Downloads · 30 days
0
0% of all-time downloads
calerio/silent-signals-rqa
silent-signals-rqa 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.
Binary disambiguator — coded vs literal use of a candidate dog-whistle term. RoBERTa-base.
Downloads · 30 days
0
0% of all-time downloads
All-time downloads
44
Public
Repo size
3 GB
Likes
0
Public
Click a slice to open those files.
.md1.8 KB · 54%
From the Hugging Face model README
Binary disambiguator — coded vs literal use of a candidate dog-whistle term. RoBERTa-base.
Headline metric: disambiguation_124_f1 — F1 on the 124-row locked human-eval disambiguation set (see DESIGN_DEFENSE.md D7).
Each variant is checked into its own branch. Load with:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("calerio/silent-signals-rqa", revision="<branch>")
tok = AutoTokenizer.from_pretrained("calerio/silent-signals-rqa", revision="<branch>")
| Branch | Variant id | disambiguation_124_f1 | Notes |
|---|---|---|---|
term-seed123 | rqa_term_seed123 | 0.6880 | — |
term-seed42 | rqa_term_seed42 | 0.7097 | — |
term-seed7 | rqa_term_seed7 | 0.7246 | default |
term-enriched-def-seed123 | rqa_term_enriched_def_seed123 | 0.6774 | — |
term-enriched-def-seed42 | rqa_term_enriched_def_seed42 | 0.6992 | — |
term-enriched-def-seed7 | rqa_term_enriched_def_seed7 | 0.7296 | raw leader (not default — see below) |
rqa_term_seed7 — see the per-task default_variant_rationale in data/manifests/model_inventory.json of the project repo.
Picked the arm with the highest mean disambiguation_124_f1 across seeds (term = 0.7074), then the best seed within. Defends a per-arm comparison, not a single-seed peak. See docs/rq_a_report.md.
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.