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: swin-tiny-patch4-window7-224-spa_saloon_classification
+  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: 0.965195246179966
+---
+
+<!-- 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
+
+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: 0.1075
+- Accuracy: 0.9652
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4613        | 1.0   | 83   | 0.3357          | 0.8718   |
+| 0.2908        | 2.0   | 166  | 0.1805          | 0.9312   |
+| 0.2341        | 3.0   | 249  | 0.1426          | 0.9516   |
+| 0.1907        | 4.0   | 332  | 0.1471          | 0.9423   |
+| 0.1836        | 5.0   | 415  | 0.1177          | 0.9576   |
+| 0.1669        | 6.0   | 498  | 0.1131          | 0.9669   |
+| 0.152         | 7.0   | 581  | 0.1100          | 0.9660   |
+| 0.1666        | 8.0   | 664  | 0.1130          | 0.9626   |
+| 0.1374        | 9.0   | 747  | 0.1132          | 0.9669   |
+| 0.1278        | 10.0  | 830  | 0.1075          | 0.9652   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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