Model save

README.md

@@ -25,16 +25,16 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8611111111111112
+      value: 0.9583333333333334
     - name: Precision
       type: precision
-      value: 0.8760606060606061
+      value: 0.9581730769230768
     - name: Recall
       type: recall
-      value: 0.8611111111111112
+      value: 0.9583333333333334
     - name: F1
       type: f1
-      value: 0.8564659977703456
+      value: 0.9580274686242009
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,12 +44,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [NekoFi/portrait_cosu_exp4](https://huggingface.co/NekoFi/portrait_cosu_exp4) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2661
-- Accuracy: 0.8611
-- Precision: 0.8761
-- Recall: 0.8611
-- F1: 0.8565
-- Confusion Matrix: [[41, 1], [9, 21]]
+- Loss: 0.1603
+- Accuracy: 0.9583
+- Precision: 0.9582
+- Recall: 0.9583
+- F1: 0.9580
+- Confusion Matrix: [[50, 1], [2, 19]]
 
 ## Model description
 
@@ -83,10 +83,10 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Confusion Matrix    |
 |:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------------------:|
-| 0.4706        | 0.9756 | 10   | 0.6059          | 0.6667   | 0.7879    | 0.6667 | 0.5926 | [[42, 0], [24, 6]]  |
-| 0.3421        | 1.9512 | 20   | 0.4176          | 0.75     | 0.825     | 0.75   | 0.7185 | [[42, 0], [18, 12]] |
-| 0.3131        | 2.9268 | 30   | 0.1941          | 0.9583   | 0.9621    | 0.9583 | 0.9586 | [[39, 3], [0, 30]]  |
-| 0.2716        | 3.9024 | 40   | 0.2661          | 0.8611   | 0.8761    | 0.8611 | 0.8565 | [[41, 1], [9, 21]]  |
+| 0.3966        | 0.9756 | 10   | 0.3024          | 0.8611   | 0.8695    | 0.8611 | 0.8498 | [[50, 1], [9, 12]]  |
+| 0.3486        | 1.9512 | 20   | 0.3286          | 0.8333   | 0.8458    | 0.8333 | 0.8147 | [[50, 1], [11, 10]] |
+| 0.2347        | 2.9268 | 30   | 0.1769          | 0.9444   | 0.9446    | 0.9444 | 0.9436 | [[50, 1], [3, 18]]  |
+| 0.2039        | 3.9024 | 40   | 0.1603          | 0.9583   | 0.9582    | 0.9583 | 0.9580 | [[50, 1], [2, 19]]  |
 
 
 ### Framework versions