Model save

README.md

@@ -7,6 +7,8 @@ datasets:
 - imagefolder
 metrics:
 - accuracy
+- precision
+- recall
 model-index:
 - name: swin-tiny-patch4-window7-224-finetuned-eurosat
   results:
@@ -22,7 +24,13 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8492143095954531
+      value: 0.9849598930481284
+    - name: Precision
+      type: precision
+      value: 0.9849602172971775
+    - name: Recall
+      type: recall
+      value: 0.9849598930481284
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +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: 0.6668
-- Accuracy: 0.8492
+- Loss: 0.0457
+- Accuracy: 0.9850
+- Precision: 0.9850
+- Recall: 0.9850
+- Confusion Matrix: [[1489, 23], [22, 1458]]
 
 ## Model description
 
@@ -65,11 +76,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.0623        | 1.0   | 374  | 0.4230          | 0.8719   |
-| 0.0401        | 2.0   | 748  | 1.3976          | 0.7757   |
-| 0.017         | 3.0   | 1122 | 0.6668          | 0.8492   |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | Confusion Matrix         |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------------------------:|
+| 0.117         | 1.0   | 374  | 0.0691          | 0.9729   | 0.9733    | 0.9729 | [[1452, 60], [21, 1459]] |
+| 0.103         | 2.0   | 748  | 0.0526          | 0.9793   | 0.9795    | 0.9793 | [[1466, 46], [16, 1464]] |
+| 0.0941        | 3.0   | 1122 | 0.0457          | 0.9850   | 0.9850    | 0.9850 | [[1489, 23], [22, 1458]] |
 
 
 ### Framework versions