update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5595238095238095
+      value: 0.5337954939341422
     - name: Recall
       type: recall
-      value: 0.3049119555143652
+      value: 0.28544949026876737
     - name: F1
       type: f1
-      value: 0.3947210557888423
+      value: 0.37198067632850246
     - name: Accuracy
       type: accuracy
-      value: 0.9413877132230345
+      value: 0.9402761745970672
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2703
-- Precision: 0.5595
-- Recall: 0.3049
-- F1: 0.3947
-- Accuracy: 0.9414
+- Loss: 0.2793
+- Precision: 0.5338
+- Recall: 0.2854
+- F1: 0.3720
+- Accuracy: 0.9403
 
 ## Model description
 
@@ -78,8 +78,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 213  | 0.2779          | 0.5441    | 0.2799 | 0.3696 | 0.9393   |
-| No log        | 2.0   | 426  | 0.2703          | 0.5595    | 0.3049 | 0.3947 | 0.9414   |
+| No log        | 1.0   | 213  | 0.2933          | 0.3959    | 0.1798 | 0.2473 | 0.9347   |
+| No log        | 2.0   | 426  | 0.2793          | 0.5338    | 0.2854 | 0.3720 | 0.9403   |
 
 
 ### Framework versions