update model card README.md

README.md

@@ -22,16 +22,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.502770083102493
+      value: 0.5312084993359893
     - name: Recall
       type: recall
-      value: 0.33642261353104724
+      value: 0.3707136237256719
     - name: F1
       type: f1
-      value: 0.4031093836757356
+      value: 0.4366812227074236
     - name: Accuracy
       type: accuracy
-      value: 0.9428840152195289
+      value: 0.9447223291009362
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -41,11 +41,11 @@ 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: 0.2724
-- Precision: 0.5028
-- Recall: 0.3364
-- F1: 0.4031
-- Accuracy: 0.9429
+- Loss: 0.2634
+- Precision: 0.5312
+- Recall: 0.3707
+- F1: 0.4367
+- Accuracy: 0.9447
 
 ## Model description
 
@@ -76,9 +76,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 213  | 0.2849          | 0.4606    | 0.2382 | 0.3140 | 0.9374   |
-| No log        | 2.0   | 426  | 0.2610          | 0.5439    | 0.3216 | 0.4042 | 0.9424   |
-| 0.1949        | 3.0   | 639  | 0.2724          | 0.5028    | 0.3364 | 0.4031 | 0.9429   |
+| No log        | 1.0   | 213  | 0.2764          | 0.4652    | 0.2604 | 0.3339 | 0.9382   |
+| No log        | 2.0   | 426  | 0.2590          | 0.5887    | 0.3475 | 0.4371 | 0.9435   |
+| 0.1938        | 3.0   | 639  | 0.2634          | 0.5312    | 0.3707 | 0.4367 | 0.9447   |
 
 
 ### Framework versions