| --- |
| tags: |
| - spacy |
| - token-classification |
| language: |
| - en |
| license: cc-by-sa-3.0 |
| model-index: |
| - name: en_core_sci_scibert |
| results: |
| - task: |
| name: NER |
| type: token-classification |
| metrics: |
| - name: NER Precision |
| type: precision |
| value: 0.6847362143 |
| - name: NER Recall |
| type: recall |
| value: 0.6724342328 |
| - name: NER F Score |
| type: f_score |
| value: 0.6785294683 |
| - task: |
| name: TAG |
| type: token-classification |
| metrics: |
| - name: TAG (XPOS) Accuracy |
| type: accuracy |
| value: 0.0 |
| - task: |
| name: LEMMA |
| type: token-classification |
| metrics: |
| - name: Lemma Accuracy |
| type: accuracy |
| value: 0.0 |
| - task: |
| name: UNLABELED_DEPENDENCIES |
| type: token-classification |
| metrics: |
| - name: Unlabeled Attachment Score (UAS) |
| type: f_score |
| value: 0.0 |
| - task: |
| name: LABELED_DEPENDENCIES |
| type: token-classification |
| metrics: |
| - name: Labeled Attachment Score (LAS) |
| type: f_score |
| value: 0.0 |
| - task: |
| name: SENTS |
| type: token-classification |
| metrics: |
| - name: Sentences F-Score |
| type: f_score |
| value: 0.0 |
| --- |
| Spacy Models for Biomedical Text. |
|
|
| | Feature | Description | |
| | --- | --- | |
| | **Name** | `en_core_sci_scibert` | |
| | **Version** | `0.5.3` | |
| | **spaCy** | `>=3.6.1,<3.7.0` | |
| | **Default Pipeline** | `transformer`, `tagger`, `attribute_ruler`, `lemmatizer`, `parser`, `ner` | |
| | **Components** | `transformer`, `tagger`, `attribute_ruler`, `lemmatizer`, `parser`, `ner` | |
| | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
| | **Sources** | OntoNotes 5<br>Common Crawl<br>GENIA 1.0 | |
| | **License** | `CC BY-SA 3.0` | |
| | **Author** | [Allen Institute for Artificial Intelligence](https://allenai.github.io/SciSpaCy/) | |
|
|
| ### Label Scheme |
|
|
| <details> |
|
|
| <summary>View label scheme (98 labels for 3 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`, ```` | |
| | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `acomp`, `advcl`, `advmod`, `amod`, `amod@nmod`, `appos`, `attr`, `aux`, `auxpass`, `case`, `cc`, `cc:preconj`, `ccomp`, `compound`, `compound:prt`, `conj`, `cop`, `csubj`, `dative`, `dep`, `det`, `det:predet`, `dobj`, `expl`, `intj`, `mark`, `meta`, `mwe`, `neg`, `nmod`, `nmod:npmod`, `nmod:poss`, `nmod:tmod`, `nsubj`, `nsubjpass`, `nummod`, `parataxis`, `pcomp`, `pobj`, `preconj`, `predet`, `prep`, `punct`, `quantmod`, `xcomp` | |
| | **`ner`** | `ENTITY` | |
| |
| </details> |
| |
| ### Accuracy |
| |
| | Type | Score | |
| | --- | --- | |
| | `TAG_ACC` | 0.00 | |
| | `LEMMA_ACC` | 0.00 | |
| | `DEP_UAS` | 0.00 | |
| | `DEP_LAS` | 0.00 | |
| | `DEP_LAS_PER_TYPE` | 0.00 | |
| | `SENTS_P` | 0.00 | |
| | `SENTS_R` | 0.00 | |
| | `SENTS_F` | 0.00 | |
| | `ENTS_F` | 67.85 | |
| | `ENTS_P` | 68.47 | |
| | `ENTS_R` | 67.24 | |
| | `NER_LOSS` | 18589304.55 | |
