README.md

metadata

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.

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:

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