update model card README.md

README.md

@@ -4,34 +4,9 @@ tags:
 - generated_from_trainer
 datasets:
 - conll2003
-metrics:
-- precision
-- recall
-- f1
-- accuracy
 model-index:
 - name: bert-base-NER-finetuned-ner
-  results:
-  - task:
-      name: Token Classification
-      type: token-classification
-    dataset:
-      name: conll2003
-      type: conll2003
-      args: conll2003
-    metrics:
-    - name: Precision
-      type: precision
-      value: 0.9327342290239345
-    - name: Recall
-      type: recall
-      value: 0.9405167773192177
-    - name: F1
-      type: f1
-      value: 0.9366093366093367
-    - name: Accuracy
-      type: accuracy
-      value: 0.9850621063165951
+  results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -40,12 +15,6 @@ should probably proofread and complete it, then remove this comment. -->
 # bert-base-NER-finetuned-ner
 
 This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the conll2003 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0723
-- Precision: 0.9327
-- Recall: 0.9405
-- F1: 0.9366
-- Accuracy: 0.9851
 
 ## Model description
 
@@ -72,15 +41,6 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 3
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 220  | 0.0754          | 0.9225    | 0.9296 | 0.9260 | 0.9831   |
-| No log        | 2.0   | 440  | 0.0688          | 0.9319    | 0.9407 | 0.9363 | 0.9849   |
-| 0.0717        | 3.0   | 660  | 0.0723          | 0.9327    | 0.9405 | 0.9366 | 0.9851   |
-
-
 ### Framework versions
 
 - Transformers 4.18.0