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en_docusco_spacy_cd_trf
browndw/en_docusco_spacy_cd_trf
en_docusco_spacy_cd_trf is a token classification model from browndw. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as mit.
English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.
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Repo size
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Repo makeup
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Access
- Public
- Created
- Dec 11, 2022
- Updated
- May 24, 2024
- SHA
- 7308f569
Try a prompt
Model card
From the Hugging Face model README
English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.
| Feature | Description |
|---|---|
| Name | en_docusco_spacy_cd_trf |
| Version | 1.3 |
| spaCy | >=3.7.4,<3.8.0 |
| Default Pipeline | transformer, tagger, ner |
| Components | transformer, tagger, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | MIT |
| Author | David Brown |
Label Scheme
<details> <summary>View label scheme (289 labels for 2 components)</summary>| Component | Labels |
|---|---|
tagger | APPGE, AT, AT1, BCL21, BCL22, CC, CCB, CS, CS21, CS22, CS31, CS32, CS33, CS41, CS42, CS43, CS44, CSA, CSN, CST, CSW, CSW31, CSW32, CSW33, DA, DA1, DA2, DAR, DAT, DB, DB2, DD, DD1, DD2, DDQ, DDQGE, DDQGE31, DDQGE32, DDQGE33, DDQV, DDQV31, DDQV32, DDQV33, EX, FO, FU, FW, GE, IF, II, II21, II22, II31, II32, II33, II41, II42, II43, II44, IO, IW, JJ, JJ21, JJ22, JJ31, JJ32, JJ33, JJ41, JJ42, JJ43, JJ44, JJR, JJT, JK, MC, MC1, MC2, MC221, MC222, MCMC, MD, MF, ND1, NN, NN1, NN121, NN122, NN131, NN132, NN133, NN141, NN142, NN143, NN144, NN2, NN21, NN22, NN221, NN222, NN31, NN32, NN33, NNA, NNB, NNL1, NNL2, NNO, NNO2, NNT1, NNT131, NNT132, NNT133, NNT2, NNU, NNU1, NNU2, NNU21, NNU22, NNU221, NNU222, NP, NP1, NP2, NPD1, NPD2, NPM1, NPM2, PN, PN1, PN121, PN122, PN21, PN22, PNQO, PNQS, PNQS31, PNQS32, PNQS33, PNQV, PNQV31, PNQV32, PNQV33, PNX1, PPGE, PPH1, PPHO1, PPHO2, PPHS1, PPHS2, PPIO1, PPIO2, PPIS1, PPIS2, PPX1, PPX121, PPX122, PPX2, PPX221, PPX222, PPY, RA, RA21, RA22, REX, REX21, REX22, REX41, REX42, REX43, REX44, RG, RG21, RG22, RG41, RG42, RG43, RG44, RGQ, RGQV, RGQV31, RGQV32, RGQV33, RGR, RGT, RL, RL21, RL22, RL31, RL32, RL33, RP, RPK, RR, RR21, RR22, RR31, RR32, RR33, RR41, RR42, RR43, RR44, RR51, RR52, RR53, RR54, RR55, RRQ, RRQV, RRQV31, RRQV32, RRQV33, RRR, RRT, RT, RT21, RT22, RT31, RT32, RT33, RT41, RT42, RT43, RT44, TO, UH, UH21, UH22, UH31, UH32, UH33, VB0, VBDR, VBDZ, VBG, VBI, VBM, VBN, VBR, VBZ, VD0, VDD, VDG, VDI, VDN, VDZ, VH0, VHD, VHG, VHI, VHN, VHZ, VM, VM21, VM22, VMK, VV0, VVD, VVG, VVGK, VVI, VVN, VVNK, VVZ, XX, Y, ZZ1, ZZ2, ZZ221, ZZ222 |
ner | ActorsAbstractions, ActorsFirstPerson, ActorsPeople, ActorsPublicEntities, CitationAuthority, CitationControversy, CitationNeutral, ConfidenceHedged, ConfidenceHigh, OrganizationNarrative, OrganizationReasoning, PlanningFuture, PlanningStrategy, SentimentNegative, SentimentPositive, SignpostingAcademicWritingMoves, SignpostingMetadiscourse, StanceEmphatic, StanceModerated |
Accuracy
| Type | Score |
|---|---|
TAG_ACC | 98.60 |
ENTS_F | 89.86 |
ENTS_P | 89.76 |
ENTS_R | 89.96 |
TRANSFORMER_LOSS | 4671131.21 |
TAGGER_LOSS | 1405830.04 |
NER_LOSS | 4168254.47 |
- Task
- Token Classification
- Library
- spacy
- License
- mit
- Languages
- en
- Created
- Dec 11, 2022
- Updated
- May 24, 2024