update model card README.md

README.md

@@ -20,11 +20,11 @@ model-index:
     - name: Accuracy
       type: accuracy
       value:
-        accuracy: 1.0
+        accuracy: 0.12185929648241206
     - name: F1
       type: f1
       value:
-        f1: 1.0
+        f1: 0.05431131019036954
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,9 +34,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [](https://huggingface.co/) on the preprocessed1024_config dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0250
-- Accuracy: {'accuracy': 1.0}
-- F1: {'f1': 1.0}
+- Loss: 0.0275
+- Accuracy: {'accuracy': 0.12185929648241206}
+- F1: {'f1': 0.05431131019036954}
 
 ## Model description
 
@@ -65,18 +65,18 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Accuracy          | F1          |
-|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:-----------:|
-| 0.0899        | 1.0   | 796  | 0.0727          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0451        | 2.0   | 1592 | 0.0395          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0388        | 3.0   | 2388 | 0.0382          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0298        | 4.0   | 3184 | 0.0310          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0239        | 5.0   | 3980 | 0.0394          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0194        | 6.0   | 4776 | 0.0254          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0178        | 7.0   | 5572 | 0.0248          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0155        | 8.0   | 6368 | 0.0258          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0137        | 9.0   | 7164 | 0.0247          | {'accuracy': 1.0} | {'f1': 1.0} |
-| 0.0129        | 10.0  | 7960 | 0.0250          | {'accuracy': 1.0} | {'f1': 1.0} |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy                           | F1                           |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------:|:----------------------------:|
+| 0.0233        | 1.0   | 796  | 0.0269          | {'accuracy': 0.042085427135678394} | {'f1': 0.02019288728149488}  |
+| 0.0202        | 2.0   | 1592 | 0.0250          | {'accuracy': 0.09610552763819095}  | {'f1': 0.043839541547277934} |
+| 0.0183        | 3.0   | 2388 | 0.0248          | {'accuracy': 0.07977386934673367}  | {'f1': 0.036940081442699245} |
+| 0.0163        | 4.0   | 3184 | 0.0259          | {'accuracy': 0.17022613065326633}  | {'f1': 0.07273215244229736}  |
+| 0.0144        | 5.0   | 3980 | 0.0258          | {'accuracy': 0.146356783919598}    | {'f1': 0.06383561643835617}  |
+| 0.0117        | 6.0   | 4776 | 0.0249          | {'accuracy': 0.0992462311557789}   | {'f1': 0.045142857142857144} |
+| 0.0105        | 7.0   | 5572 | 0.0256          | {'accuracy': 0.10238693467336683}  | {'f1': 0.04643874643874644}  |
+| 0.0084        | 8.0   | 6368 | 0.0261          | {'accuracy': 0.12185929648241206}  | {'f1': 0.05431131019036954}  |
+| 0.0071        | 9.0   | 7164 | 0.0270          | {'accuracy': 0.10238693467336683}  | {'f1': 0.04643874643874644}  |
+| 0.0065        | 10.0  | 7960 | 0.0275          | {'accuracy': 0.12185929648241206}  | {'f1': 0.05431131019036954}  |
 
 
 ### Framework versions