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ja_core_news_trf
spacy/ja_core_news_trf
ja_core_news_trf is a token classification model from spacy. Use it when you need labels on individual words, such as names. It is set up for spacy. The card lists the license as cc-by-sa-3.0.
Japanese transformer pipeline (Transformer(name='cl-tohoku/bert-base-japanese-char-v2', pieceencoder='char', stride=160, type='bert', width=768, window=216, vocabsize=6144)). Components: transformer, morphologizer, pa…
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At a glance
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2023
- SHA
- 360106f6
Model card
From the Hugging Face model README
Details: https://spacy.io/models/ja#ja_core_news_trf
Japanese transformer pipeline (Transformer(name='cl-tohoku/bert-base-japanese-char-v2', piece_encoder='char', stride=160, type='bert', width=768, window=216, vocab_size=6144)). Components: transformer, morphologizer, parser, ner.
| Feature | Description |
|---|---|
| Name | ja_core_news_trf |
| Version | 3.7.2 |
| spaCy | >=3.7.0,<3.8.0 |
| Default Pipeline | transformer, morphologizer, parser, attribute_ruler, ner |
| Components | transformer, morphologizer, parser, attribute_ruler, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | UD Japanese GSD v2.8 (Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel)<br />UD Japanese GSD v2.8 NER (Megagon Labs Tokyo)<br />cl-tohoku/bert-base-japanese-char-v2 (Inui Laboratory, Tohoku University) |
| License | CC BY-SA 3.0 |
| Author | Explosion |
Label Scheme
<details> <summary>View label scheme (64 labels for 3 components)</summary>| Component | Labels |
|---|---|
morphologizer | POS=NOUN, POS=ADP, POS=VERB, POS=SCONJ, POS=AUX, POS=PUNCT, POS=PART, POS=DET, POS=NUM, POS=ADV, POS=PRON, POS=ADJ, POS=PROPN, POS=CCONJ, POS=SYM, POS=NOUN|Polarity=Neg, POS=AUX|Polarity=Neg, POS=INTJ, POS=SCONJ|Polarity=Neg |
parser | ROOT, acl, advcl, advmod, amod, aux, case, cc, ccomp, compound, cop, csubj, dep, det, dislocated, fixed, mark, nmod, nsubj, nummod, obj, obl, punct |
ner | CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, MOVEMENT, NORP, ORDINAL, ORG, PERCENT, PERSON, PET_NAME, PHONE, PRODUCT, QUANTITY, TIME, TITLE_AFFIX, WORK_OF_ART |
Accuracy
| Type | Score |
|---|---|
TOKEN_ACC | 99.37 |
TOKEN_P | 97.64 |
TOKEN_R | 97.88 |
TOKEN_F | 97.76 |
POS_ACC | 97.94 |
MORPH_ACC | 0.00 |
MORPH_MICRO_P | 34.01 |
MORPH_MICRO_R | 98.04 |
MORPH_MICRO_F | 50.51 |
SENTS_P | 93.18 |
SENTS_R | 97.04 |
SENTS_F | 95.07 |
DEP_UAS | 93.05 |
DEP_LAS | 91.78 |
TAG_ACC | 97.13 |
LEMMA_ACC | 96.70 |
ENTS_P | 82.27 |
ENTS_R | 84.65 |
ENTS_F | 83.45 |
- Task
- Token Classification
- Library
- spacy
- License
- cc-by-sa-3.0
- Languages
- ja
- Created
- Mar 2, 2022
- Updated
- Oct 10, 2023