ihk commited on
Commit
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1 Parent(s): 676eb9b

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ en_skillner-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ ner/model filter=lfs diff=lfs merge=lfs -text
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+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
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+ vocab/key2row filter=lfs diff=lfs merge=lfs -text
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+ vocab/vectors filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,57 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - spacy
4
+ - token-classification
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+ language:
6
+ - en
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+ license: mit
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+ model-index:
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+ - name: en_skillner
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+ results:
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+ - task:
12
+ name: NER
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+ type: token-classification
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+ metrics:
15
+ - name: NER Precision
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+ type: precision
17
+ value: 0.0
18
+ - name: NER Recall
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+ type: recall
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+ value: 0.0
21
+ - 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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+
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_skillner` |
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+ | **Version** | `3.7.1` |
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+ | **spaCy** | `>=3.7.4,<3.8.0` |
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+ | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
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+ | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
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+ | **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) |
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+ | **License** | `MIT` |
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+ | **Author** | [Explosion](https://explosion.ai) |
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+
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+ ### Label Scheme
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+
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+ <details>
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+
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+ <summary>View label scheme (3 labels for 1 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`ner`** | `SKILL`, `EXPERIENCE`, `BENEFIT` |
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+
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+ </details>
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+
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+ ### Accuracy
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+
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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 |
attribute_ruler/patterns ADDED
Binary file (14.7 kB). View file
 
config.cfg ADDED
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1
+ [paths]
2
+ train = null
3
+ dev = null
4
+ vectors = null
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+ init_tok2vec = null
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+
7
+ [system]
8
+ gpu_allocator = null
9
+ seed = 0
10
+
11
+ [nlp]
12
+ lang = "en"
13
+ pipeline = ["tok2vec","tagger","parser","senter","attribute_ruler","lemmatizer","ner"]
14
+ disabled = ["senter"]
15
+ before_creation = null
16
+ after_creation = null
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+ after_pipeline_creation = null
18
+ batch_size = 256
19
+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
20
+ vectors = {"@vectors":"spacy.Vectors.v1"}
21
+
22
+ [components]
23
+
24
+ [components.attribute_ruler]
25
+ factory = "attribute_ruler"
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+ scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
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+ validate = false
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+
29
+ [components.lemmatizer]
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+ factory = "lemmatizer"
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+ mode = "rule"
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+ model = null
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+ overwrite = false
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+ scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
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+
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+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
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+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
41
+ update_with_oracle_cut_size = 100
42
+
43
+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
45
+ state_type = "ner"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = true
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy.Tok2Vec.v2"
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+
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+ [components.ner.model.tok2vec.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = 96
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+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
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+ rows = [5000,1000,2500,2500]
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+ include_static_vectors = true
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+
62
+ [components.ner.model.tok2vec.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = 96
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+ depth = 4
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+ window_size = 1
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+ maxout_pieces = 3
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+
69
+ [components.parser]
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+ factory = "parser"
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+ learn_tokens = false
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+ min_action_freq = 30
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+ moves = null
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+ scorer = {"@scorers":"spacy.parser_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.parser.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ state_type = "parser"
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+ extra_state_tokens = false
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+ hidden_width = 64
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+ maxout_pieces = 2
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+ use_upper = true
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+ nO = null
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+
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+ [components.parser.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
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+ width = ${components.tok2vec.model.encode:width}
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+ upstream = "tok2vec"
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+
91
+ [components.senter]
92
+ factory = "senter"
93
+ overwrite = false
94
+ scorer = {"@scorers":"spacy.senter_scorer.v1"}
95
+
96
+ [components.senter.model]
97
+ @architectures = "spacy.Tagger.v2"
98
+ nO = null
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+ normalize = false
100
+
101
+ [components.senter.model.tok2vec]
102
+ @architectures = "spacy.Tok2Vec.v2"
103
+
104
+ [components.senter.model.tok2vec.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = 16
107
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
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+ rows = [1000,500,500,500,50]
109
+ include_static_vectors = true
110
+
111
+ [components.senter.model.tok2vec.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = 16
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+ depth = 2
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+ window_size = 1
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+ maxout_pieces = 2
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+
118
+ [components.tagger]
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+ factory = "tagger"
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+ label_smoothing = 0.0
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+ neg_prefix = "!"
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+ overwrite = false
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+ scorer = {"@scorers":"spacy.tagger_scorer.v1"}
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+
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+ [components.tagger.model]
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+ @architectures = "spacy.Tagger.v2"
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+ nO = null
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+ normalize = false
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+
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+ [components.tagger.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
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+ width = ${components.tok2vec.model.encode:width}
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+ upstream = "tok2vec"
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+
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+ [components.tok2vec]
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+ factory = "tok2vec"
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+
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+ [components.tok2vec.model]
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+ @architectures = "spacy.Tok2Vec.v2"
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+
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+ [components.tok2vec.model.embed]
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+ @architectures = "spacy.MultiHashEmbed.v2"
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+ width = ${components.tok2vec.model.encode:width}
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+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
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+ rows = [5000,1000,2500,2500,50,50]
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+ include_static_vectors = true
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+
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+ [components.tok2vec.model.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
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+ width = 96
151
+ depth = 4
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+ window_size = 1
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+ maxout_pieces = 3
154
+
155
+ [corpora]
156
+
157
+ [corpora.dev]
158
+ @readers = "spacy.Corpus.v1"
159
+ path = ${paths.dev}
160
+ gold_preproc = false
161
+ max_length = 0
162
+ limit = 0
163
+ augmenter = null
164
+
165
+ [corpora.train]
166
+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
168
+ gold_preproc = false
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+ max_length = 0
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+ limit = 0
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+ augmenter = null
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+
173
+ [training]
174
+ train_corpus = "corpora.train"
175
+ dev_corpus = "corpora.dev"
176
+ seed = ${system:seed}
177
+ gpu_allocator = ${system:gpu_allocator}
178
+ dropout = 0.1
179
+ accumulate_gradient = 1
180
+ patience = 5000
181
+ max_epochs = 0
182
+ max_steps = 100000
183
+ eval_frequency = 1000
184
+ frozen_components = []
185
+ before_to_disk = null
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+ annotating_components = []
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+ before_update = null
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+
189
+ [training.batcher]
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+ @batchers = "spacy.batch_by_words.v1"
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+ discard_oversize = false
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+ tolerance = 0.2
193
+ get_length = null
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+
195
+ [training.batcher.size]
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+ @schedules = "compounding.v1"
197
+ start = 100
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+ stop = 1000
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+ compound = 1.001
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+ t = 0.0
201
+
202
+ [training.logger]
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+ @loggers = "spacy.ConsoleLogger.v1"
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+ progress_bar = false
205
+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
208
+ beta1 = 0.9
209
+ beta2 = 0.999
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+ L2_is_weight_decay = true
211
+ L2 = 0.01
212
+ grad_clip = 1.0
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+ use_averages = true
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+ eps = 0.00000001
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+ learn_rate = 0.001
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+
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+ [training.score_weights]
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+ tag_acc = 0.16
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+ dep_uas = 0.0
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+ dep_las = 0.16
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+ dep_las_per_type = null
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+ sents_p = null
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+ sents_r = null
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+ sents_f = 0.02
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+ lemma_acc = 0.5
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+ ents_f = 0.16
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+ ents_p = 0.0
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+ ents_r = 0.0
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+ ents_per_type = null
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+ speed = 0.0
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+
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+ [pretraining]
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+
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+ [initialize]
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+ vocab_data = null
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+ vectors = ${paths.vectors}
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+ init_tok2vec = ${paths.init_tok2vec}
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+ before_init = null
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+ after_init = null
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+
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+ [initialize.components]
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+
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+ [initialize.components.ner]
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+
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+ [initialize.components.ner.labels]
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+ @readers = "spacy.read_labels.v1"
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+ path = "corpus/labels/ner.json"
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+ require = false
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+
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+ [initialize.components.parser]
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+
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+ [initialize.components.parser.labels]
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+ @readers = "spacy.read_labels.v1"
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+ path = "corpus/labels/parser.json"
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+ require = false
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+
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+ [initialize.components.tagger]
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+
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+ [initialize.components.tagger.labels]
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+ @readers = "spacy.read_labels.v1"
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+ path = "corpus/labels/tagger.json"
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+ require = false
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+
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+ [initialize.lookups]
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+ @misc = "spacy.LookupsDataLoader.v1"
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+ lang = ${nlp.lang}
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+ tables = ["lexeme_norm"]
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+
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+ [initialize.tokenizer]
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+ {
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+ "lang":"en",
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+ "name":"skillner",
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+ "version":"3.7.1",
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+ "description":"A Named Entity Recognition (NER) model to extract SKILL, EXPERIENCE and BENEFIT from job adverts.",
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+ "author":"Explosion",
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+ "email":"contact@explosion.ai",
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+ "url":"https://explosion.ai",
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+ "license":"MIT",
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+ "spacy_version":">=3.7.4,<3.8.0",
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+ "spacy_git_version":"bd2c17e20",
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+ "name":null
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+ "labels":{
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+ "ner":[
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+ "SKILL",
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+ "EXPERIENCE",
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+ "BENEFIT"
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+ ]
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+ },
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+ "pipeline":[
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+ "tok2vec",
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+ "tagger",
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+ "parser",
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+ "attribute_ruler",
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+ "lemmatizer",
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+ "ner"
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+ ],
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+ "components":[
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+ "tok2vec",
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+ "tagger",
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+ "parser",
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+ "senter",
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+ "attribute_ruler",
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+ "lemmatizer",
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+ "ner"
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+ ],
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+ }
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+ }
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+ }
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+ },
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+ "sources":[
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+ {
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+ "name":"OntoNotes 5",
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+ "url":"https://catalog.ldc.upenn.edu/LDC2013T19",
206
+ "license":"commercial (licensed by Explosion)",
207
+ "author":"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"
208
+ },
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+ {
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+ "name":"ClearNLP Constituent-to-Dependency Conversion",
211
+ "url":"https://github.com/clir/clearnlp-guidelines/blob/master/md/components/dependency_conversion.md",
212
+ "license":"Citation provided for reference, no code packaged with model",
213
+ "author":"Emory University"
214
+ },
215
+ {
216
+ "name":"WordNet 3.0",
217
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