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Laya fine-tuned on GIZ vulnerability data: macro-F1 0.654 (zero-shot 0.108)
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metadata
license: apache-2.0
library_name: transformers
tags:
  - laya
  - text-classification
  - multi-label
  - climate
  - vulnerability
  - rlcd
pipeline_tag: text-classification

Laya fine-tuned for climate-vulnerability group detection (multi-label)

convaiinnovations/laya (421M, ModernBERT-large backbone) fine-tuned with the official RLCD recipe on GIZ/vulnerability_training_data_full (380 train rows x 17 binary vulnerability-group questions; 36 all-negative rows included as negatives).

Each vulnerability group is asked as one binary (noul) typed question; all 17 are answered in a single forward pass. Evaluate with laya.load("peter2000/laya-vulnerability-groups") and agent.predict(state, questions).

Test-set metrics (held-out 95 rows, threshold 0.5)

metric value
macro-F1 0.6544
micro-F1 0.6694
ECE 0.0263
subset accuracy 0.4737

Per-label F1:

label F1
Agricultural communities 0.9565
Coastal communities 0.5000
Ethnic, racial or other minorities 0.6000
Fishery communities 0.4000
Informal sector workers 1.0000
Members of indigenous and local communities 0.9333
Migrants and displaced persons 0.5714
Older persons 0.8889
Other 0.0000
Persons living in poverty 0.3333
Persons with disabilities 1.0000
Persons with pre-existing health conditions 0.8000
Residents of drought-prone regions 0.5714
Rural populations 0.8000
Sexual minorities (LGBTQI+) 0.3333
Urban populations 0.5714
Women and other genders 0.8649