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@@ -10,14 +10,16 @@ metrics:
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  model-index:
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  - name: codebert-code-clone-detector
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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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- should probably proofread and complete it, then remove this comment. -->
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  # codebert-code-clone-detector
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- This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on the None dataset.
 
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  It achieves the following results on the evaluation set:
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  - Loss: 0.3452
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  - Accuracy: 0.9525
@@ -67,4 +69,4 @@ The following hyperparameters were used during training:
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  - Transformers 4.39.3
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  - Pytorch 2.1.2
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  - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  model-index:
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  - name: codebert-code-clone-detector
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  results: []
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+ license: mit
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+ pipeline_tag: sentence-similarity
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  ---
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+
 
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  # codebert-code-clone-detector
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+ This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on a Code Clone Benchmark dataset.
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+ See this [github repository](https://github.com/LucK1Y/CodeCloneBERT) for more information.
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  It achieves the following results on the evaluation set:
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  - Loss: 0.3452
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  - Accuracy: 0.9525
 
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  - Transformers 4.39.3
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  - Pytorch 2.1.2
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  - Datasets 2.18.0
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+ - Tokenizers 0.15.2