294   | 0.9401    |
+| 0.0474        | 5.97  | 115  | 0.1384          | 0.9482   | 0.9494   | 0.9547    |
+| 0.032         | 6.96  | 134  | 0.1683          | 0.9430   | 0.9447   | 0.9511    |
+| 0.0225        | 8.0   | 154  | 0.1101          | 0.9650   | 0.9657   | 0.9671    |
+| 0.0193        | 8.99  | 173  | 0.1372          | 0.9533   | 0.9544   | 0.9585    |
+| 0.0193        | 9.87  | 190  | 0.1210          | 0.9592   | 0.9600   | 0.9628    |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3