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---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_engagement_LSTM
  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
  - 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: 0.9144831558
---
---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_engagement_LSTM
  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
  - 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: 0.9144831558
---
| Feature              | Description                                                                                                   |
| -------------------- | ------------------------------------------------------------------------------------------------------------- |
| **Name**             | `en_engagement_LSTM`                                                                                          |
| **Version**          | `1.1.7`                                                                                                       |
| **spaCy**            | `>=3.4.4,<4`                                                                                                  |
| **Default Pipeline** | `transformer`, `parser`, `tagger`, `ner`, `attribute_ruler`, `lemmatizer`, `trainable_transformer`, `spancat` |
| **Components**       | `transformer`, `parser`, `tagger`, `ner`, `attribute_ruler`, `lemmatizer`, `trainable_transformer`, `spancat` |
| **Vectors**          | 0 keys, 0 unique vectors (0 dimensions)                                                                       |
| **Sources**          | n/a                                                                                                           |
| **License**          | n/a                                                                                                           |
| **Author**           | [n/a]()                                                                                                       |

### Label Scheme

<details>

<summary>View label scheme (122 labels for 4 components)</summary>

| Component     | Labels                                                                                                                                                                                                                                                                                                                                                                                                             |
| ------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **`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` |
| **`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`, ````                                                                                  |
| **`ner`**     | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART`                                                                                                                                                                                                                                          |
| **`spancat`** | `ATTRIBUTION`, `ENTERTAIN`, `PROCLAIM`, `SOURCES`, `MONOGLOSS`, `CITATION`, `ENDOPHORIC`, `DENY`, `JUSTIFYING`, `COUNTER`                                                                                                                                                                                                                                                                                          |

</details>

### Accuracy

| Type                         | Score     |
| ---------------------------- | --------- |
| `DEP_UAS`                    | 0.00      |
| `DEP_LAS`                    | 0.00      |
| `DEP_LAS_PER_TYPE`           | 0.00      |
| `SENTS_P`                    | 89.82     |
| `SENTS_R`                    | 93.14     |
| `SENTS_F`                    | 91.45     |
| `TAG_ACC`                    | 0.00      |
| `ENTS_F`                     | 0.00      |
| `ENTS_P`                     | 0.00      |
| `ENTS_R`                     | 0.00      |
| `LEMMA_ACC`                  | 0.00      |
| `SPANS_SC_F`                 | 77.22     |
| `SPANS_SC_P`                 | 79.33     |
| `SPANS_SC_R`                 | 75.22     |
| `TRAINABLE_TRANSFORMER_LOSS` | 885.71    |
| `SPANCAT_LOSS`               | 104829.66 |