Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-tiny-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: ai_vs_real-finetuned-eurosat
+  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: 0.9901960784313726
+---
+
+<!-- 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. -->
+
+# ai_vs_real-finetuned-eurosat
+
+This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0432
+- Accuracy: 0.9902
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 0.8   | 3    | 0.7072          | 0.5      |
+| No log        | 1.87  | 7    | 0.5099          | 0.7255   |
+| 0.6036        | 2.93  | 11   | 0.3836          | 0.8529   |
+| 0.6036        | 4.0   | 15   | 0.2382          | 0.9118   |
+| 0.6036        | 4.8   | 18   | 0.1662          | 0.9412   |
+| 0.2575        | 5.87  | 22   | 0.1505          | 0.9412   |
+| 0.2575        | 6.93  | 26   | 0.0722          | 0.9804   |
+| 0.0813        | 8.0   | 30   | 0.0788          | 0.9608   |
+| 0.0813        | 8.8   | 33   | 0.0697          | 0.9608   |
+| 0.0813        | 9.87  | 37   | 0.0596          | 0.9608   |
+| 0.053         | 10.93 | 41   | 0.0437          | 0.9902   |
+| 0.053         | 12.0  | 45   | 0.0432          | 0.9902   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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