update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: F1
       type: f1
-      value: 0.9885057471264367
+      value: 0.9884393063583815
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,8 +31,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0410
-- F1: 0.9885
+- Loss: 0.0404
+- F1: 0.9884
 
 ## Model description
 
@@ -57,21 +57,43 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 3
+- num_epochs: 9
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.4811        | 0.34  | 100  | 0.4447          | 0.7468 |
-| 0.2985        | 0.67  | 200  | 0.2198          | 0.8793 |
-| 0.1199        | 1.01  | 300  | 0.0846          | 0.9709 |
-| 0.128         | 1.35  | 400  | 0.1119          | 0.9574 |
-| 0.1387        | 1.68  | 500  | 0.1222          | 0.9496 |
-| 0.0899        | 2.02  | 600  | 0.0800          | 0.9765 |
-| 0.0048        | 2.36  | 700  | 0.0731          | 0.9769 |
-| 0.0195        | 2.69  | 800  | 0.0410          | 0.9885 |
+| 0.4747        | 0.3   | 100  | 0.3939          | 0.7964 |
+| 0.3318        | 0.6   | 200  | 0.2622          | 0.8710 |
+| 0.2525        | 0.89  | 300  | 0.2597          | 0.8670 |
+| 0.091         | 1.19  | 400  | 0.1451          | 0.9415 |
+| 0.2035        | 1.49  | 500  | 0.1765          | 0.9051 |
+| 0.1965        | 1.79  | 600  | 0.0625          | 0.9784 |
+| 0.0938        | 2.08  | 700  | 0.1094          | 0.9645 |
+| 0.0243        | 2.38  | 800  | 0.3224          | 0.8956 |
+| 0.0712        | 2.68  | 900  | 0.0944          | 0.9646 |
+| 0.3702        | 2.98  | 1000 | 0.1179          | 0.9534 |
+| 0.0557        | 3.27  | 1100 | 0.0709          | 0.9742 |
+| 0.081         | 3.57  | 1200 | 0.0616          | 0.9811 |
+| 0.1308        | 3.87  | 1300 | 0.0933          | 0.9676 |
+| 0.0196        | 4.17  | 1400 | 0.0579          | 0.9811 |
+| 0.0051        | 4.46  | 1500 | 0.0472          | 0.9854 |
+| 0.0102        | 4.76  | 1600 | 0.0607          | 0.9814 |
+| 0.0031        | 5.06  | 1700 | 0.0426          | 0.9899 |
+| 0.0952        | 5.36  | 1800 | 0.0503          | 0.9884 |
+| 0.0013        | 5.65  | 1900 | 0.0558          | 0.9827 |
+| 0.0424        | 5.95  | 2000 | 0.0504          | 0.9840 |
+| 0.0014        | 6.25  | 2100 | 0.0429          | 0.9898 |
+| 0.001         | 6.55  | 2200 | 0.0480          | 0.9884 |
+| 0.0008        | 6.85  | 2300 | 0.0399          | 0.9913 |
+| 0.0009        | 7.14  | 2400 | 0.0394          | 0.9914 |
+| 0.0007        | 7.44  | 2500 | 0.0480          | 0.9884 |
+| 0.0007        | 7.74  | 2600 | 0.0482          | 0.9869 |
+| 0.0007        | 8.04  | 2700 | 0.0397          | 0.9884 |
+| 0.0007        | 8.33  | 2800 | 0.0408          | 0.9884 |
+| 0.0006        | 8.63  | 2900 | 0.0414          | 0.9884 |
+| 0.0006        | 8.93  | 3000 | 0.0404          | 0.9884 |
 
 
 ### Framework versions