Model save

README.md

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+---
+license: apache-2.0
+base_model: WinKawaks/vit-tiny-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-tiny-patch16-224-winkawaks
+  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: 0.8397770811563915
+---
+
+<!-- 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. -->
+
+# vit-tiny-patch16-224-winkawaks
+
+This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3540
+- Accuracy: 0.8398
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5345        | 1.0   | 202  | 0.4689          | 0.7771   |
+| 0.4936        | 2.0   | 404  | 0.5022          | 0.7485   |
+| 0.4911        | 3.0   | 606  | 0.3887          | 0.8279   |
+| 0.4191        | 4.0   | 808  | 0.4121          | 0.8098   |
+| 0.4408        | 5.0   | 1010 | 0.3897          | 0.8255   |
+| 0.4134        | 6.0   | 1212 | 0.3714          | 0.8332   |
+| 0.4117        | 7.0   | 1414 | 0.3685          | 0.8377   |
+| 0.3991        | 8.0   | 1616 | 0.3602          | 0.8412   |
+| 0.3936        | 9.0   | 1818 | 0.3542          | 0.8429   |
+| 0.3422        | 10.0  | 2020 | 0.3540          | 0.8398   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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