Model save

README.md

@@ -6,7 +6,7 @@ tags:
 datasets:
 - imagefolder
 metrics:
-- f1
+- accuracy
 model-index:
 - name: dinov2-base-finetuned-eurosat
   results:
@@ -20,9 +20,9 @@ model-index:
       split: train
       args: default
     metrics:
-    - name: F1
-      type: f1
-      value: 0.6808059384941676
+    - name: Accuracy
+      type: accuracy
+      value: 0.7536231884057971
 ---
 
 <!-- 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 [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6882
-- F1: 0.6808
+- Loss: 0.5223
+- Accuracy: 0.7536
 
 ## Model description
 
@@ -65,11 +65,11 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | F1     |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.6972        | 1.0   | 45   | 0.6850          | 0.5402 |
-| 0.6839        | 2.0   | 90   | 0.6882          | 0.6808 |
-| 0.6829        | 3.0   | 135  | 0.6814          | 0.6529 |
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.5271        | 0.9960 | 63   | 0.5549          | 0.7135   |
+| 0.4804        | 1.9921 | 126  | 0.5335          | 0.7380   |
+| 0.3901        | 2.9881 | 189  | 0.5223          | 0.7536   |
 
 
 ### Framework versions