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-hotel_classifier_v1
+  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: 0.9374278867489128
+---
+
+<!-- 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-hotel_classifier_v1
+
+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: 0.1932
+- Accuracy: 0.9374
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.3281        | 1.0   | 792  | 0.2726          | 0.9074   |
+| 0.3858        | 2.0   | 1584 | 0.2388          | 0.9191   |
+| 0.3153        | 3.0   | 2376 | 0.2123          | 0.9270   |
+| 0.3438        | 4.0   | 3169 | 0.2063          | 0.9289   |
+| 0.3219        | 5.0   | 3961 | 0.2061          | 0.9283   |
+| 0.2293        | 6.0   | 4753 | 0.1965          | 0.9333   |
+| 0.264         | 7.0   | 5545 | 0.1966          | 0.9360   |
+| 0.2112        | 8.0   | 6338 | 0.1964          | 0.9340   |
+| 0.2716        | 9.0   | 7130 | 0.1969          | 0.9350   |
+| 0.1938        | 10.0  | 7920 | 0.1932          | 0.9374   |
+
+
+### Framework versions
+
+- Transformers 4.38.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2