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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
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