update model card README.md

README.md

@@ -22,16 +22,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9358041032428855
+      value: 0.9329479768786128
     - name: Recall
       type: recall
-      value: 0.9518680578929654
+      value: 0.9506900033658701
     - name: F1
       type: f1
-      value: 0.9437677290171868
+      value: 0.9417354338584647
     - name: Accuracy
       type: accuracy
-      value: 0.9862983457938423
+      value: 0.9863719314770119
 ---
 
 <!-- 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 [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0605
-- Precision: 0.9358
-- Recall: 0.9519
-- F1: 0.9438
-- Accuracy: 0.9863
+- Loss: 0.0609
+- Precision: 0.9329
+- Recall: 0.9507
+- F1: 0.9417
+- Accuracy: 0.9864
 
 ## Model description
 
@@ -76,9 +76,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0891        | 1.0   | 1756 | 0.0671          | 0.9166    | 0.9398 | 0.9280 | 0.9834   |
-| 0.033         | 2.0   | 3512 | 0.0610          | 0.9287    | 0.9465 | 0.9375 | 0.9852   |
-| 0.0213        | 3.0   | 5268 | 0.0605          | 0.9358    | 0.9519 | 0.9438 | 0.9863   |
+| 0.086         | 1.0   | 1756 | 0.0632          | 0.9255    | 0.9408 | 0.9331 | 0.9833   |
+| 0.0316        | 2.0   | 3512 | 0.0631          | 0.9252    | 0.9456 | 0.9353 | 0.9846   |
+| 0.0219        | 3.0   | 5268 | 0.0609          | 0.9329    | 0.9507 | 0.9417 | 0.9864   |
 
 
 ### Framework versions