tonyassi
/

celebrity-classifier

@@ -17,8 +17,8 @@ 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 an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.0002
-- Accuracy: 0.7850
 ## Model description
@@ -52,26 +52,26 @@ The following hyperparameters were used during training:
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
-| 0.7184        | 1.0   | 227  | 1.6196          | 0.7327   |
-| 0.6575        | 2.0   | 455  | 1.6466          | 0.7102   |
-| 0.6033        | 3.0   | 682  | 1.5743          | 0.7226   |
-| 0.4692        | 4.0   | 910  | 1.4970          | 0.7289   |
-| 0.3551        | 5.0   | 1137 | 1.4109          | 0.7393   |
-| 0.4104        | 6.0   | 1365 | 1.3546          | 0.7352   |
-| 0.3038        | 7.0   | 1592 | 1.3356          | 0.7393   |
-| 0.3195        | 8.0   | 1820 | 1.3145          | 0.7371   |
-| 0.3254        | 9.0   | 2047 | 1.2262          | 0.7580   |
-| 0.3182        | 10.0  | 2275 | 1.1926          | 0.7630   |
-| 0.3278        | 11.0  | 2502 | 1.1491          | 0.7704   |
-| 0.2805        | 12.0  | 2730 | 1.1514          | 0.7627   |
-| 0.3188        | 13.0  | 2957 | 1.0948          | 0.7795   |
-| 0.3161        | 14.0  | 3185 | 1.1231          | 0.7685   |
-| 0.229         | 15.0  | 3412 | 1.0588          | 0.7789   |
-| 0.2544        | 16.0  | 3640 | 1.0311          | 0.7806   |
-| 0.2872        | 17.0  | 3867 | 1.0586          | 0.7762   |
-| 0.3974        | 18.0  | 4095 | 1.0341          | 0.7833   |
-| 0.337         | 19.0  | 4322 | 0.9834          | 0.7891   |
-| 0.3165        | 19.96 | 4540 | 1.0002          | 0.7850   |
 ### Framework versions

 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.9089
+- Accuracy: 0.7982
 ## Model description
 | Training Loss | Epoch | Step | Validation Loss | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.2075        | 1.0   | 227  | 1.0255          | 0.7831   |
+| 0.1359        | 2.0   | 455  | 1.1713          | 0.7517   |
+| 0.1703        | 3.0   | 682  | 1.1582          | 0.7503   |
+| 0.1052        | 4.0   | 910  | 1.1482          | 0.7567   |
+| 0.0826        | 5.0   | 1137 | 1.1340          | 0.7514   |
+| 0.1412        | 6.0   | 1365 | 1.1149          | 0.7514   |
+| 0.105         | 7.0   | 1592 | 1.1071          | 0.7523   |
+| 0.1067        | 8.0   | 1820 | 1.1161          | 0.7539   |
+| 0.1329        | 9.0   | 2047 | 1.0587          | 0.7693   |
+| 0.1196        | 10.0  | 2275 | 1.0416          | 0.7688   |
+| 0.1368        | 11.0  | 2502 | 1.0618          | 0.7663   |
+| 0.1162        | 12.0  | 2730 | 1.0285          | 0.7721   |
+| 0.145         | 13.0  | 2957 | 1.0040          | 0.7776   |
+| 0.1449        | 14.0  | 3185 | 0.9967          | 0.7800   |
+| 0.1135        | 15.0  | 3412 | 0.9603          | 0.7842   |
+| 0.1266        | 16.0  | 3640 | 0.9333          | 0.7861   |
+| 0.1571        | 17.0  | 3867 | 0.9643          | 0.7836   |
+| 0.278         | 18.0  | 4095 | 0.9526          | 0.7861   |
+| 0.2596        | 19.0  | 4322 | 0.9022          | 0.7965   |
+| 0.2432        | 19.96 | 4540 | 0.9089          | 0.7982   |
 ### Framework versions