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README.md
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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
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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
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@@ -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
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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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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