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: deit-base-distilled-patch16-224-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: 0.8045685279187818
+---
+
+<!-- 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. -->
+
+# deit-base-distilled-patch16-224-Brain_Tumors_Image_Classification
+
+This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.8587
+- Accuracy: 0.8046
+- Weighted f1: 0.7749
+- Micro f1: 0.8046
+- Macro f1: 0.7814
+- Weighted recall: 0.8046
+- Micro recall: 0.8046
+- Macro recall: 0.7996
+- Weighted precision: 0.8567
+- Micro precision: 0.8046
+- Macro precision: 0.8710
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
+| 1.6561        | 1.0   | 180  | 1.5974          | 0.7792   | 0.7454      | 0.7792   | 0.7524   | 0.7792          | 0.7792       | 0.7722       | 0.8318             | 0.7792          | 0.8488          |
+| 1.6561        | 2.0   | 360  | 1.7614          | 0.7944   | 0.7575      | 0.7944   | 0.7633   | 0.7944          | 0.7944       | 0.7896       | 0.8458             | 0.7944          | 0.8582          |
+| 0.172         | 3.0   | 540  | 1.8587          | 0.8046   | 0.7749      | 0.8046   | 0.7814   | 0.8046          | 0.8046       | 0.7996       | 0.8567             | 0.8046          | 0.8710          |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0
+- Datasets 2.11.0
+- Tokenizers 0.13.3