Model save

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-base-patch16-224-RU3-10
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.7833333333333333
+---
+
+<!-- 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-RU3-10
+
+This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6589
+- Accuracy: 0.7833
+
+## 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: 5.5e-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: 0.05
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.3698        | 0.99  | 19   | 1.1845          | 0.65     |
+| 1.1232        | 1.97  | 38   | 0.9393          | 0.65     |
+| 0.8168        | 2.96  | 57   | 0.9117          | 0.6333   |
+| 0.5992        | 4.0   | 77   | 0.8330          | 0.7333   |
+| 0.4258        | 4.99  | 96   | 0.7471          | 0.7      |
+| 0.3283        | 5.97  | 115  | 0.6241          | 0.7833   |
+| 0.2543        | 6.96  | 134  | 0.5916          | 0.7833   |
+| 0.2345        | 8.0   | 154  | 0.6783          | 0.7833   |
+| 0.2027        | 8.99  | 173  | 0.6577          | 0.7833   |
+| 0.1733        | 9.87  | 190  | 0.6589          | 0.7833   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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