update model card README.md

README.md

@@ -0,0 +1,86 @@
+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: swin-tiny-patch4-window7-224-LongSleeveCleanedData
+  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: 1.0
+---
+
+<!-- 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-LongSleeveCleanedData
+
+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: 0.0011
+- Accuracy: 1.0
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.1472        | 0.99  | 132  | 0.0460          | 0.9831   |
+| 0.1171        | 1.99  | 265  | 0.0213          | 0.9903   |
+| 0.133         | 3.0   | 398  | 0.0076          | 0.9976   |
+| 0.0714        | 4.0   | 531  | 0.0081          | 0.9976   |
+| 0.0776        | 5.0   | 664  | 0.0053          | 0.9988   |
+| 0.0812        | 6.0   | 797  | 0.0049          | 0.9976   |
+| 0.0658        | 7.0   | 930  | 0.0030          | 1.0      |
+| 0.0804        | 7.99  | 1062 | 0.0035          | 0.9976   |
+| 0.0508        | 8.99  | 1195 | 0.0011          | 1.0      |
+| 0.0725        | 9.94  | 1320 | 0.0011          | 1.0      |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3