Model save

README.md

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+---
+license: apache-2.0
+base_model: microsoft/swin-base-patch4-window7-224
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-base-patch4-window7-224-finetuned-piid
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: val
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8127853881278538
+---
+
+<!-- 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-base-patch4-window7-224-finetuned-piid
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6630
+- Accuracy: 0.8128
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.1815        | 0.98  | 20   | 1.0441          | 0.5251   |
+| 0.6548        | 2.0   | 41   | 0.8150          | 0.6393   |
+| 0.6083        | 2.98  | 61   | 0.6395          | 0.6986   |
+| 0.4925        | 4.0   | 82   | 0.6273          | 0.6804   |
+| 0.4448        | 4.98  | 102  | 0.4812          | 0.8174   |
+| 0.3387        | 6.0   | 123  | 0.5868          | 0.7945   |
+| 0.2622        | 6.98  | 143  | 0.7868          | 0.7260   |
+| 0.2656        | 8.0   | 164  | 0.4432          | 0.8128   |
+| 0.2259        | 8.98  | 184  | 0.6553          | 0.7489   |
+| 0.1997        | 10.0  | 205  | 0.5143          | 0.7854   |
+| 0.1892        | 10.98 | 225  | 0.5657          | 0.7945   |
+| 0.1522        | 12.0  | 246  | 0.7339          | 0.7580   |
+| 0.1309        | 12.98 | 266  | 0.6064          | 0.8174   |
+| 0.1482        | 14.0  | 287  | 0.5875          | 0.8128   |
+| 0.1459        | 14.98 | 307  | 0.6443          | 0.7900   |
+| 0.1224        | 16.0  | 328  | 0.6521          | 0.8037   |
+| 0.0533        | 16.98 | 348  | 0.5915          | 0.8493   |
+| 0.1133        | 18.0  | 369  | 0.6152          | 0.8265   |
+| 0.0923        | 18.98 | 389  | 0.6819          | 0.7854   |
+| 0.086         | 19.51 | 400  | 0.6630          | 0.8128   |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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