--- 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"}]} |