Model save

README.md

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+---
+license: apache-2.0
+base_model: 100rab25/swin-tiny-patch4-window7-224-spa_saloon_classification
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224-spa_saloon_classification-spa-saloon
+  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: 0.9686411149825784
+---
+
+<!-- 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. -->
+
+# swin-tiny-patch4-window7-224-spa_saloon_classification-spa-saloon
+
+This model is a fine-tuned version of [100rab25/swin-tiny-patch4-window7-224-spa_saloon_classification](https://huggingface.co/100rab25/swin-tiny-patch4-window7-224-spa_saloon_classification) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0982
+- Accuracy: 0.9686
+
+## 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: 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: 0.1
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2585        | 0.99  | 20   | 0.1616          | 0.9408   |
+| 0.2042        | 1.98  | 40   | 0.2162          | 0.9338   |
+| 0.1464        | 2.96  | 60   | 0.1001          | 0.9721   |
+| 0.1621        | 4.0   | 81   | 0.0915          | 0.9791   |
+| 0.1469        | 4.99  | 101  | 0.0797          | 0.9826   |
+| 0.1272        | 5.98  | 121  | 0.0753          | 0.9756   |
+| 0.0985        | 6.96  | 141  | 0.0860          | 0.9791   |
+| 0.1013        | 8.0   | 162  | 0.1178          | 0.9652   |
+| 0.111         | 8.99  | 182  | 0.1036          | 0.9652   |
+| 0.0737        | 9.88  | 200  | 0.0982          | 0.9686   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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