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Laya fine-tuned on GIZ vulnerability data: macro-F1 0.654 (zero-shot 0.108)

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Files changed (3) hide show
  1. README.md +21 -21
  2. model.safetensors +1 -1
  3. rl_agent_config.json +2 -2
README.md CHANGED
@@ -14,33 +14,33 @@ fine-tuned with the official RLCD recipe on [GIZ/vulnerability_training_data_ful
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  Each vulnerability group is asked as one binary (`noul`) typed question; all 17 are answered in a single forward pass.
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  Evaluate with `laya.load("peter2000/laya-vulnerability-groups")` and `agent.predict(state, questions)`.
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- ## Test-set metrics (held-out 5 rows, threshold 0.5)
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  | metric | value |
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  |---|---|
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- | macro-F1 | 0.0000 |
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- | micro-F1 | 0.0000 |
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- | ECE | 0.0688 |
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- | subset accuracy | 0.0000 |
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  Per-label F1:
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  | label | F1 |
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  |---|---|
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- | Agricultural communities | 0.0000 |
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- | Coastal communities | 0.0000 |
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- | Ethnic, racial or other minorities | 0.0000 |
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- | Fishery communities | 0.0000 |
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- | Informal sector workers | 0.0000 |
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- | Members of indigenous and local communities | 0.0000 |
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- | Migrants and displaced persons | 0.0000 |
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- | Older persons | 0.0000 |
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  | Other | 0.0000 |
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- | Persons living in poverty | 0.0000 |
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- | Persons with disabilities | 0.0000 |
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- | Persons with pre-existing health conditions | 0.0000 |
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- | Residents of drought-prone regions | 0.0000 |
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- | Rural populations | 0.0000 |
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- | Sexual minorities (LGBTQI+) | 0.0000 |
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- | Urban populations | 0.0000 |
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- | Women and other genders | 0.0000 |
 
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  Each vulnerability group is asked as one binary (`noul`) typed question; all 17 are answered in a single forward pass.
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  Evaluate with `laya.load("peter2000/laya-vulnerability-groups")` and `agent.predict(state, questions)`.
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+ ## Test-set metrics (held-out 95 rows, threshold 0.5)
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  | metric | value |
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  |---|---|
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+ | macro-F1 | 0.6544 |
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+ | micro-F1 | 0.6694 |
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+ | ECE | 0.0263 |
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+ | subset accuracy | 0.4737 |
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  Per-label F1:
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  | label | F1 |
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  |---|---|
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+ | Agricultural communities | 0.9565 |
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+ | Coastal communities | 0.5000 |
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+ | Ethnic, racial or other minorities | 0.6000 |
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+ | Fishery communities | 0.4000 |
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+ | Informal sector workers | 1.0000 |
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+ | Members of indigenous and local communities | 0.9333 |
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+ | Migrants and displaced persons | 0.5714 |
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+ | Older persons | 0.8889 |
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  | Other | 0.0000 |
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+ | Persons living in poverty | 0.3333 |
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+ | Persons with disabilities | 1.0000 |
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+ | Persons with pre-existing health conditions | 0.8000 |
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+ | Residents of drought-prone regions | 0.5714 |
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+ | Rural populations | 0.8000 |
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+ | Sexual minorities (LGBTQI+) | 0.3333 |
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+ | Urban populations | 0.5714 |
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+ | Women and other genders | 0.8649 |
model.safetensors CHANGED
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rl_agent_config.json CHANGED
@@ -13,13 +13,13 @@
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  "temperature": [
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  1.2,
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  1.2,
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- 1.0
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  ],
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  "temperature_by_options": {
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  "choice:3-5": 1.7601518630981445,
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  "choice:6-10": 1.0000158548355103,
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  "score:3-5": 1.2514300346374512,
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- "noul:2": 1.0,
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  "choice:11+": 0.10058280825614929,
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  "choice:2": 1.9063563346862793
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  },
 
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  "temperature": [
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  1.2,
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  1.2,
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+ 4.928757667541504
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  ],
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  "temperature_by_options": {
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  "choice:3-5": 1.7601518630981445,
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  "choice:6-10": 1.0000158548355103,
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  "score:3-5": 1.2514300346374512,
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+ "noul:2": 4.928757667541504,
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  "choice:11+": 0.10058280825614929,
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  "choice:2": 1.9063563346862793
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  },