rafmacalaba
/

lfm2.5-350M-datause

@@ -1,207 +1,77 @@
 ---
-base_model: LiquidAI/LFM2.5-350M
-library_name: peft
 pipeline_tag: text-generation
 tags:
-- base_model:adapter:LiquidAI/LFM2.5-350M
-- lora
-- transformers
 ---
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-### Framework versions
-- PEFT 0.20.0

 ---
+license: apache-2.0
 pipeline_tag: text-generation
 tags:
+  - lfm2
+  - data-use
+  - data-mentions
+  - extraction
+  - sft
+  - lora
 ---
+# lfm2.5-350M-datause
+LoRA SFT of `LiquidAI/LFM2.5-350M` for data-mention extraction: emit the
+data-bearing phrases in a text as compact JSON
+(`data_mentions` with `data_mention`/`specificity_type`).
+## Training
+- base model: `LiquidAI/LFM2.5-350M`
+- dataset: `rafmacalaba/data-use-mention-sft`
+- epochs: 3
+- learning rate: 0.0002
+- LoRA: r=16 alpha=32 dropout=0.05
+- completion-only masking (loss on assistant JSON turn)
+## Evaluation (holdout, n=12531)
+Jaccard entity-level matching: acronym-aware span clustering +
+Hungarian optimal bipartite match (match thr=0.5), F0.5
+primary. Aligned with `rafmacalaba/gliner_datause_extended`. The
+holdout is `rafmacalaba/data-use-mention-sft`, so numbers are **not
+directly comparable** to the GLiNER model's `data-use-mentions-extended`
+holdout.
+| label | tp | fp | fn | precision | recall | f0.5 | f1 |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| **overall** | 13176 | 3097 | 2998 | 0.8097 | 0.8146 | 0.8107 | 0.8122 |
+## Per-label
+| label | tp | fp | fn | precision | recall | f0.5 | f1 |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| descriptive | 5522 | 2631 | 2078 | 0.6773 | 0.7266 | 0.6866 | 0.7011 |
+| named | 5344 | 1538 | 1629 | 0.7765 | 0.7664 | 0.7745 | 0.7714 |
+| vague | 670 | 604 | 934 | 0.5259 | 0.4177 | 0.5000 | 0.4656 |
+## Per-corpus
+| label | tp | fp | fn | precision | recall | f0.5 | f1 |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| fcv | 3142 | 619 | 730 | 0.8354 | 0.8115 | 0.8305 | 0.8233 |
+| prwp | 10034 | 2478 | 2268 | 0.8020 | 0.8156 | 0.8047 | 0.8087 |
+## Per-origin
+| label | tp | fp | fn | precision | recall | f0.5 | f1 |
+| --- | --- | --- | --- | --- | --- | --- | --- |
+| fcv_pads_east_asia | 728 | 96 | 110 | 0.8835 | 0.8687 | 0.8805 | 0.8761 |
+| general_prwp | 10034 | 2478 | 2268 | 0.8020 | 0.8156 | 0.8047 | 0.8087 |
+| jdc_operational | 149 | 25 | 24 | 0.8563 | 0.8613 | 0.8573 | 0.8588 |
+| refugee_pads | 704 | 147 | 152 | 0.8273 | 0.8224 | 0.8263 | 0.8248 |
+| reliefweb | 1561 | 351 | 444 | 0.8164 | 0.7786 | 0.8086 | 0.7970 |
+## Sample predictions (holdout)
+| gold | predicted |
+| --- | --- |
+| {"data_mentions":[{"data_mention":"administrative data","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"administrative data","specificity_type":"descriptive"}]} |
+| {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"CPHS","spe | {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"CPHS","spe |
+| {"data_mentions":[{"data_mention":"ES data","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"ES data","specificity_type":"named"}]} |
+| {"data_mentions":[]} | {"data_mentions":[{"data_mention":"EUROMOD I4.0+","specificity_type":"named"}]} |
+| {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"IMF World  | {"data_mentions":[{"data_mention":"World Development Indicators","specificity_type":"named"},{"data_mention":"IMF World  |
+| {"data_mentions":[]} | {"data_mentions":[]} |
+| {"data_mentions":[]} | {"data_mentions":[]} |
+| {"data_mentions":[{"data_mention":"UNESCO-provided data","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"PIRLS","specificity_type":"named"},{"data_mention":"UNESCO-provided data","specificit |
+| {"data_mentions":[{"data_mention":"IHPS dataset","specificity_type":"named"},{"data_mention":"IHS4 data","specificity_ty | {"data_mentions":[{"data_mention":"IHS4","specificity_type":"named"},{"data_mention":"IHPS dataset","specificity_type":" |
+| {"data_mentions":[{"data_mention":"HFSSS","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"HFSSS","specificity_type":"named"}]} |
+| {"data_mentions":[{"data_mention":"HFCS data","specificity_type":"named"}]} | {"data_mentions":[{"data_mention":"HFCS data","specificity_type":"named"}]} |
+| {"data_mentions":[{"data_mention":"data on patents and publications","specificity_type":"descriptive"}]} | {"data_mentions":[{"data_mention":"data on patents and publications","specificity_type":"descriptive"}]} |