update model card README.md

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224-shortSleeveCleanedData
+  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: 0.9923497267759562
+---
+
+<!-- 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-shortSleeveCleanedData
+
+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: 0.0327
+- Accuracy: 0.9923
+
+## 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: 7
+- total_train_batch_size: 56
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.01
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1819        | 1.0   | 147  | 0.0471          | 0.9880   |
+| 0.1431        | 2.0   | 294  | 0.0457          | 0.9891   |
+| 0.1001        | 3.0   | 441  | 0.0392          | 0.9891   |
+| 0.116         | 4.0   | 588  | 0.0451          | 0.9880   |
+| 0.1144        | 5.0   | 735  | 0.0398          | 0.9902   |
+| 0.0787        | 6.0   | 882  | 0.0441          | 0.9902   |
+| 0.0998        | 7.0   | 1029 | 0.0320          | 0.9902   |
+| 0.124         | 8.0   | 1176 | 0.0364          | 0.9902   |
+| 0.103         | 9.0   | 1323 | 0.0395          | 0.9880   |
+| 0.0591        | 10.0  | 1470 | 0.0299          | 0.9913   |
+| 0.0445        | 11.0  | 1617 | 0.0302          | 0.9913   |
+| 0.0684        | 12.0  | 1764 | 0.0350          | 0.9880   |
+| 0.0358        | 13.0  | 1911 | 0.0408          | 0.9891   |
+| 0.0548        | 14.0  | 2058 | 0.0382          | 0.9902   |
+| 0.0611        | 15.0  | 2205 | 0.0331          | 0.9923   |
+| 0.0231        | 16.0  | 2352 | 0.0355          | 0.9945   |
+| 0.046         | 17.0  | 2499 | 0.0321          | 0.9934   |
+| 0.0648        | 18.0  | 2646 | 0.0327          | 0.9923   |
+| 0.0565        | 19.0  | 2793 | 0.0320          | 0.9923   |
+| 0.0413        | 20.0  | 2940 | 0.0327          | 0.9923   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3