| --- |
| tags: |
| - spacy |
| - token-classification |
| - text-classification |
| language: |
| - en |
| model-index: |
| - name: en_tako_query_analyzer |
| results: |
| - task: |
| name: NER |
| type: token-classification |
| metrics: |
| - name: NER Precision |
| type: precision |
| value: 0.0 |
| - name: NER Recall |
| type: recall |
| value: 0.0 |
| - name: NER F Score |
| type: f_score |
| value: 0.0 |
| --- |
| | Feature | Description | |
| | --- | --- | |
| | **Name** | `en_tako_query_analyzer` | |
| | **Version** | `0.0.5` | |
| | **spaCy** | `>=3.8.11,<3.9.0` | |
| | **Default Pipeline** | `tok2vec_small`, `tagger`, `parser`, `attribute_ruler`, `senter`, `tok2vec`, `ner`, `textcat_multilabel`, `textcat_classify` | |
| | **Components** | `tok2vec_small`, `tagger`, `parser`, `attribute_ruler`, `senter`, `tok2vec`, `ner`, `textcat_multilabel`, `textcat_classify` | |
| | **Vectors** | 684830 keys, 342918 unique vectors (300 dimensions) | |
| | **Sources** | n/a | |
| | **License** | n/a | |
| | **Author** | [n/a]() | |
|
|
| ### Label Scheme |
|
|
| <details> |
|
|
| <summary>View label scheme (124 labels for 5 components)</summary> |
|
|
| | Component | Labels | |
| | --- | --- | |
| | **`tagger`** | `$`, `''`, `,`, `-LRB-`, `-RRB-`, `.`, `:`, `ADD`, `AFX`, `CC`, `CD`, `DT`, `EX`, `FW`, `HYPH`, `IN`, `JJ`, `JJR`, `JJS`, `LS`, `MD`, `NFP`, `NN`, `NNP`, `NNPS`, `NNS`, `PDT`, `POS`, `PRP`, `PRP$`, `RB`, `RBR`, `RBS`, `RP`, `SYM`, `TO`, `UH`, `VB`, `VBD`, `VBG`, `VBN`, `VBP`, `VBZ`, `WDT`, `WP`, `WP$`, `WRB`, `XX`, `_SP`, ```` | |
| | **`parser`** | `ROOT`, `acl`, `acomp`, `advcl`, `advmod`, `agent`, `amod`, `appos`, `attr`, `aux`, `auxpass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `csubj`, `csubjpass`, `dative`, `dep`, `det`, `dobj`, `expl`, `intj`, `mark`, `meta`, `neg`, `nmod`, `npadvmod`, `nsubj`, `nsubjpass`, `nummod`, `oprd`, `parataxis`, `pcomp`, `pobj`, `poss`, `preconj`, `predet`, `prep`, `prt`, `punct`, `quantmod`, `relcl`, `xcomp` | |
| | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `STOCK_TICKER`, `TIME`, `WORK_OF_ART` | |
| | **`textcat_multilabel`** | `Finance`, `Economics`, `Demographics`, `Health`, `Politics`, `Sports`, `Climate`, `Other` | |
| | **`textcat_classify`** | `ACCEPT`, `REJECT` | |
| |
| </details> |
| |
| ### Accuracy |
| |
| | Type | Score | |
| | --- | --- | |
| | `ENTS_F` | 0.00 | |
| | `ENTS_P` | 0.00 | |
| | `ENTS_R` | 0.00 | |
| | `ENTS_PER_TYPE` | 0.00 | |
| | `CATS_SCORE` | 84.62 | |
| | `CATS_MICRO_P` | 83.50 | |
| | `CATS_MICRO_R` | 83.50 | |
| | `CATS_MICRO_F` | 83.50 | |
| | `CATS_MACRO_P` | 84.23 | |
| | `CATS_MACRO_R` | 83.50 | |
| | `CATS_MACRO_F` | 83.41 | |
| | `CATS_MACRO_AUC` | 83.96 | |
| | `TEXTCAT_CLASSIFY_LOSS` | 1108.70 | |
