Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-Rado_5
+  results: []
+---
+
+<!-- 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-base-patch16-224-Rado_5
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1831
+- Accuracy: 0.9185
+
+## 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: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.554         | 1.0   | 10   | 0.3765          | 0.8741   |
+| 0.2117        | 2.0   | 20   | 0.2063          | 0.8963   |
+| 0.1368        | 3.0   | 30   | 0.1797          | 0.9259   |
+| 0.0953        | 4.0   | 40   | 0.2555          | 0.9037   |
+| 0.0726        | 5.0   | 50   | 0.1396          | 0.9185   |
+| 0.079         | 6.0   | 60   | 0.2110          | 0.9185   |
+| 0.0622        | 7.0   | 70   | 0.1790          | 0.9259   |
+| 0.0655        | 8.0   | 80   | 0.1837          | 0.9333   |
+| 0.0736        | 9.0   | 90   | 0.1798          | 0.9259   |
+| 0.0541        | 10.0  | 100  | 0.1831          | 0.9185   |
+
+
+### Framework versions
+
+- Transformers 4.41.1
+- Pytorch 2.3.0+cu121
+- Tokenizers 0.19.1

model.safetensors

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