update model card README.md

README.md

@@ -22,16 +22,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9270541742137329
+      value: 0.934260639178672
     - name: Recall
       type: recall
-      value: 0.9474924267923258
+      value: 0.9495119488387749
     - name: F1
       type: f1
-      value: 0.9371618809821057
+      value: 0.9418245555462816
     - name: Accuracy
       type: accuracy
-      value: 0.9859598516512628
+      value: 0.9868281627126626
 ---
 
 <!-- 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: 0.0608
-- Precision: 0.9271
-- Recall: 0.9475
-- F1: 0.9372
-- Accuracy: 0.9860
+- Loss: 0.0573
+- Precision: 0.9343
+- Recall: 0.9495
+- F1: 0.9418
+- Accuracy: 0.9868
 
 ## Model description
 
@@ -76,14 +76,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0865        | 1.0   | 1756 | 0.0623          | 0.9193    | 0.9409 | 0.9300 | 0.9833   |
-| 0.0407        | 2.0   | 3512 | 0.0594          | 0.9250    | 0.9487 | 0.9367 | 0.9851   |
-| 0.02          | 3.0   | 5268 | 0.0608          | 0.9271    | 0.9475 | 0.9372 | 0.9860   |
+| 0.0854        | 1.0   | 1756 | 0.0639          | 0.9148    | 0.9329 | 0.9238 | 0.9822   |
+| 0.0403        | 2.0   | 3512 | 0.0542          | 0.9370    | 0.9512 | 0.9440 | 0.9866   |
+| 0.0204        | 3.0   | 5268 | 0.0573          | 0.9343    | 0.9495 | 0.9418 | 0.9868   |
 
 
 ### Framework versions
 
-- Transformers 4.20.1
-- Pytorch 1.12.0+cu113
-- Datasets 2.3.2
+- Transformers 4.18.0
+- Pytorch 1.11.0
+- Datasets 2.1.0
 - Tokenizers 0.12.1