Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: model
+  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: 0.9867232343399052
+---
+
+<!-- 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. -->
+
+# model
+
+This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0560
+- Accuracy: 0.9867
+
+## 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: 3
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|
+| 0.1455        | 0.4279 | 10000 | 0.0871          | 0.9822   |
+| 0.2997        | 0.8557 | 20000 | 0.0938          | 0.9748   |
+| 0.0095        | 1.2836 | 30000 | 0.0787          | 0.9822   |
+| 0.0047        | 1.7114 | 40000 | 0.0804          | 0.9799   |
+| 0.0025        | 2.1393 | 50000 | 0.0647          | 0.9848   |
+| 0.0085        | 2.5672 | 60000 | 0.0577          | 0.9864   |
+| 0.0015        | 2.9950 | 70000 | 0.0618          | 0.9867   |
+| 0.0996        | 3.4229 | 80000 | 0.0596          | 0.9869   |
+| 0.0755        | 3.8508 | 90000 | 0.0560          | 0.9867   |
+
+
+### Framework versions
+
+- Transformers 4.48.0
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

model.safetensors

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