Ishaank18/scn-deberta-v3-large

Span Consistency Network (SCN) + DeBERTa-v3-Large

Custom architecture + custom loss (SCRD) trained for span-level extraction.

Architecture

• Encoder: microsoft/deberta-v3-large
• Span Consistency Network (SCN)
• Marker-specific span width priors
• Cross-marker attention (Actor → Action → Effect)
• Loss: Span-Count Regularized Dice (SCRD)

Files

• model.pt: PyTorch state dict + config
• Tokenizer files: standard HuggingFace tokenizer artifacts

Usage

This is not a transformers.PreTrainedModel.

Load manually in PyTorch:

import torch
ckpt = torch.load('model.pt', map_location='cpu')
model.load_state_dict(ckpt['model_state_dict'])

Citation

If you use this model, please cite the associated paper or repository.