Update README.md

README.md

@@ -1,9 +1,5 @@
 ---
 license: apache-2.0
-tags:
-- generated_from_trainer
-datasets:
-- conll2003
 metrics:
 - precision
 - recall
@@ -34,57 +30,12 @@ model-index:
     - name: Accuracy
       type: accuracy
       value: 0.9788521589318402
+language:
+- en
+- id
+pipeline_tag: token-classification
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # bert-base-uncased-conll2003
 
-This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.0423
-- Precision: 0.8859
-- Recall: 0.9076
-- F1: 0.8966
-- Accuracy: 0.9789
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
-- seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- num_epochs: 2
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.0101        | 1.0   | 3922 | 0.0392          | 0.8840    | 0.8996 | 0.8917 | 0.9783   |
-| 0.0044        | 2.0   | 7844 | 0.0423          | 0.8859    | 0.9076 | 0.8966 | 0.9789   |
-
-
-### Framework versions
-
-- Transformers 4.30.2
-- Pytorch 2.0.1
-- Datasets 2.13.0
-- Tokenizers 0.13.3
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the conll2003 dataset.