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
+  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: 0.9219817767653758
+    - name: Precision
+      type: precision
+      value: 0.9235132299409764
+---
+
+<!-- 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
+
+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: 0.2021
+- Accuracy: 0.9220
+- F1 Score: 0.9207
+- Precision: 0.9235
+
+## 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: 1e-05
+- train_batch_size: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
+| 1.2212        | 0.96  | 20   | 1.1407          | 0.6429   | 0.6225   | 0.6601    |
+| 0.565         | 1.98  | 41   | 0.5162          | 0.8326   | 0.8311   | 0.8428    |
+| 0.3245        | 2.99  | 62   | 0.3265          | 0.8804   | 0.8784   | 0.8843    |
+| 0.2618        | 4.0   | 83   | 0.2713          | 0.9066   | 0.9054   | 0.9105    |
+| 0.2164        | 4.96  | 103  | 0.2812          | 0.8946   | 0.8929   | 0.8994    |
+| 0.1814        | 5.98  | 124  | 0.2411          | 0.9060   | 0.9043   | 0.9091    |
+| 0.1481        | 6.99  | 145  | 0.2345          | 0.9100   | 0.9084   | 0.9130    |
+| 0.1468        | 8.0   | 166  | 0.2340          | 0.9072   | 0.9055   | 0.9108    |
+| 0.1336        | 8.96  | 186  | 0.1925          | 0.9265   | 0.9252   | 0.9270    |
+| 0.133         | 9.64  | 200  | 0.2021          | 0.9220   | 0.9207   | 0.9235    |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3