update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: van-base-Brain_Tumors_Image_Classification
+  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: 0.7918781725888325
+---
+
+<!-- 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. -->
+
+# van-base-Brain_Tumors_Image_Classification
+
+This model is a fine-tuned version of [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7847
+- Accuracy: 0.7919
+- Weighted f1: 0.7588
+- Micro f1: 0.7919
+- Macro f1: 0.7665
+- Weighted recall: 0.7919
+- Micro recall: 0.7919
+- Macro recall: 0.7865
+- Weighted precision: 0.8505
+- Micro precision: 0.7919
+- Macro precision: 0.8675
+
+## 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: 0.0002
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.3357        | 1.0   | 180  | 1.5273          | 0.7183   | 0.6631      | 0.7183   | 0.6695   | 0.7183          | 0.7183       | 0.7058       | 0.8219             | 0.7183          | 0.8420          |
+| 1.3357        | 2.0   | 360  | 1.9359          | 0.7792   | 0.7314      | 0.7792   | 0.7411   | 0.7792          | 0.7792       | 0.7764       | 0.8467             | 0.7792          | 0.8636          |
+| 0.1229        | 3.0   | 540  | 1.7847          | 0.7919   | 0.7588      | 0.7919   | 0.7665   | 0.7919          | 0.7919       | 0.7865       | 0.8505             | 0.7919          | 0.8675          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3