Update spaCy pipeline

README.md

@@ -14,25 +14,25 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.4605714286
+      value: 0.5991309071
     - name: NER Recall
       type: recall
-      value: 0.4574347333
+      value: 0.5768828452
     - name: NER F Score
       type: f_score
-      value: 0.4589977221
+      value: 0.5877964295
 ---
 A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `en_skillner` |
-| **Version** | `3.7.1` |
-| **spaCy** | `>=3.7.4,<3.8.0` |
+| **Version** | `3.5.0` |
+| **spaCy** | `>=3.5.3,<3.6.0` |
 | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 514157 keys, 514157 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>[Explosion Vectors (OSCAR 2109 + Wikipedia + OpenSubtitles + WMT News Crawl)](https://github.com/explosion/spacy-vectors-builder) (Explosion) |
+| **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) |
 | **License** | `MIT` |
 | **Author** | [nestauk](https://explosion.ai) |
 
@@ -52,6 +52,6 @@ A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT
 
 | Type | Score |
 | --- | --- |
-| `ENTS_P` | 46.06 |
-| `ENTS_R` | 45.74 |
-| `ENTS_F` | 45.90 |
+| `ENTS_P` | 59.91 |
+| `ENTS_R` | 57.69 |
+| `ENTS_F` | 58.78 |

config.cfg

@@ -17,7 +17,6 @@ after_creation = null
 after_pipeline_creation = null
 batch_size = 256
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
-vectors = {"@vectors":"spacy.Vectors.v1"}
 
 [components]
 
@@ -117,7 +116,6 @@ maxout_pieces = 2
 
 [components.tagger]
 factory = "tagger"
-label_smoothing = 0.0
 neg_prefix = "!"
 overwrite = false
 scorer = {"@scorers":"spacy.tagger_scorer.v1"}

en_skillner-any-py3-none-any.whl

@@ -1,3 +1,3 @@
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meta.json

@@ -1,14 +1,14 @@
 {
   "lang":"en",
   "name":"skillner",
-  "version":"3.7.1",
+  "version":"3.5.0",
   "description":"A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.",
   "author":"nestauk",
   "email":"contact@explosion.ai",
   "url":"https://explosion.ai",
   "license":"MIT",
-  "spacy_version":">=3.7.4,<3.8.0",
-  "spacy_git_version":"bd2c17e20",
+  "spacy_version":">=3.5.3,<3.6.0",
+  "spacy_git_version":"9e0322de1",
   "vectors":{
     "width":300,
     "vectors":514157,
@@ -43,45 +43,45 @@
     "senter"
   ],
   "performance":{
-    "ents_p":0.4605714286,
-    "ents_r":0.4574347333,
-    "ents_f":0.4589977221,
+    "ents_p":0.5991309071,
+    "ents_r":0.5768828452,
+    "ents_f":0.5877964295,
     "ents_per_type":{
       "SKILL":{
-        "correct":461,
-        "incorrect":8,
+        "correct":1208,
+        "incorrect":32,
         "partial":0,
-        "missed":304,
-        "spurious":340,
-        "possible":773,
-        "actual":809,
-        "precision":0.5698393078,
-        "recall":0.596377749,
-        "f1":0.582806574
+        "missed":429,
+        "spurious":420,
+        "possible":1669,
+        "actual":1660,
+        "precision":0.7277108434,
+        "recall":0.7237866986,
+        "f1":0.7257434665
       },
       "EXPERIENCE":{
-        "correct":33,
-        "incorrect":16,
+        "correct":84,
+        "incorrect":37,
         "partial":0,
-        "missed":59,
-        "spurious":17,
-        "possible":108,
-        "actual":66,
-        "precision":0.5,
-        "recall":0.3055555556,
-        "f1":0.3793103448
+        "missed":55,
+        "spurious":29,
+        "possible":176,
+        "actual":150,
+        "precision":0.56,
+        "recall":0.4772727273,
+        "f1":0.5153374233
       },
       "BENEFIT":{
-        "correct":0,
-        "incorrect":0,
+        "correct":24,
+        "incorrect":3,
         "partial":0,
-        "missed":0,
-        "spurious":0,
-        "possible":0,
-        "actual":0,
-        "precision":0,
-        "recall":0,
-        "f1":0
+        "missed":40,
+        "spurious":4,
+        "possible":67,
+        "actual":31,
+        "precision":0.7741935484,
+        "recall":0.3582089552,
+        "f1":0.4897959184
       }
     }
   },

ner/model

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ner/moves

@@ -1 +1 @@
-��moves�|{"0":{},"1":{"ORG":56516,"DATE":40493,"PERSON":36534,"GPE":26745,"MONEY":15158,"CARDINAL":14109,"NORP":9641,"PERCENT":9199,"WORK_OF_ART":4488,"LOC":4055,"TIME":3678,"QUANTITY":3123,"FAC":3046,"EVENT":3021,"ORDINAL":2142,"PRODUCT":1787,"LAW":1624,"LANGUAGE":355,"SKILL":-1,"EXPERIENCE":-2},"2":{"ORG":56516,"DATE":40493,"PERSON":36534,"GPE":26745,"MONEY":15158,"CARDINAL":14109,"NORP":9641,"PERCENT":9199,"WORK_OF_ART":4488,"LOC":4055,"TIME":3678,"QUANTITY":3123,"FAC":3046,"EVENT":3021,"ORDINAL":2142,"PRODUCT":1787,"LAW":1624,"LANGUAGE":355,"SKILL":-1,"EXPERIENCE":-2},"3":{"ORG":56516,"DATE":40493,"PERSON":36534,"GPE":26745,"MONEY":15158,"CARDINAL":14109,"NORP":9641,"PERCENT":9199,"WORK_OF_ART":4488,"LOC":4055,"TIME":3678,"QUANTITY":3123,"FAC":3046,"EVENT":3021,"ORDINAL":2142,"PRODUCT":1787,"LAW":1624,"LANGUAGE":355,"SKILL":-1,"EXPERIENCE":-2},"4":{"ORG":56516,"DATE":40493,"PERSON":36534,"GPE":26745,"MONEY":15158,"CARDINAL":14109,"NORP":9641,"PERCENT":9199,"WORK_OF_ART":4488,"LOC":4055,"TIME":3678,"QUANTITY":3123,"FAC":3046,"EVENT":3021,"ORDINAL":2142,"PRODUCT":1787,"LAW":1624,"LANGUAGE":355,"":1,"SKILL":-1,"EXPERIENCE":-2},"5":{"":1}}�cfg��neg_key�
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tagger/cfg

@@ -1,5 +1,4 @@
 {
-  "label_smoothing":0.0,
   "labels":[
     "$",
     "''",

vocab/lookups.bin

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