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-bottom_cleaned_data-hpt
+  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: 0.9694041867954911
+---
+
+<!-- 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-bottom_cleaned_data-hpt
+
+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: 0.0701
+- Accuracy: 0.9694
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4307        | 0.99  | 99   | 0.2332          | 0.9227   |
+| 0.3425        | 2.0   | 199  | 0.1904          | 0.9404   |
+| 0.29          | 3.0   | 299  | 0.1316          | 0.9388   |
+| 0.2597        | 3.99  | 398  | 0.1158          | 0.9533   |
+| 0.2638        | 4.99  | 498  | 0.0987          | 0.9614   |
+| 0.209         | 6.0   | 598  | 0.0802          | 0.9710   |
+| 0.1776        | 7.0   | 698  | 0.0838          | 0.9597   |
+| 0.1776        | 7.99  | 797  | 0.0787          | 0.9694   |
+| 0.1502        | 9.0   | 897  | 0.0797          | 0.9726   |
+| 0.1402        | 9.93  | 990  | 0.0701          | 0.9694   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3