update model card README.md

README.md

@@ -0,0 +1,94 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+- f1
+- recall
+- precision
+model-index:
+- name: Brain_Tumor_Classification_using_swin
+  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: 0.9960906958561376
+    - name: F1
+      type: f1
+      value: 0.9960906958561376
+    - name: Recall
+      type: recall
+      value: 0.9960906958561376
+    - name: Precision
+      type: precision
+      value: 0.9960906958561376
+---
+
+<!-- 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. -->
+
+# Brain_Tumor_Classification_using_swin
+
+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: 0.0123
+- Accuracy: 0.9961
+- F1: 0.9961
+- Recall: 0.9961
+- Precision: 0.9961
+
+## 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: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.1234        | 1.0   | 180  | 0.0450          | 0.9840   | 0.9840 | 0.9840 | 0.9840    |
+| 0.0837        | 2.0   | 360  | 0.0198          | 0.9926   | 0.9926 | 0.9926 | 0.9926    |
+| 0.0373        | 3.0   | 540  | 0.0123          | 0.9961   | 0.9961 | 0.9961 | 0.9961    |
+
+
+### Framework versions
+
+- Transformers 4.23.1
+- Pytorch 1.13.0
+- Datasets 2.6.1
+- Tokenizers 0.13.1