update model card README.md

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 1.0
+      value: 0.7586206896551724
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +32,8 @@ 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: 0.0021
-- Accuracy: 1.0
+- Loss: 0.6803
+- Accuracy: 0.7586
 
 ## Model description
 
@@ -53,11 +53,11 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 5e-05
-- train_batch_size: 10
-- eval_batch_size: 10
+- train_batch_size: 50
+- eval_batch_size: 50
 - seed: 42
 - gradient_accumulation_steps: 4
-- total_train_batch_size: 40
+- total_train_batch_size: 200
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
@@ -67,24 +67,20 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| No log        | 0.89  | 6    | 1.1566          | 0.2414   |
-| 1.11          | 1.93  | 13   | 0.9865          | 0.6552   |
-| 0.8833        | 2.96  | 20   | 0.8093          | 0.6552   |
-| 0.8833        | 4.0   | 27   | 0.4920          | 0.8276   |
-| 0.5072        | 4.89  | 33   | 0.3906          | 0.8276   |
-| 0.2935        | 5.93  | 40   | 0.0612          | 1.0      |
-| 0.2935        | 6.96  | 47   | 0.0375          | 1.0      |
-| 0.2311        | 8.0   | 54   | 0.2657          | 0.8621   |
-| 0.2665        | 8.89  | 60   | 0.0595          | 1.0      |
-| 0.2665        | 9.93  | 67   | 0.1044          | 0.9655   |
-| 0.2008        | 10.96 | 74   | 0.0150          | 1.0      |
-| 0.1557        | 12.0  | 81   | 0.0056          | 1.0      |
-| 0.1557        | 12.89 | 87   | 0.0028          | 1.0      |
-| 0.131         | 13.93 | 94   | 0.0011          | 1.0      |
-| 0.1708        | 14.96 | 101  | 0.0019          | 1.0      |
-| 0.1708        | 16.0  | 108  | 0.0023          | 1.0      |
-| 0.1799        | 16.89 | 114  | 0.0021          | 1.0      |
-| 0.1598        | 17.78 | 120  | 0.0021          | 1.0      |
+| No log        | 0.67  | 1    | 1.2027          | 0.3103   |
+| No log        | 2.0   | 3    | 1.1212          | 0.3448   |
+| No log        | 2.67  | 4    | 1.0648          | 0.4138   |
+| No log        | 4.0   | 6    | 0.9779          | 0.5172   |
+| No log        | 4.67  | 7    | 0.9494          | 0.5517   |
+| No log        | 6.0   | 9    | 0.9168          | 0.5862   |
+| 0.9535        | 6.67  | 10   | 0.8808          | 0.6552   |
+| 0.9535        | 8.0   | 12   | 0.8136          | 0.7241   |
+| 0.9535        | 8.67  | 13   | 0.8015          | 0.7241   |
+| 0.9535        | 10.0  | 15   | 0.7727          | 0.7586   |
+| 0.9535        | 10.67 | 16   | 0.7510          | 0.7586   |
+| 0.9535        | 12.0  | 18   | 0.6997          | 0.7586   |
+| 0.9535        | 12.67 | 19   | 0.6856          | 0.7586   |
+| 0.5181        | 13.33 | 20   | 0.6803          | 0.7586   |
 
 
 ### Framework versions