End of training

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: attraction-classifier-swin
+  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: 0.739010989010989
+---
+
+<!-- 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. -->
+
+# attraction-classifier-swin
+
+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: 0.5367
+- Accuracy: 0.7390
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 69
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6207        | 0.49  | 100  | 0.5599          | 0.7115   |
+| 0.6256        | 0.98  | 200  | 0.5238          | 0.7225   |
+| 0.597         | 1.46  | 300  | 0.5003          | 0.7418   |
+| 0.6121        | 1.95  | 400  | 0.5409          | 0.7610   |
+| 0.5457        | 2.44  | 500  | 0.5123          | 0.7555   |
+| 0.5258        | 2.93  | 600  | 0.4792          | 0.7637   |
+| 0.504         | 3.41  | 700  | 0.5169          | 0.7390   |
+| 0.541         | 3.9   | 800  | 0.4858          | 0.7582   |
+| 0.5704        | 4.39  | 900  | 0.5367          | 0.7390   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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