browndw commited on
Commit
8943bbd
1 Parent(s): a65ca70

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -32,3 +32,5 @@ 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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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* 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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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_docusco_spacy_cd-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,69 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ tags:
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+ - 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:
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+ - name: en_docusco_spacy_cd
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+ results:
11
+ - task:
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+ name: NER
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+ type: token-classification
14
+ metrics:
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+ - name: NER Precision
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+ type: precision
17
+ value: 0.7896141572
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+ - name: NER Recall
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+ type: recall
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+ value: 0.7757775447
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+ - name: NER F Score
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+ type: f_score
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+ value: 0.7826346995
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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: 0.9734866573
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+ ---
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+ English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.
33
+
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+ | Feature | Description |
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+ | --- | --- |
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+ | **Name** | `en_docusco_spacy_cd` |
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+ | **Version** | `1.2` |
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+ | **spaCy** | `>=3.5.0,<3.6.0` |
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+ | **Default Pipeline** | `tok2vec`, `tagger`, `ner` |
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+ | **Components** | `tok2vec`, `tagger`, `ner` |
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+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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+ | **Sources** | n/a |
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+ | **License** | `MIT` |
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+ | **Author** | [David Brown](https://docuscope.github.io) |
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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 (270 labels for 2 components)</summary>
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+
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+ | Component | Labels |
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+ | --- | --- |
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+ | **`tagger`** | `APPGE`, `AT`, `AT1`, `BCL21`, `BCL22`, `CC`, `CCB`, `CS`, `CS21`, `CS22`, `CS31`, `CS32`, `CS33`, `CS41`, `CS42`, `CS43`, `CS44`, `CSA`, `CSN`, `CST`, `CSW`, `CSW31`, `CSW32`, `CSW33`, `DA`, `DA1`, `DA2`, `DAR`, `DAT`, `DB`, `DB2`, `DD`, `DD1`, `DD2`, `DDQ`, `DDQGE`, `DDQV`, `DDQV31`, `DDQV32`, `DDQV33`, `EX`, `FO`, `FU`, `FW`, `GE`, `IF`, `II`, `II21`, `II22`, `II31`, `II32`, `II33`, `II41`, `II42`, `II43`, `II44`, `IO`, `IW`, `JJ`, `JJ21`, `JJ22`, `JJ31`, `JJ32`, `JJ33`, `JJR`, `JJT`, `JK`, `MC`, `MC1`, `MC2`, `MC221`, `MC222`, `MCMC`, `MD`, `MF`, `ND1`, `NN`, `NN1`, `NN121`, `NN122`, `NN131`, `NN132`, `NN133`, `NN141`, `NN142`, `NN143`, `NN144`, `NN2`, `NN21`, `NN22`, `NN221`, `NN222`, `NN231`, `NN232`, `NN233`, `NN31`, `NN33`, `NNA`, `NNB`, `NNL1`, `NNL2`, `NNO`, `NNO2`, `NNT1`, `NNT2`, `NNU`, `NNU1`, `NNU2`, `NNU21`, `NNU22`, `NP`, `NP1`, `NP2`, `NPD1`, `NPD2`, `NPM1`, `NPM2`, `PN`, `PN1`, `PN121`, `PN122`, `PN21`, `PN22`, `PNQO`, `PNQS`, `PNQS31`, `PNQS32`, `PNQS33`, `PNQV`, `PNX1`, `PPGE`, `PPH1`, `PPHO1`, `PPHO2`, `PPHS1`, `PPHS2`, `PPIO1`, `PPIO2`, `PPIS1`, `PPIS2`, `PPX1`, `PPX121`, `PPX122`, `PPX2`, `PPX221`, `PPX222`, `PPY`, `RA`, `RA21`, `RA22`, `REX`, `REX21`, `REX22`, `REX41`, `REX42`, `REX43`, `REX44`, `RG`, `RG21`, `RG22`, `RGQ`, `RGQV`, `RGQV31`, `RGQV32`, `RGQV33`, `RGR`, `RGT`, `RL`, `RL21`, `RL22`, `RP`, `RPK`, `RR`, `RR21`, `RR22`, `RR31`, `RR32`, `RR33`, `RR41`, `RR42`, `RR43`, `RR44`, `RR51`, `RR52`, `RR53`, `RR54`, `RR55`, `RRQ`, `RRQV`, `RRQV31`, `RRQV32`, `RRQV33`, `RRR`, `RRT`, `RT`, `RT21`, `RT22`, `RT31`, `RT32`, `RT33`, `RT41`, `RT42`, `RT43`, `RT44`, `TO`, `UH`, `UH21`, `UH22`, `UH31`, `UH32`, `UH33`, `VB0`, `VBDR`, `VBDZ`, `VBG`, `VBI`, `VBM`, `VBN`, `VBR`, `VBZ`, `VD0`, `VDD`, `VDG`, `VDI`, `VDN`, `VDZ`, `VH0`, `VHD`, `VHG`, `VHI`, `VHN`, `VHZ`, `VM`, `VM21`, `VM22`, `VMK`, `VV0`, `VVD`, `VVG`, `VVGK`, `VVI`, `VVN`, `VVNK`, `VVZ`, `XX`, `Y`, `ZZ1`, `ZZ2`, `ZZ221`, `ZZ222` |
55
+ | **`ner`** | `ActorsAbstractions`, `ActorsFirstPerson`, `ActorsPeople`, `ActorsPublicEntities`, `CitationAuthority`, `CitationControversy`, `CitationHedged`, `CitationNeutral`, `ConfidenceHedged`, `ConfidenceHigh`, `OrganizationNarrative`, `OrganizationReasoning`, `PlanningFuture`, `PlanningStrategy`, `SentimentNegative`, `SentimentPositive`, `SignpostingAcademicWritingMoves`, `SignpostingMetadiscourse`, `StanceEmphatic`, `StanceModerated` |
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+
57
+ </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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+ | `TAG_ACC` | 97.35 |
64
+ | `ENTS_F` | 78.26 |
65
+ | `ENTS_P` | 78.96 |
66
+ | `ENTS_R` | 77.58 |
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+ | `TOK2VEC_LOSS` | 5937424.94 |
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+ | `TAGGER_LOSS` | 1136040.49 |
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+ | `NER_LOSS` | 3941726.32 |
config.cfg ADDED
@@ -0,0 +1,175 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ [paths]
2
+ train = ""
3
+ dev = ""
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+ vectors = null
5
+ init_tok2vec = null
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+
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+ [system]
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+ gpu_allocator = null
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+ seed = 0
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+
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+ [nlp]
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+ lang = "en"
13
+ pipeline = ["tok2vec","tagger","ner"]
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+ batch_size = 1000
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+ disabled = []
16
+ before_creation = null
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+ after_creation = null
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+ after_pipeline_creation = null
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+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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+
21
+ [components]
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+
23
+ [components.ner]
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+ factory = "ner"
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+ incorrect_spans_key = null
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+ moves = null
27
+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
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+ update_with_oracle_cut_size = 100
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+
30
+ [components.ner.model]
31
+ @architectures = "spacy.TransitionBasedParser.v2"
32
+ state_type = "ner"
33
+ 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.Tok2VecListener.v1"
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+ width = ${components.tok2vec.model.encode.width}
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+ upstream = "*"
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+
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+ [components.tagger]
45
+ factory = "tagger"
46
+ neg_prefix = "!"
47
+ overwrite = false
48
+ scorer = {"@scorers":"spacy.tagger_scorer.v1"}
49
+
50
+ [components.tagger.model]
51
+ @architectures = "spacy.Tagger.v2"
52
+ nO = null
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+ normalize = false
54
+
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+ [components.tagger.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
57
+ width = ${components.tok2vec.model.encode.width}
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+ upstream = "*"
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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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+
66
+ [components.tok2vec.model.embed]
67
+ @architectures = "spacy.MultiHashEmbed.v2"
68
+ width = ${components.tok2vec.model.encode.width}
69
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
70
+ rows = [5000,1000,2500,2500]
71
+ include_static_vectors = false
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+
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+ [components.tok2vec.model.encode]
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+ @architectures = "spacy.MaxoutWindowEncoder.v2"
75
+ width = 96
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+ depth = 4
77
+ window_size = 1
78
+ maxout_pieces = 3
79
+
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+ [corpora]
81
+
82
+ [corpora.dev]
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+ @readers = "spacy.Corpus.v1"
84
+ path = ${paths.dev}
85
+ max_length = 0
86
+ gold_preproc = false
87
+ limit = 0
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+ augmenter = null
89
+
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+ [corpora.train]
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+ @readers = "spacy.Corpus.v1"
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+ path = ${paths.train}
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+ max_length = 0
94
+ gold_preproc = false
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+ limit = 0
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+ augmenter = null
97
+
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+ [training]
99
+ dev_corpus = "corpora.dev"
100
+ train_corpus = "corpora.train"
101
+ seed = ${system.seed}
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+ gpu_allocator = ${system.gpu_allocator}
103
+ dropout = 0.1
104
+ accumulate_gradient = 1
105
+ patience = 1600
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+ max_epochs = 0
107
+ max_steps = 35000
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+ eval_frequency = 250
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+ frozen_components = []
110
+ annotating_components = []
111
+ before_to_disk = null
112
+ before_update = null
113
+
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+ [training.batcher]
115
+ @batchers = "spacy.batch_by_words.v1"
116
+ discard_oversize = false
117
+ tolerance = 0.2
118
+ get_length = null
119
+
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+ [training.batcher.size]
121
+ @schedules = "compounding.v1"
122
+ start = 100
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+ stop = 1000
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+ compound = 1.001
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+ t = 0.0
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+
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+ [training.logger]
128
+ @loggers = "spacy.ConsoleLogger.v1"
129
+ progress_bar = false
130
+
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+ [training.optimizer]
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+ @optimizers = "Adam.v1"
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+ beta1 = 0.9
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+ beta2 = 0.999
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+ L2_is_weight_decay = true
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+ L2 = 0.01
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+ grad_clip = 1.0
138
+ use_averages = false
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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 = 0.5
144
+ ents_f = 0.5
145
+ ents_p = 0.0
146
+ ents_r = 0.0
147
+ ents_per_type = null
148
+
149
+ [pretraining]
150
+
151
+ [initialize]
152
+ vectors = ${paths.vectors}
153
+ init_tok2vec = ${paths.init_tok2vec}
154
+ vocab_data = null
155
+ lookups = null
156
+ before_init = null
157
+ after_init = null
158
+
159
+ [initialize.components]
160
+
161
+ [initialize.components.ner]
162
+
163
+ [initialize.components.ner.labels]
164
+ @readers = "spacy.read_labels.v1"
165
+ path = "ner.json"
166
+ require = false
167
+
168
+ [initialize.components.tagger]
169
+
170
+ [initialize.components.tagger.labels]
171
+ @readers = "spacy.read_labels.v1"
172
+ path = "tagger.json"
173
+ require = false
174
+
175
+ [initialize.tokenizer]
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1
+ {
2
+ "lang":"en",
3
+ "name":"docusco_spacy_cd",
4
+ "version":"1.2",
5
+ "description":"English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.",
6
+ "author":"David Brown",
7
+ "email":"dwb2@andrew.cmu.edu",
8
+ "url":"https://docuscope.github.io",
9
+ "license":"MIT",
10
+ "spacy_git_version":"Unknown",
11
+ "vectors":{
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+ "width":0,
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+ "vectors":0,
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+ "keys":0,
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+ "name":null
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+ },
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+ "labels":{
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+ "tok2vec":[
19
+
20
+ ],
21
+ "tagger":[
22
+ "APPGE",
23
+ "AT",
24
+ "AT1",
25
+ "BCL21",
26
+ "BCL22",
27
+ "CC",
28
+ "CCB",
29
+ "CS",
30
+ "CS21",
31
+ "CS22",
32
+ "CS31",
33
+ "CS32",
34
+ "CS33",
35
+ "CS41",
36
+ "CS42",
37
+ "CS43",
38
+ "CS44",
39
+ "CSA",
40
+ "CSN",
41
+ "CST",
42
+ "CSW",
43
+ "CSW31",
44
+ "CSW32",
45
+ "CSW33",
46
+ "DA",
47
+ "DA1",
48
+ "DA2",
49
+ "DAR",
50
+ "DAT",
51
+ "DB",
52
+ "DB2",
53
+ "DD",
54
+ "DD1",
55
+ "DD2",
56
+ "DDQ",
57
+ "DDQGE",
58
+ "DDQV",
59
+ "DDQV31",
60
+ "DDQV32",
61
+ "DDQV33",
62
+ "EX",
63
+ "FO",
64
+ "FU",
65
+ "FW",
66
+ "GE",
67
+ "IF",
68
+ "II",
69
+ "II21",
70
+ "II22",
71
+ "II31",
72
+ "II32",
73
+ "II33",
74
+ "II41",
75
+ "II42",
76
+ "II43",
77
+ "II44",
78
+ "IO",
79
+ "IW",
80
+ "JJ",
81
+ "JJ21",
82
+ "JJ22",
83
+ "JJ31",
84
+ "JJ32",
85
+ "JJ33",
86
+ "JJR",
87
+ "JJT",
88
+ "JK",
89
+ "MC",
90
+ "MC1",
91
+ "MC2",
92
+ "MC221",
93
+ "MC222",
94
+ "MCMC",
95
+ "MD",
96
+ "MF",
97
+ "ND1",
98
+ "NN",
99
+ "NN1",
100
+ "NN121",
101
+ "NN122",
102
+ "NN131",
103
+ "NN132",
104
+ "NN133",
105
+ "NN141",
106
+ "NN142",
107
+ "NN143",
108
+ "NN144",
109
+ "NN2",
110
+ "NN21",
111
+ "NN22",
112
+ "NN221",
113
+ "NN222",
114
+ "NN231",
115
+ "NN232",
116
+ "NN233",
117
+ "NN31",
118
+ "NN33",
119
+ "NNA",
120
+ "NNB",
121
+ "NNL1",
122
+ "NNL2",
123
+ "NNO",
124
+ "NNO2",
125
+ "NNT1",
126
+ "NNT2",
127
+ "NNU",
128
+ "NNU1",
129
+ "NNU2",
130
+ "NNU21",
131
+ "NNU22",
132
+ "NP",
133
+ "NP1",
134
+ "NP2",
135
+ "NPD1",
136
+ "NPD2",
137
+ "NPM1",
138
+ "NPM2",
139
+ "PN",
140
+ "PN1",
141
+ "PN121",
142
+ "PN122",
143
+ "PN21",
144
+ "PN22",
145
+ "PNQO",
146
+ "PNQS",
147
+ "PNQS31",
148
+ "PNQS32",
149
+ "PNQS33",
150
+ "PNQV",
151
+ "PNX1",
152
+ "PPGE",
153
+ "PPH1",
154
+ "PPHO1",
155
+ "PPHO2",
156
+ "PPHS1",
157
+ "PPHS2",
158
+ "PPIO1",
159
+ "PPIO2",
160
+ "PPIS1",
161
+ "PPIS2",
162
+ "PPX1",
163
+ "PPX121",
164
+ "PPX122",
165
+ "PPX2",
166
+ "PPX221",
167
+ "PPX222",
168
+ "PPY",
169
+ "RA",
170
+ "RA21",
171
+ "RA22",
172
+ "REX",
173
+ "REX21",
174
+ "REX22",
175
+ "REX41",
176
+ "REX42",
177
+ "REX43",
178
+ "REX44",
179
+ "RG",
180
+ "RG21",
181
+ "RG22",
182
+ "RGQ",
183
+ "RGQV",
184
+ "RGQV31",
185
+ "RGQV32",
186
+ "RGQV33",
187
+ "RGR",
188
+ "RGT",
189
+ "RL",
190
+ "RL21",
191
+ "RL22",
192
+ "RP",
193
+ "RPK",
194
+ "RR",
195
+ "RR21",
196
+ "RR22",
197
+ "RR31",
198
+ "RR32",
199
+ "RR33",
200
+ "RR41",
201
+ "RR42",
202
+ "RR43",
203
+ "RR44",
204
+ "RR51",
205
+ "RR52",
206
+ "RR53",
207
+ "RR54",
208
+ "RR55",
209
+ "RRQ",
210
+ "RRQV",
211
+ "RRQV31",
212
+ "RRQV32",
213
+ "RRQV33",
214
+ "RRR",
215
+ "RRT",
216
+ "RT",
217
+ "RT21",
218
+ "RT22",
219
+ "RT31",
220
+ "RT32",
221
+ "RT33",
222
+ "RT41",
223
+ "RT42",
224
+ "RT43",
225
+ "RT44",
226
+ "TO",
227
+ "UH",
228
+ "UH21",
229
+ "UH22",
230
+ "UH31",
231
+ "UH32",
232
+ "UH33",
233
+ "VB0",
234
+ "VBDR",
235
+ "VBDZ",
236
+ "VBG",
237
+ "VBI",
238
+ "VBM",
239
+ "VBN",
240
+ "VBR",
241
+ "VBZ",
242
+ "VD0",
243
+ "VDD",
244
+ "VDG",
245
+ "VDI",
246
+ "VDN",
247
+ "VDZ",
248
+ "VH0",
249
+ "VHD",
250
+ "VHG",
251
+ "VHI",
252
+ "VHN",
253
+ "VHZ",
254
+ "VM",
255
+ "VM21",
256
+ "VM22",
257
+ "VMK",
258
+ "VV0",
259
+ "VVD",
260
+ "VVG",
261
+ "VVGK",
262
+ "VVI",
263
+ "VVN",
264
+ "VVNK",
265
+ "VVZ",
266
+ "XX",
267
+ "Y",
268
+ "ZZ1",
269
+ "ZZ2",
270
+ "ZZ221",
271
+ "ZZ222"
272
+ ],
273
+ "ner":[
274
+ "ActorsAbstractions",
275
+ "ActorsFirstPerson",
276
+ "ActorsPeople",
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