End of training

README.md

@@ -23,16 +23,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6217151244059268
+      value: 0.6336664802907465
     - name: F1
       type: f1
-      value: 0.5152478617168957
+      value: 0.5299313932110667
     - name: Precision
       type: precision
-      value: 0.5801734570391287
+      value: 0.5977139389034999
     - name: Recall
       type: recall
-      value: 0.4633910592025775
+      value: 0.4759565042287555
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,11 +42,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6730
-- Accuracy: 0.6217
-- F1: 0.5152
-- Precision: 0.5802
-- Recall: 0.4634
+- Loss: 0.6854
+- Accuracy: 0.6337
+- F1: 0.5299
+- Precision: 0.5977
+- Recall: 0.4760
 
 ## Model description
 
@@ -80,10 +80,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
-| 0.5705        | 1.0   | 2015 | 0.6879          | 0.5897   | 0.4460 | 0.5384    | 0.3807 |
-| 0.5309        | 2.0   | 4031 | 0.6788          | 0.6091   | 0.4859 | 0.5657    | 0.4258 |
-| 0.5263        | 3.0   | 6047 | 0.7020          | 0.6036   | 0.4322 | 0.5709    | 0.3477 |
-| 0.496         | 4.0   | 8060 | 0.6730          | 0.6217   | 0.5152 | 0.5802    | 0.4634 |
+| 0.499         | 1.0   | 2015 | 0.7028          | 0.6189   | 0.4730 | 0.5911    | 0.3942 |
+| 0.4738        | 2.0   | 4031 | 0.7003          | 0.6268   | 0.4981 | 0.5979    | 0.4268 |
+| 0.4788        | 3.0   | 6047 | 0.7195          | 0.6148   | 0.4517 | 0.5906    | 0.3657 |
+| 0.4523        | 4.0   | 8060 | 0.6854          | 0.6337   | 0.5299 | 0.5977    | 0.4760 |
 
 
 ### Framework versions