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VeriPromise_ESG_2026_9906_SetFit
maxbeettww/VeriPromise_ESG_2026_9906_SetFit
VeriPromise_ESG_2026_9906_SetFit is a machine learning model from maxbeettww. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository stores SetFit artifacts generated by app/model/modelsetfit.ipynb.
Access
Public
Updated Jun 11, 2026
Repo size
44.8 GB
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0
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Repo makeup
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At a glance
- Access
- Public
- Created
- Jun 3, 2026
- Updated
- Jun 11, 2026
- SHA
- a636ea9c
Model card
From the Hugging Face model README
VeriPromiseESG Multi-Task SetFit
This repository stores SetFit artifacts generated by app/model/model_setfit.ipynb.
Artifact Layout
fold_1/encoder/
fold_1/task_heads.joblib
...
fold_5/encoder/
fold_5/task_heads.joblib
setfit_thresholds.json
setfit_inference_config.json
setfit_oof_predictions.csv
setfit_oof_probabilities.csv
Model
- Primary encoder:
yiyanghkust/finbert-tone-chinese - Fallback encoder:
yiyanghkust/finbert-tone-chinese - One shared SentenceTransformer encoder is trained once per fold.
- Encoder checkpoints maximize competition-weighted T1-T4 validation pair AP.
- Task heads are selected by fold validation macro F1.
- T2 supports an ordinal cumulative-logistic head.
- Inference routing matches the original submission format.
Thresholds
- T1 threshold:
0.21 - T3 threshold:
0.48
Validation
- OOF average macro F1: not recorded
- OOF competition score: not recorded
- T1/T3 quality gate passed:
True
Inference
Use app/model/model_setfit_inference.ipynb and pass this repository id to ensemble_inference_and_export.
Repository id: maxbeettww/VeriPromise_ESG_2026_9906_SetFit
Output Columns
id,promise_status,verification_timeline,evidence_status,evidence_quality
- Created
- Jun 3, 2026
- Updated
- Jun 11, 2026