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silent-signals-rqb
calerio/silent-signals-rqb
silent-signals-rqb is a machine learning model from calerio. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Multiclass ingroup classifier (17 classes; train-only label space). RoBERTa-base.
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At a glance
- Access
- Public
- Created
- Apr 29, 2026
- Updated
- Apr 29, 2026
- SHA
- c7676c3e
Model card
From the Hugging Face model README
calerio/silent-signals-rqb
Multiclass ingroup classifier (17 classes; train-only label space). RoBERTa-base.
Headline metric: f1_macro — macro-F1 on the grouped-split test (held-out roots; see docs/rq_b_report.md § 4.1).
Variants
Each variant is checked into its own branch. Load with:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("calerio/silent-signals-rqb", revision="<branch>")
tok = AutoTokenizer.from_pretrained("calerio/silent-signals-rqb", revision="<branch>")
| Branch | Variant id | f1_macro | Notes |
|---|---|---|---|
term-seed123 | rqb_term_seed123 | 0.3626 | default |
term-seed42 | rqb_term_seed42 | 0.3491 | — |
term-seed7 | rqb_term_seed7 | 0.3468 | — |
term-altsplit-seed42 | rqb_term_altsplit_seed42 | 0.9964 | raw leader (not default — see below) |
term-weighted-seed42 | rqb_term_weighted_seed42 | 0.3346 | — |
text-only-seed42 | rqb_text_only_seed42 | 0.3140 | — |
Default variant
rqb_term_seed123 — see the per-task default_variant_rationale in data/manifests/model_inventory.json of the project repo.
Restricted to Run A (term arm, grouped split, no run_tag) — the headline system in docs/rq_b_report.md. Run C (altsplit, 0.996) is excluded: it's a glossary-determinism artefact, not generalization, and defaulting to it would misrepresent RQ-B's central finding. The Run C model remains selectable in the dropdown for the educational tab (Step 6).
Where this came from
Bocconi 597 NLP group project on dog-whistle detection and disambiguation, on the silent_signals corpus (Kruk et al. 2024). Full methodology: docs/DESIGN_DEFENSE.md + per-RQ reports in the project repo. HF Space build write-up: docs/hf_space_report.md.
- Created
- Apr 29, 2026
- Updated
- Apr 29, 2026