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