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_10
+  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: 0.9359780047132757
+    - name: Precision
+      type: precision
+      value: 0.9436683740999858
+---
+
+<!-- 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_10
+
+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: 0.2116
+- Accuracy: 0.9360
+- F1 Score: 0.9374
+- Precision: 0.9437
+- Sensitivity: 0.9372
+- Specificity: 0.9839
+
+## 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: 0.0001
+- 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 | Sensitivity | Specificity |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:-----------:|:-----------:|
+| 1.3428        | 0.99  | 19   | 0.7059          | 0.7467   | 0.7535   | 0.7951    | 0.7464      | 0.9332      |
+| 0.3308        | 1.97  | 38   | 0.2314          | 0.9183   | 0.9194   | 0.9239    | 0.9191      | 0.9792      |
+| 0.1601        | 2.96  | 57   | 0.2024          | 0.9305   | 0.9314   | 0.9349    | 0.9306      | 0.9824      |
+| 0.0976        | 4.0   | 77   | 0.3376          | 0.8904   | 0.8943   | 0.9126    | 0.8930      | 0.9724      |
+| 0.0585        | 4.99  | 96   | 0.3893          | 0.8830   | 0.8853   | 0.9115    | 0.8854      | 0.9706      |
+| 0.0432        | 5.97  | 115  | 0.2559          | 0.9214   | 0.9239   | 0.9330    | 0.9237      | 0.9802      |
+| 0.0313        | 6.96  | 134  | 0.2175          | 0.9375   | 0.9383   | 0.9451    | 0.9381      | 0.9843      |
+| 0.0176        | 8.0   | 154  | 0.2309          | 0.9313   | 0.9326   | 0.9386    | 0.9320      | 0.9827      |
+| 0.0152        | 8.99  | 173  | 0.2358          | 0.9328   | 0.9339   | 0.9416    | 0.9336      | 0.9831      |
+| 0.0089        | 9.87  | 190  | 0.2116          | 0.9360   | 0.9374   | 0.9437    | 0.9372      | 0.9839      |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3