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-original-10
+  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: 0.9916476841305999
+---
+
+<!-- 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-original-10
+
+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: 0.0443
+- Accuracy: 0.9916
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 5.6259        | 1.0   | 247  | 3.3200          | 0.3994   |
+| 1.9734        | 2.0   | 494  | 0.5108          | 0.9370   |
+| 0.6166        | 3.0   | 741  | 0.2288          | 0.9749   |
+| 0.4348        | 4.0   | 988  | 0.1149          | 0.9858   |
+| 0.2823        | 5.0   | 1235 | 0.0760          | 0.9899   |
+| 0.2351        | 6.0   | 1482 | 0.0618          | 0.9906   |
+| 0.1889        | 7.0   | 1729 | 0.0550          | 0.9894   |
+| 0.1681        | 8.0   | 1976 | 0.0505          | 0.9901   |
+| 0.144         | 9.0   | 2223 | 0.0446          | 0.9919   |
+| 0.1248        | 10.0  | 2470 | 0.0443          | 0.9916   |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.2.2+cu121
+- Datasets 3.0.0
+- Tokenizers 0.15.2

model.safetensors

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