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-U8-10
+  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: 0.8
+---
+
+<!-- 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-U8-10
+
+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: 0.4801
+- Accuracy: 0.8
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.2473        | 1.0   | 20   | 1.1804          | 0.5833   |
+| 0.9555        | 2.0   | 40   | 0.9370          | 0.65     |
+| 0.727         | 3.0   | 60   | 0.7202          | 0.6833   |
+| 0.5288        | 4.0   | 80   | 0.5606          | 0.8833   |
+| 0.3876        | 5.0   | 100  | 0.6482          | 0.7667   |
+| 0.296         | 6.0   | 120  | 0.7458          | 0.7167   |
+| 0.236         | 7.0   | 140  | 0.4677          | 0.8833   |
+| 0.2129        | 8.0   | 160  | 0.5138          | 0.8333   |
+| 0.1781        | 9.0   | 180  | 0.4736          | 0.85     |
+| 0.1854        | 10.0  | 200  | 0.4801          | 0.8      |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu118
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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