Same 200k-row floret table as fa_ent_news_lg, now with dep/core too.
- configs/fa_dep_news_lg.cfg (fa_dep_news_md.cfg unchanged except vectors)
- project.yml: lg workflow expanded to train-dep-lg, finalize-dep-lg,
assemble-core-lg, evaluate-lg, finalize-meta-lg, package-lg,
smoke-lg (mirrors the md tier's dep/core commands)
- scripts/compare_tiers.py: dep/core UD test groups now 3-way (sm/md/lg)
- scripts/finalize_pipeline.py: FLORET_LG url points at the published
vectors, https://huggingface.co/Phazel/fa-floret-wiki-vectors
UD test: DEP_UAS 90.96 (sm 89.69, md 90.52), DEP_LAS 86.60 (sm 85.15,
md 86.34). NER unchanged from the earlier fa_ent_news_lg run, ENTS_F
75.94. docs/MODELS.md §7 rewritten from ent-only to the full tier.
New table: 200k rows x 300d, full Persian Wikipedia dump, 5 epochs,
vs md's 50k rows / 400k documents.
- configs/fa_ner_lg.cfg, project.yml ent-lg workflow (vectors-lg
through smoke-ent-lg)
- scripts/compare_tiers.py: generalized sm/md pair to N tiers; ent
NER test now includes lg; fixed sm baseline to the file that's
actually scored (perdt-ner-test.json, not the missing ent-test.json)
- scripts/finalize_pipeline.py: FLORET_LG source and vectors_note_lg
corrected to full Wikipedia, 5 epochs (were a generic Wikipedia +
OSCAR placeholder)
- docs/MODELS.md §7: PerDT NER test ENTS_F 75.94 (sm 71.87, md
74.71), full per-label table, cost (217 MB wheel)
Not built: fa_dep_news_lg / fa_core_news_lg.
- project.yml: new md workflow (vectors-md, train-dep-md, train-ner-md,
finalize-dep-md, assemble-core-md, evaluate-md, finalize-meta-md,
compare-md, package-md, smoke-md), same corpus/architecture as sm plus
the fa_floret static vector table (50k rows x 300d, 400k Persian
documents).
- configs/fa_dep_news_md.cfg, configs/fa_ner_md.cfg: byte-identical to the
sm configs except include_static_vectors, isolating what the vectors buy.
- scripts/unpack_vectors.py: extracts a floret wheel's vectors-only
pipeline into a directory --paths.vectors can point at.
- scripts/finalize_pipeline.py: --size now accepts md (floret source +
vectors note), plus lg/trf (used by the pending Colab notebook on
colab-lg-trf-training; lg's vectors note is generated from the trained
model's actual vector table shape since that tier is still being
iterated on).
- scripts/compare_tiers.py: sm vs md metrics diff.
- docs/MODELS.md, README.md, README.fa.md: md tier results, fa_ent_news_md
package row, and the analysis of why floret helps NER recall.
- docs/CONTRIBUTING-GUIDE.md, README.md, README.fa.md: fixed every
documented pip install URL. spacy huggingface-hub push names the
uploaded wheel '<name>-any-py3-none-any.whl'; 'any' is not a valid PEP
440 version, so current pip rejects it. Re-uploaded a correctly
versioned copy of every published wheel (fa_core_news_sm, fa_dep_news_sm,
fa_ent_news_md) to the Hub and repointed the docs at that filename.
Mohamad Fazeli