update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.9245439469320066
+      value: 0.9293063391968138
     - name: Recall
       type: recall
-      value: 0.9382362840794345
+      value: 0.9424436216762033
     - name: F1
       type: f1
-      value: 0.9313397928499834
+      value: 0.9358288770053477
     - name: Accuracy
       type: accuracy
-      value: 0.985050915849842
+      value: 0.9860676442086199
 ---
 
 <!-- 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 conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0601
-- Precision: 0.9245
-- Recall: 0.9382
-- F1: 0.9313
-- Accuracy: 0.9851
+- Loss: 0.0594
+- Precision: 0.9293
+- Recall: 0.9424
+- F1: 0.9358
+- Accuracy: 0.9861
 
 ## Model description
 
@@ -78,9 +78,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0799        | 1.0   | 1756 | 0.0567          | 0.9186    | 0.9303 | 0.9244 | 0.9844   |
-| 0.0362        | 2.0   | 3512 | 0.0576          | 0.9215    | 0.9367 | 0.9291 | 0.9846   |
-| 0.0201        | 3.0   | 5268 | 0.0601          | 0.9245    | 0.9382 | 0.9313 | 0.9851   |
+| 0.0807        | 1.0   | 1756 | 0.0581          | 0.9156    | 0.9317 | 0.9236 | 0.9845   |
+| 0.0364        | 2.0   | 3512 | 0.0567          | 0.9252    | 0.9384 | 0.9317 | 0.9852   |
+| 0.0202        | 3.0   | 5268 | 0.0594          | 0.9293    | 0.9424 | 0.9358 | 0.9861   |
 
 
 ### Framework versions