Update tags in README

README.md

@@ -1,95 +1,7 @@
 ---
 tags:
 - spacy
-- token-classification
+- text-classification
 language:
 - en
 license: mit
-model-index:
-- name: en_statistics
-  results:
-  - task:
-      name: NER
-      type: text-classification
-    metrics:
-    - name: NER Precision
-      type: precision
-      value: 0.853733758
-    - name: NER Recall
-      type: recall
-      value: 0.8456530449
-    - name: NER F Score
-      type: f_score
-      value: 0.8496741892
-  - task:
-      name: TAG
-      type: token-classification
-    metrics:
-    - name: TAG (XPOS) Accuracy
-      type: accuracy
-      value: 0.9727831973
-  - task:
-      name: UNLABELED_DEPENDENCIES
-      type: token-classification
-    metrics:
-    - name: Unlabeled Attachment Score (UAS)
-      type: f_score
-      value: 0.9186878782
-  - task:
-      name: LABELED_DEPENDENCIES
-      type: token-classification
-    metrics:
-    - name: Labeled Attachment Score (LAS)
-      type: f_score
-      value: 0.9005160534
-  - task:
-      name: SENTS
-      type: token-classification
-    metrics:
-    - name: Sentences F-Score
-      type: f_score
-      value: 0.8923519379
----
-English pipeline that provides statistics, readability and formality scores.
-
-| Feature | Description |
-| --- | --- |
-| **Name** | `en_statistics` |
-| **Version** | `0.0.1` |
-| **spaCy** | `>=3.1.1,<3.2.0` |
-| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner`, `syllables`, `formality`, `readability` |
-| **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner`, `syllables`, `formality`, `readability` |
-| **Vectors** | 684830 keys, 20000 unique vectors (300 dimensions) |
-| **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br />[ClearNLP Constituent-to-Dependency Conversion](https://github.com/clir/clearnlp-guidelines/blob/master/md/components/dependency_conversion.md) (Emory University)<br />[WordNet 3.0](https://wordnet.princeton.edu/) (Princeton University)<br />[GloVe Common Crawl](https://nlp.stanford.edu/projects/glove/) (Jeffrey Pennington, Richard Socher, and Christopher D. Manning) |
-| **License** | `MIT` |
-| **Author** | [Contentologie]() |
-
-### Label Scheme
-
-<details>
-
-<summary>View label scheme (114 labels for 4 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`, `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` |
-| **`senter`** | `I`, `S` |
-| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
-
-</details>
-
-### Accuracy
-
-| Type | Score |
-| --- | --- |
-| `TOKEN_ACC` | 99.93 |
-| `TAG_ACC` | 97.28 |
-| `DEP_UAS` | 91.87 |
-| `DEP_LAS` | 90.05 |
-| `ENTS_P` | 85.37 |
-| `ENTS_R` | 84.57 |
-| `ENTS_F` | 84.97 |
-| `SENTS_P` | 90.49 |
-| `SENTS_R` | 88.01 |
-| `SENTS_F` | 89.24 |