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-finetuned-eurosat
+  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: 0.972
+---
+
+<!-- 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-finetuned-eurosat
+
+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: 0.1017
+- Accuracy: 0.972
+
+## 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: 5e-05
+- train_batch_size: 450
+- eval_batch_size: 450
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 1800
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3243        | 1.0   | 46   | 0.2033          | 0.944    |
+| 0.1247        | 2.0   | 92   | 0.0791          | 0.976    |
+| 0.0937        | 3.0   | 138  | 0.0971          | 0.963    |
+| 0.0716        | 4.0   | 184  | 0.0778          | 0.972    |
+| 0.0543        | 5.0   | 230  | 0.0654          | 0.98     |
+| 0.0367        | 6.0   | 276  | 0.0913          | 0.972    |
+| 0.0292        | 7.0   | 322  | 0.0778          | 0.979    |
+| 0.0204        | 8.0   | 368  | 0.0914          | 0.971    |
+| 0.0161        | 9.0   | 414  | 0.1026          | 0.971    |
+| 0.0154        | 10.0  | 460  | 0.1017          | 0.972    |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

model.safetensors

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