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update model card README.md

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@@ -3,6 +3,8 @@ license: mit
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  base_model: vinai/phobert-base
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  tags:
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  - generated_from_trainer
 
 
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  metrics:
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  - precision
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  - recall
@@ -10,7 +12,26 @@ metrics:
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  - accuracy
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  model-index:
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  - name: ner_base
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- results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +39,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # ner_base
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- This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6385
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- - Precision: 0.6467
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- - Recall: 0.7038
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- - F1: 0.6741
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- - Accuracy: 0.8256
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  ## Model description
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  base_model: vinai/phobert-base
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - hts98/UIT
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  metrics:
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  - precision
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  - recall
 
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  - accuracy
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  model-index:
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  - name: ner_base
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+ results:
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+ - task:
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+ name: Token Classification
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+ type: token-classification
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+ dataset:
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+ name: hts98/UIT
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+ type: hts98/UIT
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.6524877545759217
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+ - name: Recall
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+ type: recall
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+ value: 0.7065884980457845
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+ - name: F1
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+ type: f1
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+ value: 0.6784613322610911
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.8276281577252451
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # ner_base
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+ This model is a fine-tuned version of [vinai/phobert-base](https://huggingface.co/vinai/phobert-base) on the hts98/UIT dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6160
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+ - Precision: 0.6525
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+ - Recall: 0.7066
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+ - F1: 0.6785
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+ - Accuracy: 0.8276
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  ## Model description
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