update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.98
+      value: 0.7656078860898138
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.0679
-- Accuracy: 0.98
+- Loss: 1.0179
+- Accuracy: 0.7656
 
 ## Model description
 
@@ -52,11 +52,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 32
-- eval_batch_size: 32
+- train_batch_size: 16
+- eval_batch_size: 16
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 128
+- 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
@@ -66,9 +66,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.2555        | 1.0   | 190  | 0.1379          | 0.9548   |
-| 0.2007        | 2.0   | 380  | 0.0858          | 0.9711   |
-| 0.1318        | 3.0   | 570  | 0.0679          | 0.98     |
+| 3.2064        | 1.0   | 57   | 2.6102          | 0.4151   |
+| 1.6522        | 2.0   | 114  | 1.2683          | 0.7065   |
+| 1.339         | 3.0   | 171  | 1.0179          | 0.7656   |
 
 
 ### Framework versions