---
license: mit
library_name: transformers
tags:
- reinforcement-learning
- cognitive-offloading
- education
- dqn
- deberta
- pytorch
---

# Cognitive Offloading Detection & Adaptive Pedagogical Policy Models

Model artifacts for the [Cognitive Offloading Prevention System](https://github.com/Addy0606/cognitiveoffloading).

## Contents
- **`classifier_v1/`**: `microsoft/deberta-base` fine-tuned to classify student messages for cognitive offloading / answer extraction behavior.
  - `backbone/`: Tokenizer files and transformer base weights (`model.safetensors`).
  - `head.pth`: 2-layer MLP classification head (`768 -> 256 -> 64 -> 2`).
  - `config.json`: Model configuration and hyperparameters.
- **`policy_network_v1.pth`**: Deep Q-Network (DQN) policy trained via reinforcement learning to select dynamic pedagogical intervention actions (`redirect`, `scaffold`, `socratic`, `delay`) balancing learning gains against engagement friction.

## Usage
To download these models locally:
```python
from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="addy0606/cognitive-offloading",
    local_dir="models",
)
```

## GitHub Repository
Source code, evaluation pipeline, and Flask interface:
https://github.com/Addy0606/cognitiveoffloading