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-finetuned-sealv1
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9119804400977995
+---
+
+<!-- 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-finetuned-sealv1
+
+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: 0.2553
+- Accuracy: 0.9120
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.1068        | 0.95  | 14   | 0.6518          | 0.7066   |
+| 0.4912        | 1.97  | 29   | 0.4668          | 0.8435   |
+| 0.2749        | 2.98  | 44   | 0.4127          | 0.8704   |
+| 0.3189        | 4.0   | 59   | 0.3626          | 0.8875   |
+| 0.2226        | 4.95  | 73   | 0.2638          | 0.9046   |
+| 0.2394        | 5.97  | 88   | 0.3584          | 0.8802   |
+| 0.2241        | 6.98  | 103  | 0.2821          | 0.9046   |
+| 0.1815        | 8.0   | 118  | 0.2138          | 0.9218   |
+| 0.1862        | 8.95  | 132  | 0.2738          | 0.9046   |
+| 0.1942        | 9.49  | 140  | 0.2553          | 0.9120   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 1.10.2+cu113
+- Datasets 2.18.0
+- Tokenizers 0.15.2

model.safetensors

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