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_06
+  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: 0.9225512528473804
+    - name: Precision
+      type: precision
+      value: 0.9214370287637926
+---
+
+<!-- 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_06
+
+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: 0.2384
+- Accuracy: 0.9226
+- F1 Score: 0.9210
+- Precision: 0.9214
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|
+| 1.3082        | 0.98  | 13   | 0.7669          | 0.7819   | 0.7689   | 0.7723    |
+| 0.5415        | 1.96  | 26   | 0.3100          | 0.8867   | 0.8812   | 0.8816    |
+| 0.279         | 2.94  | 39   | 0.2901          | 0.8992   | 0.8967   | 0.8961    |
+| 0.1563        | 4.0   | 53   | 0.2655          | 0.9089   | 0.9078   | 0.9084    |
+| 0.1304        | 4.98  | 66   | 0.2971          | 0.8964   | 0.8935   | 0.8958    |
+| 0.1058        | 5.96  | 79   | 0.2358          | 0.9243   | 0.9218   | 0.9224    |
+| 0.0971        | 6.94  | 92   | 0.2298          | 0.9260   | 0.9245   | 0.9258    |
+| 0.079         | 8.0   | 106  | 0.2468          | 0.9134   | 0.9123   | 0.9125    |
+| 0.0638        | 8.98  | 119  | 0.2534          | 0.9112   | 0.9097   | 0.9101    |
+| 0.0538        | 9.81  | 130  | 0.2384          | 0.9226   | 0.9210   | 0.9214    |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.12.0
+- Tokenizers 0.13.3