update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5355648535564853
+      value: 0.5310245310245311
     - name: Recall
       type: recall
-      value: 0.35588507877664505
+      value: 0.3410565338276182
     - name: F1
       type: f1
-      value: 0.4276169265033407
+      value: 0.4153498871331829
     - name: Accuracy
       type: accuracy
-      value: 0.9440383053311102
+      value: 0.9433542815612842
 ---
 
 <!-- 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: 0.2542
-- Precision: 0.5356
-- Recall: 0.3559
-- F1: 0.4276
-- Accuracy: 0.9440
+- Loss: 0.2699
+- Precision: 0.5310
+- Recall: 0.3411
+- F1: 0.4153
+- Accuracy: 0.9434
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 213  | 0.2542          | 0.5356    | 0.3559 | 0.4276 | 0.9440   |
-| No log        | 2.0   | 426  | 0.2605          | 0.5538    | 0.3818 | 0.4520 | 0.9460   |
-| 0.0867        | 3.0   | 639  | 0.2745          | 0.5153    | 0.3911 | 0.4447 | 0.9459   |
+| No log        | 1.0   | 213  | 0.2802          | 0.5587    | 0.2956 | 0.3867 | 0.9393   |
+| No log        | 2.0   | 426  | 0.2642          | 0.5698    | 0.3216 | 0.4111 | 0.9422   |
+| 0.188         | 3.0   | 639  | 0.2699          | 0.5310    | 0.3411 | 0.4153 | 0.9434   |
 
 
 ### Framework versions