update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.8585940019348597
+      value: 0.8597087378640776
     - name: Recall
       type: recall
-      value: 0.8961629081117469
+      value: 0.8941433860652979
     - name: F1
       type: f1
-      value: 0.8769762845849803
+      value: 0.8765880217785844
     - name: Accuracy
       type: accuracy
-      value: 0.9764312118219713
+      value: 0.9760991339759331
 ---
 
 <!-- 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 [klue/bert-base](https://huggingface.co/klue/bert-base) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0967
-- Precision: 0.8586
-- Recall: 0.8962
-- F1: 0.8770
-- Accuracy: 0.9764
+- Loss: 0.0943
+- Precision: 0.8597
+- Recall: 0.8941
+- F1: 0.8766
+- Accuracy: 0.9761
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.1317        | 1.0   | 1756 | 0.1035          | 0.7946    | 0.8516 | 0.8221 | 0.9679   |
-| 0.0648        | 2.0   | 3512 | 0.0943          | 0.8420    | 0.8879 | 0.8644 | 0.9751   |
-| 0.0381        | 3.0   | 5268 | 0.0967          | 0.8586    | 0.8962 | 0.8770 | 0.9764   |
+| 0.1321        | 1.0   | 1756 | 0.1003          | 0.8010    | 0.8514 | 0.8254 | 0.9687   |
+| 0.0654        | 2.0   | 3512 | 0.0927          | 0.8331    | 0.8862 | 0.8588 | 0.9739   |
+| 0.0382        | 3.0   | 5268 | 0.0943          | 0.8597    | 0.8941 | 0.8766 | 0.9761   |
 
 
 ### Framework versions