update model card README.md

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: alzheimer-image-classification-google-vit-base-patch16
+  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: 0.9261006289308176
+---
+
+<!-- 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. -->
+
+# alzheimer-image-classification-google-vit-base-patch16
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2127
+- Accuracy: 0.9261
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8167        | 1.0   | 715  | 0.7520          | 0.6494   |
+| 0.6264        | 2.0   | 1431 | 0.6467          | 0.7091   |
+| 0.5003        | 3.0   | 2146 | 0.5430          | 0.7594   |
+| 0.3543        | 4.0   | 2862 | 0.4372          | 0.8145   |
+| 0.3816        | 5.0   | 3577 | 0.3681          | 0.8428   |
+| 0.2055        | 6.0   | 4293 | 0.3746          | 0.8514   |
+| 0.2526        | 7.0   | 5008 | 0.2836          | 0.8907   |
+| 0.1262        | 8.0   | 5724 | 0.2798          | 0.8954   |
+| 0.1332        | 9.0   | 6439 | 0.2301          | 0.9159   |
+| 0.0702        | 9.99  | 7150 | 0.2127          | 0.9261   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1
+- Datasets 2.14.3
+- Tokenizers 0.13.3