browndw commited on
Commit
1118d83
·
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1 Parent(s): 30b803d

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -30,3 +30,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
30
  *strings.json filter=lfs diff=lfs merge=lfs -text
31
  vectors filter=lfs diff=lfs merge=lfs -text
32
  model filter=lfs diff=lfs merge=lfs -text
 
 
 
 
30
  *strings.json filter=lfs diff=lfs merge=lfs -text
31
  vectors filter=lfs diff=lfs merge=lfs -text
32
  model filter=lfs diff=lfs merge=lfs -text
33
+ ner/model filter=lfs diff=lfs merge=lfs -text
34
+ tagger/model filter=lfs diff=lfs merge=lfs -text
35
+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -14,28 +14,28 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.7999501539
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8082591001
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8040831626
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9732027902
31
  ---
32
  English pipeline for part-of-speech and rhetorical tagging.
33
 
34
  | Feature | Description |
35
  | --- | --- |
36
  | **Name** | `en_docusco_spacy` |
37
- | **Version** | `1.4` |
38
- | **spaCy** | `>=3.7.4,<3.8.0` |
39
  | **Default Pipeline** | `tok2vec`, `tagger`, `ner` |
40
  | **Components** | `tok2vec`, `tagger`, `ner` |
41
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -47,11 +47,11 @@ English pipeline for part-of-speech and rhetorical tagging.
47
 
48
  <details>
49
 
50
- <summary>View label scheme (314 labels for 2 components)</summary>
51
 
52
  | Component | Labels |
53
  | --- | --- |
54
- | **`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`, `DDQGE31`, `DDQGE32`, `DDQGE33`, `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`, `JJ41`, `JJ42`, `JJ43`, `JJ44`, `JJR`, `JJT`, `JK`, `MC`, `MC1`, `MC121`, `MC122`, `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`, `NN32`, `NN33`, `NNA`, `NNB`, `NNL1`, `NNL2`, `NNO`, `NNO2`, `NNT1`, `NNT131`, `NNT132`, `NNT133`, `NNT2`, `NNU`, `NNU1`, `NNU2`, `NNU21`, `NNU22`, `NNU221`, `NNU222`, `NP`, `NP1`, `NP2`, `NPD1`, `NPD2`, `NPM1`, `NPM2`, `PN`, `PN1`, `PN121`, `PN122`, `PN21`, `PN22`, `PNQO`, `PNQS`, `PNQS31`, `PNQS32`, `PNQS33`, `PNQV`, `PNQV31`, `PNQV32`, `PNQV33`, `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`, `RG31`, `RG32`, `RG33`, `RG41`, `RG42`, `RG43`, `RG44`, `RGQ`, `RGQV`, `RGQV31`, `RGQV32`, `RGQV33`, `RGR`, `RGT`, `RL`, `RL21`, `RL22`, `RL31`, `RL32`, `RL33`, `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`** | `AcademicTerms`, `AcademicWritingMoves`, `Character`, `Citation`, `CitationAuthority`, `CitationHedged`, `ConfidenceHedged`, `ConfidenceHigh`, `ConfidenceLow`, `Contingent`, `Description`, `Facilitate`, `FirstPerson`, `ForceStressed`, `Future`, `InformationChange`, `InformationChangeNegative`, `InformationChangePositive`, `InformationExposition`, `InformationPlace`, `InformationReportVerbs`, `InformationStates`, `InformationTopics`, `Inquiry`, `Interactive`, `MetadiscourseCohesive`, `MetadiscourseInteractive`, `Narrative`, `Negative`, `Positive`, `PublicTerms`, `Reasoning`, `Responsibility`, `Strategic`, `Uncertainty`, `Updates` |
56
 
57
  </details>
@@ -60,10 +60,10 @@ English pipeline for part-of-speech and rhetorical tagging.
60
 
61
  | Type | Score |
62
  | --- | --- |
63
- | `TAG_ACC` | 97.32 |
64
- | `ENTS_F` | 80.41 |
65
- | `ENTS_P` | 80.00 |
66
- | `ENTS_R` | 80.83 |
67
- | `TOK2VEC_LOSS` | 297770148.23 |
68
- | `TAGGER_LOSS` | 4485596.63 |
69
- | `NER_LOSS` | 21563546.64 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8052588763
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8119413755
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  - name: NER F Score
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  type: f_score
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+ value: 0.8085863194
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9737589551
31
  ---
32
  English pipeline for part-of-speech and rhetorical tagging.
33
 
34
  | Feature | Description |
35
  | --- | --- |
36
  | **Name** | `en_docusco_spacy` |
37
+ | **Version** | `1.5` |
38
+ | **spaCy** | `>=3.8.6,<3.9.0` |
39
  | **Default Pipeline** | `tok2vec`, `tagger`, `ner` |
40
  | **Components** | `tok2vec`, `tagger`, `ner` |
41
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
47
 
48
  <details>
49
 
50
+ <summary>View label scheme (311 labels for 2 components)</summary>
51
 
52
  | Component | Labels |
53
  | --- | --- |
54
+ | **`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`, `DDQGE31`, `DDQGE32`, `DDQGE33`, `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`, `JJ41`, `JJ42`, `JJ43`, `JJ44`, `JJR`, `JJT`, `JK`, `MC`, `MC1`, `MC121`, `MC122`, `MC2`, `MC221`, `MC222`, `MCMC`, `MD`, `MF`, `ND1`, `NN`, `NN1`, `NN121`, `NN122`, `NN131`, `NN132`, `NN133`, `NN141`, `NN142`, `NN143`, `NN144`, `NN2`, `NN21`, `NN22`, `NN221`, `NN222`, `NN31`, `NN32`, `NN33`, `NNA`, `NNB`, `NNL1`, `NNL2`, `NNO`, `NNO2`, `NNT1`, `NNT131`, `NNT132`, `NNT133`, `NNT2`, `NNU`, `NNU1`, `NNU2`, `NNU21`, `NNU22`, `NNU221`, `NNU222`, `NP`, `NP1`, `NP2`, `NPD1`, `NPD2`, `NPM1`, `NPM2`, `PN`, `PN1`, `PN121`, `PN122`, `PN21`, `PN22`, `PNQO`, `PNQS`, `PNQS31`, `PNQS32`, `PNQS33`, `PNQV`, `PNQV31`, `PNQV32`, `PNQV33`, `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`, `RG31`, `RG32`, `RG33`, `RG41`, `RG42`, `RG43`, `RG44`, `RGQ`, `RGQV`, `RGQV31`, `RGQV32`, `RGQV33`, `RGR`, `RGT`, `RL`, `RL21`, `RL22`, `RL31`, `RL32`, `RL33`, `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`** | `AcademicTerms`, `AcademicWritingMoves`, `Character`, `Citation`, `CitationAuthority`, `CitationHedged`, `ConfidenceHedged`, `ConfidenceHigh`, `ConfidenceLow`, `Contingent`, `Description`, `Facilitate`, `FirstPerson`, `ForceStressed`, `Future`, `InformationChange`, `InformationChangeNegative`, `InformationChangePositive`, `InformationExposition`, `InformationPlace`, `InformationReportVerbs`, `InformationStates`, `InformationTopics`, `Inquiry`, `Interactive`, `MetadiscourseCohesive`, `MetadiscourseInteractive`, `Narrative`, `Negative`, `Positive`, `PublicTerms`, `Reasoning`, `Responsibility`, `Strategic`, `Uncertainty`, `Updates` |
56
 
57
  </details>
 
60
 
61
  | Type | Score |
62
  | --- | --- |
63
+ | `TAG_ACC` | 97.38 |
64
+ | `ENTS_F` | 80.86 |
65
+ | `ENTS_P` | 80.53 |
66
+ | `ENTS_R` | 81.19 |
67
+ | `TOK2VEC_LOSS` | 415094086.10 |
68
+ | `TAGGER_LOSS` | 5414630.50 |
69
+ | `NER_LOSS` | 25495485.94 |
config.cfg CHANGED
@@ -1,6 +1,6 @@
1
  [paths]
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- train = "spacy_train_08.spacy"
3
- dev = "spacy_dev_08.spacy"
4
  vectors = null
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  init_tok2vec = null
6
 
@@ -106,8 +106,8 @@ dropout = 0.1
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  accumulate_gradient = 1
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  patience = 20000
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  max_epochs = -1
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- max_steps = 80000
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- eval_frequency = 1000
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  frozen_components = []
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  annotating_components = []
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  before_to_disk = null
@@ -142,8 +142,8 @@ eps = 0.00000001
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  learn_rate = 0.001
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  [training.score_weights]
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- tag_acc = 0.4
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- ents_f = 0.6
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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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  [paths]
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+ train = "spacy_train.spacy"
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+ dev = "spacy_test.spacy"
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  vectors = null
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  init_tok2vec = null
6
 
 
106
  accumulate_gradient = 1
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  patience = 20000
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  max_epochs = -1
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+ max_steps = 96000
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+ eval_frequency = 1200
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  frozen_components = []
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  annotating_components = []
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  before_to_disk = null
 
142
  learn_rate = 0.001
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  [training.score_weights]
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+ ents_f = 0.65
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  ents_p = 0.0
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  ents_r = 0.0
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meta.json CHANGED
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  "name":"docusco_spacy",
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- "version":"1.4",
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  "description":"English pipeline for part-of-speech and rhetorical tagging.",
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  "author":"David Brown",
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  "email":"[email protected]",
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  "url":"https://docuscope.github.io",
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  "lang":"en",
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  "name":"docusco_spacy",
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