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-base-patch4-window7-224-in22k-finetuned_swinv1-all-classes-autotags-latest
+  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: 0.9544554455445544
+---
+
+<!-- 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-in22k-finetuned_swinv1-all-classes-autotags-latest
+
+This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1665
+- Accuracy: 0.9545
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 64
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.8729        | 1.0   | 63   | 0.6445          | 0.7921   |
+| 0.4323        | 2.0   | 126  | 0.3358          | 0.8960   |
+| 0.3421        | 3.0   | 189  | 0.2650          | 0.9178   |
+| 0.198         | 4.0   | 252  | 0.2080          | 0.9327   |
+| 0.1239        | 5.0   | 315  | 0.1797          | 0.9446   |
+| 0.1053        | 6.0   | 378  | 0.1625          | 0.9525   |
+| 0.1109        | 7.0   | 441  | 0.1712          | 0.9505   |
+| 0.0411        | 8.0   | 504  | 0.1850          | 0.9436   |
+| 0.0615        | 9.0   | 567  | 0.1695          | 0.9554   |
+| 0.0407        | 10.0  | 630  | 0.1665          | 0.9545   |
+
+
+### Framework versions
+
+- Transformers 4.25.1
+- Pytorch 1.13.1+cu117
+- Datasets 2.11.0
+- Tokenizers 0.13.2