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  model-index:
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  - name: vulnerability-severity-classification-chinese-macbert-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
@@ -16,23 +18,14 @@ should probably proofread and complete it, then remove this comment. -->
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  # vulnerability-severity-classification-chinese-macbert-base
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- This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on an unknown dataset.
 
 
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6177
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  - Accuracy: 0.7801
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- ## Model description
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-
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- More information needed
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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- More information needed
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  ## Training procedure
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  ### Training hyperparameters
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  - Transformers 4.51.3
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  - Pytorch 2.7.1+cu126
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  - Datasets 3.6.0
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- - Tokenizers 0.21.1
 
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  model-index:
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  - name: vulnerability-severity-classification-chinese-macbert-base
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  results: []
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+ datasets:
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+ - CIRCL/Vulnerability-CNVD
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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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  # vulnerability-severity-classification-chinese-macbert-base
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+ This model is a fine-tuned version of [hfl/chinese-macbert-base](https://huggingface.co/hfl/chinese-macbert-base) on the dataset [CIRCL/Vulnerability-CNVD](https://huggingface.co/datasets/CIRCL/Vulnerability-CNVD).
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+ You can read [this page](https://www.vulnerability-lookup.org/user-manual/ai/) for more information.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.6177
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  - Accuracy: 0.7801
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  ## Training procedure
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  ### Training hyperparameters
 
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  - Transformers 4.51.3
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  - Pytorch 2.7.1+cu126
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  - Datasets 3.6.0
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+ - Tokenizers 0.21.1