CREDENCE
Collection
CREDENCE checkpoints for text classification (sentiment, toxicity, emotion). Paper: https://huggingface.co/papers/2604.24170 • 41 items • Updated
CREDENCE checkpoint for cebab (sentiment) with backbone answerdotai/ModernBERT-base (5 concept heads).
Paper: https://huggingface.co/papers/2604.24170 · arXiv: 2604.24170
Training run folder: ModernBERT_20251224_071945
credence_checkpoint.pt — PyTorch checkpoint (model_state_dict, config, metadata, optimizer state)from huggingface_hub import hf_hub_download
import torch
path = hf_hub_download(repo_id="tankiit/credence-modernbert-20251224-071945-cebab", filename="credence_checkpoint.pt")
ckpt = torch.load(path, map_location="cpu", weights_only=False)
state = ckpt["model_state_dict"]
config = ckpt["config"]
Load into your CREDENCE model implementation (see project credence.py).
@article{mukherjee2026credence,
title={Credal Concept Bottleneck Models for Epistemic--Aleatoric Uncertainty Decomposition},
author={Mukherjee, et al.},
journal={arXiv preprint arXiv:2604.24170},
year={2026}
}
| Metric | Value |
|---|---|
| Accuracy | 0.6856 |
| ρ(epistemic, error) | 0.1418 |
| ρ(aleatoric, unknown) | 0.6781 |
Base model
answerdotai/ModernBERT-base