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--- |
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language: en |
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tags: |
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- code |
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- algorithms |
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- competitive-programming |
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- multi-label-classification |
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- codebert |
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datasets: |
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- xCodeEval |
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metrics: |
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- f1 |
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- precision |
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- recall |
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library_name: transformers |
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pipeline_tag: text-classification |
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--- |
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# CodeBERT Algorithm Tagger |
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A fine-tuned CodeBERT model for multi-label classification of algorithmic problems from competitive programming platforms like Codeforces. |
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## Model Description |
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This model predicts algorithmic tags/categories for competitive programming problems based on their problem descriptions and solution code. |
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**Supported Tags:** |
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- math |
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- graphs |
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- strings |
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- number theory |
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- trees |
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- geometry |
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- games |
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- probabilities |
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## Training Data |
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- **Dataset**: xCodeEval (Codeforces problems) |
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- **Training examples**: 2,147 problems (filtered for focus tags) |
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- **Test examples**: 531 problems |
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- **Source**: Problems and solutions from Codeforces platform |
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### Model Architecture |
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- **Input**: Concatenated problem description and solution code |
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- **Encoder**: CodeBERT (RoBERTa-based architecture) |
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- **Output**: 8-dimensional binary classification (one per tag) |
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## Usage |
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### Installation |
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```bash |
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pip install transformers torch |
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``` |
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