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- License
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## Model Info
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There are three BERT models, each fine-tuned on a dataset of
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- `bert_lc100_hp25`: This model classifies code based on the 25th percentile as its threshold. It is designed for identifying lower quartile code solutions in terms of quality or performance.
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- `bert_lc100_hp50`: Operating with a median-based approach, this model uses the 50th percentile as its classification threshold. It is suitable for general assessments, providing a balanced view of code quality.
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- `bert_lc100_regression`: Unlike the others, this is a regression model. It provides a nuanced prediction of the overall code quality score, offering a more detailed evaluation compared to the binary classification approach.
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- License
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## Model Info
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There are three BERT models, each fine-tuned on a dataset of 70K Python 3 solutions submitted by users for problems #1 through #100 on LeetCode:
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- `bert_lc100_hp25`: This model classifies code based on the 25th percentile as its threshold. It is designed for identifying lower quartile code solutions in terms of quality or performance.
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- `bert_lc100_hp50`: Operating with a median-based approach, this model uses the 50th percentile as its classification threshold. It is suitable for general assessments, providing a balanced view of code quality.
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- `bert_lc100_regression`: Unlike the others, this is a regression model. It provides a nuanced prediction of the overall code quality score, offering a more detailed evaluation compared to the binary classification approach.
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