Model save

README.md

@@ -24,13 +24,13 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.9896390374331551
+      value: 0.9669117647058824
     - name: Precision
       type: precision
-      value: 0.9897531473312668
+      value: 0.9669680640397452
     - name: Recall
       type: recall
-      value: 0.9896390374331551
+      value: 0.9669117647058824
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,11 +40,11 @@ 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: 0.0355
-- Accuracy: 0.9896
-- Precision: 0.9898
-- Recall: 0.9896
-- Confusion Matrix: [[1508, 4], [27, 1453]]
+- Loss: 0.0861
+- Accuracy: 0.9669
+- Precision: 0.9670
+- Recall: 0.9669
+- Confusion Matrix: [[1471, 41], [58, 1422]]
 
 ## Model description
 
@@ -72,15 +72,13 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 3
+- num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix        |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:-----------------------:|
-| 0.0585        | 1.0   | 374  | 0.0224          | 0.9940   | 0.9940    | 0.9940 | [[1506, 6], [12, 1468]] |
-| 0.0792        | 2.0   | 748  | 0.0346          | 0.9910   | 0.9911    | 0.9910 | [[1509, 3], [24, 1456]] |
-| 0.0634        | 3.0   | 1122 | 0.0355          | 0.9896   | 0.9898    | 0.9896 | [[1508, 4], [27, 1453]] |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix         |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
+| 0.1483        | 1.0   | 374  | 0.0861          | 0.9669   | 0.9670    | 0.9669 | [[1471, 41], [58, 1422]] |
 
 
 ### Framework versions