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1 Parent(s): fa0d427

Update spaCy pipeline

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.gitattributes CHANGED
@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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+ en_core_web_trf_esco_ner-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ transformer/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,98 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
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+ tags:
3
+ - spacy
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+ - token-classification
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+ language:
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+ - en
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+ license: mit
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+ model-index:
9
+ - name: en_core_web_trf_esco_ner
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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
16
+ type: precision
17
+ value: 0.9008293365
18
+ - name: NER Recall
19
+ type: recall
20
+ value: 0.9029947917
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.9019107643
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+ - task:
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+ name: TAG
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+ type: token-classification
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+ metrics:
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+ - name: TAG (XPOS) Accuracy
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+ type: accuracy
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+ value: 0.9812819818
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+ - task:
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+ name: UNLABELED_DEPENDENCIES
33
+ type: token-classification
34
+ metrics:
35
+ - name: Unlabeled Attachment Score (UAS)
36
+ type: f_score
37
+ value: 0.9526219812
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+ - task:
39
+ name: LABELED_DEPENDENCIES
40
+ type: token-classification
41
+ metrics:
42
+ - name: Labeled Attachment Score (LAS)
43
+ type: f_score
44
+ value: 0.9390746643
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+ - task:
46
+ name: SENTS
47
+ type: token-classification
48
+ metrics:
49
+ - name: Sentences F-Score
50
+ type: f_score
51
+ value: 0.9011225055
52
+ ---
53
+ English transformer pipeline based on en_core_web_trf plus an entity recognizer based on the ESCO taxonomy. (Transformer(name='roberta-base', piece_encoder='byte-bpe', stride=104, type='roberta', width=768, window=144, vocab_size=50265)). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.
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+
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_core_web_trf_esco_ner` |
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+ | **Version** | `3.7.3` |
59
+ | **spaCy** | `>=3.7.2,<3.8.0` |
60
+ | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner`, `entity_ruler` |
61
+ | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner`, `entity_ruler` |
62
+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
63
+ | **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>[roberta-base](https://github.com/pytorch/fairseq/tree/master/examples/roberta) (Yinhan Liu and Myle Ott and Naman Goyal and Jingfei Du and Mandar Joshi and Danqi Chen and Omer Levy and Mike Lewis and Luke Zettlemoyer and Veselin Stoyanov) |
64
+ | **License** | `MIT` |
65
+ | **Author** | [[email protected]](https://github.com/par-tec/esco-playground) |
66
+
67
+ ### Label Scheme
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+
69
+ <details>
70
+
71
+ <summary>View label scheme (113 labels for 4 components)</summary>
72
+
73
+ | Component | Labels |
74
+ | --- | --- |
75
+ | **`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`, ```` |
76
+ | **`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` |
77
+ | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
78
+ | **`entity_ruler`** | `ESCO` |
79
+
80
+ </details>
81
+
82
+ ### Accuracy
83
+
84
+ | Type | Score |
85
+ | --- | --- |
86
+ | `TOKEN_ACC` | 99.86 |
87
+ | `TOKEN_P` | 99.57 |
88
+ | `TOKEN_R` | 99.58 |
89
+ | `TOKEN_F` | 99.57 |
90
+ | `TAG_ACC` | 98.13 |
91
+ | `SENTS_P` | 94.89 |
92
+ | `SENTS_R` | 85.79 |
93
+ | `SENTS_F` | 90.11 |
94
+ | `DEP_UAS` | 95.26 |
95
+ | `DEP_LAS` | 93.91 |
96
+ | `ENTS_P` | 90.08 |
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+ | `ENTS_R` | 90.30 |
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+ | `ENTS_F` | 90.19 |
attribute_ruler/patterns ADDED
Binary file (14.7 kB). View file
 
config.cfg ADDED
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+ [paths]
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+ train = null
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+ dev = null
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+ vectors = null
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+ init_tok2vec = null
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+
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+ [system]
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+ gpu_allocator = "pytorch"
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+ seed = 1
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+
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+ [nlp]
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+ lang = "en"
13
+ pipeline = ["transformer","tagger","parser","attribute_ruler","lemmatizer","ner","entity_ruler"]
14
+ disabled = []
15
+ before_creation = null
16
+ after_creation = null
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+ after_pipeline_creation = null
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+ batch_size = 64
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
20
+ vectors = {"@vectors":"spacy.Vectors.v1"}
21
+
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+ [components]
23
+
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+ [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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+
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+ [components.entity_ruler]
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+ factory = "entity_ruler"
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+ ent_id_sep = "||"
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+ matcher_fuzzy_compare = {"@misc":"spacy.levenshtein_compare.v1"}
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+ overwrite_ents = false
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+ phrase_matcher_attr = null
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+ scorer = {"@scorers":"spacy.entity_ruler_scorer.v1"}
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+ validate = false
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+
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+ [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"}
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+ update_with_oracle_cut_size = 100
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+
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+ [components.ner.model]
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+ @architectures = "spacy.TransitionBasedParser.v2"
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+ 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 = false
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+ nO = null
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+
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+ [components.ner.model.tok2vec]
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+ @architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
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+ width = ${components.transformer.model.hidden_width}
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+ upstream = "transformer"
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ grad_factor = 1.0
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+
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+ [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 = false
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+ nO = null
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+
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+ [components.parser.model.tok2vec]
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+ @architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
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+ width = ${components.transformer.model.hidden_width}
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+ upstream = "transformer"
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ grad_factor = 1.0
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+
92
+ [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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+
104
+ [components.tagger.model.tok2vec]
105
+ @architectures = "spacy-curated-transformers.LastTransformerLayerListener.v1"
106
+ width = ${components.transformer.model.hidden_width}
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+ upstream = "transformer"
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+ pooling = {"@layers":"reduce_mean.v1"}
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+ grad_factor = 1.0
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+
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+ [components.transformer]
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+ factory = "curated_transformer"
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+ all_layer_outputs = false
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+ frozen = false
115
+
116
+ [components.transformer.model]
117
+ @architectures = "spacy-curated-transformers.RobertaTransformer.v1"
118
+ vocab_size = 50265
119
+ hidden_width = 768
120
+ piece_encoder = {"@architectures":"spacy-curated-transformers.ByteBpeEncoder.v1"}
121
+ attention_probs_dropout_prob = 0.1
122
+ hidden_act = "gelu"
123
+ hidden_dropout_prob = 0.1
124
+ intermediate_width = 3072
125
+ layer_norm_eps = 0.00001
126
+ max_position_embeddings = 514
127
+ model_max_length = 512
128
+ num_attention_heads = 12
129
+ num_hidden_layers = 12
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+ padding_idx = 1
131
+ type_vocab_size = 1
132
+ torchscript = false
133
+ mixed_precision = false
134
+ wrapped_listener = null
135
+
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+ [components.transformer.model.grad_scaler_config]
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+
138
+ [components.transformer.model.with_spans]
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+ @architectures = "spacy-curated-transformers.WithStridedSpans.v1"
140
+ stride = 104
141
+ window = 144
142
+ batch_size = 384
143
+
144
+ [corpora]
145
+
146
+ [corpora.dev]
147
+ @readers = "spacy.Corpus.v1"
148
+ path = ${paths.dev}
149
+ gold_preproc = false
150
+ max_length = 0
151
+ limit = 0
152
+ augmenter = null
153
+
154
+ [corpora.train]
155
+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
157
+ gold_preproc = false
158
+ max_length = 0
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+ limit = 0
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+ augmenter = null
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+
162
+ [training]
163
+ train_corpus = "corpora.train"
164
+ dev_corpus = "corpora.dev"
165
+ seed = ${system:seed}
166
+ gpu_allocator = ${system:gpu_allocator}
167
+ dropout = 0.1
168
+ accumulate_gradient = 3
169
+ patience = 5000
170
+ max_epochs = 0
171
+ max_steps = 20000
172
+ eval_frequency = 1000
173
+ frozen_components = []
174
+ before_to_disk = null
175
+ annotating_components = []
176
+ before_update = null
177
+
178
+ [training.batcher]
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+ @batchers = "spacy.batch_by_words.v1"
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+ discard_oversize = false
181
+ size = 2000
182
+ tolerance = 0.2
183
+ get_length = null
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+
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+ [training.logger]
186
+ @loggers = "spacy.ConsoleLogger.v1"
187
+ progress_bar = false
188
+
189
+ [training.optimizer]
190
+ @optimizers = "Adam.v1"
191
+ beta1 = 0.9
192
+ beta2 = 0.999
193
+ L2_is_weight_decay = true
194
+ L2 = 0.01
195
+ grad_clip = 1.0
196
+ use_averages = true
197
+ eps = 0.00000001
198
+
199
+ [training.optimizer.learn_rate]
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+ @schedules = "warmup_linear.v1"
201
+ warmup_steps = 250
202
+ total_steps = 20000
203
+ initial_rate = 0.00005
204
+
205
+ [training.score_weights]
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+ tag_acc = 0.16
207
+ 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
218
+ speed = 0.0
219
+
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+ [pretraining]
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+
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+ [initialize]
223
+ vocab_data = null
224
+ vectors = ${paths.vectors}
225
+ init_tok2vec = ${paths.init_tok2vec}
226
+ before_init = null
227
+ after_init = null
228
+
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+ [initialize.components]
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+
231
+ [initialize.components.ner]
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+
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+ [initialize.components.ner.labels]
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+ @readers = "spacy.read_labels.v1"
235
+ path = "corpus/labels/ner.json"
236
+ require = false
237
+
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+ [initialize.components.parser]
239
+
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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.components.transformer]
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+
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+ [initialize.components.transformer.encoder_loader]
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+ @model_loaders = "spacy-curated-transformers.HFTransformerEncoderLoader.v1"
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+ name = "roberta-base"
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+ revision = "main"
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+
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+ [initialize.components.transformer.piecer_loader]
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+ @model_loaders = "spacy-curated-transformers.HFPieceEncoderLoader.v1"
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+ name = "roberta-base"
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+ revision = "main"
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+
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+ [initialize.lookups]
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+ @misc = "spacy.LookupsDataLoader.v1"
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+ lang = ${nlp.lang}
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+ tables = ["lexeme_norm"]
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+
269
+ [initialize.tokenizer]
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+ {
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+ "lang":"en",
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+ "name":"core_web_trf_esco_ner",
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+ "version":"3.7.3",
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+ "description":"English transformer pipeline based on en_core_web_trf plus an entity recognizer based on the ESCO taxonomy. (Transformer(name='roberta-base', piece_encoder='byte-bpe', stride=104, type='roberta', width=768, window=144, vocab_size=50265)). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.",
6
+ "author":"[email protected]",
7
+ "email":"[email protected]",
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+ "url":"https://github.com/par-tec/esco-playground",
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+ "license":"MIT",
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+ "spacy_version":">=3.7.2,<3.8.0",
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+ "spacy_git_version":"a89eae928",
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+ "vectors":{
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+ "width":0,
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+ "labels":{
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+ "transformer":[
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+ "tagger":[
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+ "$",
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+ "''",
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+ ",",
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+ "-LRB-",
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+ "-RRB-",
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+ ".",
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+ ":",
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+ "ADD",
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+ "AFX",
32
+ "CC",
33
+ "CD",
34
+ "DT",
35
+ "EX",
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+ "FW",
37
+ "HYPH",
38
+ "IN",
39
+ "JJ",
40
+ "JJR",
41
+ "JJS",
42
+ "LS",
43
+ "MD",
44
+ "NFP",
45
+ "NN",
46
+ "NNP",
47
+ "NNPS",
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+ "NNS",
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+ "PDT",
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+ "POS",
51
+ "PRP",
52
+ "PRP$",
53
+ "RB",
54
+ "RBR",
55
+ "RBS",
56
+ "RP",
57
+ "SYM",
58
+ "TO",
59
+ "UH",
60
+ "VB",
61
+ "VBD",
62
+ "VBG",
63
+ "VBN",
64
+ "VBP",
65
+ "VBZ",
66
+ "WDT",
67
+ "WP",
68
+ "WP$",
69
+ "WRB",
70
+ "XX",
71
+ "``"
72
+ ],
73
+ "parser":[
74
+ "ROOT",
75
+ "acl",
76
+ "acomp",
77
+ "advcl",
78
+ "advmod",
79
+ "agent",
80
+ "amod",
81
+ "appos",
82
+ "attr",
83
+ "aux",
84
+ "auxpass",
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