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nestauk
/
en_skillner

Token Classification
spaCy
English
Eval Results
Model card Files Community
ihk commited on
Commit
cb74416
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1 Parent(s): 13ee2e1

Update spaCy pipeline

Browse files
Files changed (5) hide show
  1. README.md +7 -7
  2. en_skillner-any-py3-none-any.whl +2 -2
  3. meta.json +34 -148
  4. ner/model +1 -1
  5. vocab/strings.json +0 -0
README.md CHANGED
@@ -14,13 +14,13 @@ model-index:
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  metrics:
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  - name: NER Precision
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  type: precision
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- value: 0.0
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  - name: NER Recall
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  type: recall
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- value: 0.0
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  - name: NER F Score
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  type: f_score
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- value: 0
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  ---
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  A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.
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@@ -34,7 +34,7 @@ A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT
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  | **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
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  | **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>[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) |
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  | **License** | `MIT` |
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- | **Author** | [Explosion](https://explosion.ai) |
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  ### Label Scheme
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@@ -52,6 +52,6 @@ A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT
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  | Type | Score |
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  | --- | --- |
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- | `ENTS_P` | 0.00 |
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- | `ENTS_R` | 0.00 |
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- | `ENTS_F` | 0.00 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
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+ value: 0.4605714286
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.4574347333
21
  - name: NER F Score
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  type: f_score
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+ value: 0.4589977221
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  ---
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  A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.
26
 
 
34
  | **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
35
  | **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>[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) |
36
  | **License** | `MIT` |
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+ | **Author** | [nestauk](https://explosion.ai) |
38
 
39
  ### Label Scheme
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52
 
53
  | Type | Score |
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  | --- | --- |
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+ | `ENTS_P` | 46.06 |
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+ | `ENTS_R` | 45.74 |
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+ | `ENTS_F` | 45.90 |
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  "name":"skillner",
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