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-high-vit
+  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: 0.8421052631578947
+---
+
+<!-- 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-high-vit
+
+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: 0.6555
+- Accuracy: 0.8421
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 1.8073        | 0.9787 | 23   | 1.4742          | 0.5211   |
+| 0.9801        | 2.0    | 47   | 1.2410          | 0.5526   |
+| 0.5808        | 2.9787 | 70   | 0.9728          | 0.7053   |
+| 0.3797        | 4.0    | 94   | 0.7751          | 0.7632   |
+| 0.2559        | 4.9787 | 117  | 0.8020          | 0.7684   |
+| 0.1131        | 6.0    | 141  | 0.7116          | 0.8105   |
+| 0.1207        | 6.9787 | 164  | 0.7258          | 0.8105   |
+| 0.1068        | 8.0    | 188  | 0.6817          | 0.8316   |
+| 0.0559        | 8.9787 | 211  | 0.6589          | 0.8368   |
+| 0.0529        | 9.7872 | 230  | 0.6555          | 0.8421   |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1