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update model card README.md

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@@ -3,9 +3,36 @@ tags:
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  - generated_from_trainer
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  datasets:
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  - klue
 
 
 
 
 
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  model-index:
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  - name: ko_roberta_small_model
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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
@@ -13,7 +40,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # ko_roberta_small_model
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- This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the klue dataset.
 
 
 
 
 
 
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 2
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  ### Framework versions
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  - Transformers 4.28.0
 
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  - generated_from_trainer
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  datasets:
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  - klue
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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  model-index:
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  - name: ko_roberta_small_model
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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: klue
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+ type: klue
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+ config: ner
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+ split: validation
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+ args: ner
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+ metrics:
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+ - name: Precision
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+ type: precision
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+ value: 0.6827303934512807
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+ - name: Recall
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+ type: recall
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+ value: 0.7253980500806622
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+ - name: F1
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+ type: f1
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+ value: 0.703417786090801
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9403969397937687
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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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  # ko_roberta_small_model
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+ This model is a fine-tuned version of [hyeonseo/ko_roberta_small_model](https://huggingface.co/hyeonseo/ko_roberta_small_model) on the klue dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1864
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+ - Precision: 0.6827
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+ - Recall: 0.7254
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+ - F1: 0.7034
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+ - Accuracy: 0.9404
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  ## Model description
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  - lr_scheduler_type: linear
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  - num_epochs: 2
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.2341 | 1.0 | 1313 | 0.2069 | 0.6516 | 0.6999 | 0.6749 | 0.9336 |
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+ | 0.16 | 2.0 | 2626 | 0.1864 | 0.6827 | 0.7254 | 0.7034 | 0.9404 |
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+
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+
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  ### Framework versions
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  - Transformers 4.28.0