| --- |
| tags: |
| - spacy |
| - token-classification |
| language: |
| - en |
| model-index: |
| - name: en_acnl_electra_pipeline |
| results: |
| - task: |
| name: POS |
| type: token-classification |
| metrics: |
| - name: POS Accuracy |
| type: accuracy |
| value: 0.9769257272 |
| - task: |
| name: SENTER |
| type: token-classification |
| metrics: |
| - name: SENTER Precision |
| type: precision |
| value: 0.9508884151 |
| - name: SENTER Recall |
| type: recall |
| value: 0.94805839 |
| - name: SENTER F Score |
| type: f_score |
| value: 0.9494712937 |
| - task: |
| name: UNLABELED_DEPENDENCIES |
| type: token-classification |
| metrics: |
| - name: Unlabeled Dependencies Accuracy |
| type: accuracy |
| value: 0.9577103137 |
| - task: |
| name: LABELED_DEPENDENCIES |
| type: token-classification |
| metrics: |
| - name: Labeled Dependencies Accuracy |
| type: accuracy |
| value: 0.9577103137 |
| --- |
| | Feature | Description | |
| | --- | --- | |
| | **Name** | `en_acnl_electra_pipeline` | |
| | **Version** | `0.0.1` | |
| | **spaCy** | `>=3.1.3,<3.2.0` | |
| | **Default Pipeline** | `transformer`, `tagger`, `parser` | |
| | **Components** | `transformer`, `tagger`, `parser` | |
| | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
| | **Sources** | n/a | |
| | **License** | GPL | |
| | **Author** | Daniel Vasić() | |
|
|
| ### Label Scheme |
|
|
| <details> |
|
|
| <summary>View label scheme (87 labels for 2 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`, `VERB`, `WDT`, `WP`, `WP$`, `WRB`, `XX`, ```` | |
| | **`parser`** | `ROOT`, `acl`, `acomp`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `auxpass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `dative`, `dep`, `det`, `dobj`, `intj`, `mark`, `meta`, `neg`, `nmod`, `npadvmod`, `nummod`, `parataxis`, `pcomp`, `pobj`, `poss`, `preconj`, `predet`, `prep`, `prt`, `punct`, `quantmod`, `relcl`, `xcomp` | |
| |
| </details> |
| |
| ### Accuracy |
| |
| | Type | Score | |
| | --- | --- | |
| | `TAG_ACC` | 97.69 | |
| | `DEP_UAS` | 95.77 | |
| | `DEP_LAS` | 94.52 | |
| | `SENTS_P` | 95.09 | |
| | `SENTS_R` | 94.81 | |
| | `SENTS_F` | 94.95 | |
| | `TRANSFORMER_LOSS` | 6123357.72 | |
| | `TAGGER_LOSS` | 338995.26 | |
| | `PARSER_LOSS` | 4101825.66 | |
