Update spaCy pipeline
Browse files- .gitattributes +3 -0
- README.md +15 -15
- config.cfg +6 -6
- en_docusco_spacy_cd-any-py3-none-any.whl +2 -2
- meta.json +90 -86
- ner/model +0 -0
- ner/moves +1 -1
- tagger/cfg +6 -2
- tagger/model +0 -0
- tok2vec/model +1 -1
- vocab/strings.json +0 -0
.gitattributes
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@@ -34,3 +34,6 @@ saved_model/**/* 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
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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
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ner/model filter=lfs diff=lfs merge=lfs -text
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tagger/model filter=lfs diff=lfs merge=lfs -text
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vocab/strings.json filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -14,28 +14,28 @@ model-index:
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metrics:
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- name: NER Precision
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type: precision
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-
value: 0.
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- name: NER Recall
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type: recall
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-
value: 0.
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- name: NER F Score
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type: f_score
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-
value: 0.
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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.
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---
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English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.
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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.
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| **spaCy** | `>=3.
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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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@@ -47,11 +47,11 @@ English pipeline for part-of-speech and rhetorical tagging using a smaller 'comm
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<details>
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-
<summary>View label scheme (
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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`, `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`, `
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| **`ner`** | `ActorsAbstractions`, `ActorsFirstPerson`, `ActorsPeople`, `ActorsPublicEntities`, `CitationAuthority`, `CitationControversy`, `CitationNeutral`, `ConfidenceHedged`, `ConfidenceHigh`, `OrganizationNarrative`, `OrganizationReasoning`, `PlanningFuture`, `PlanningStrategy`, `SentimentNegative`, `SentimentPositive`, `SignpostingAcademicWritingMoves`, `SignpostingMetadiscourse`, `StanceEmphatic`, `StanceModerated` |
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</details>
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@@ -60,10 +60,10 @@ English pipeline for part-of-speech and rhetorical tagging using a smaller 'comm
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| Type | Score |
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| --- | --- |
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-
| `TAG_ACC` | 97.
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| `ENTS_F` | 81.
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| `ENTS_P` | 82.
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| `ENTS_R` | 80.
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-
| `TOK2VEC_LOSS` |
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| `TAGGER_LOSS` |
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| `NER_LOSS` |
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metrics:
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- name: NER Precision
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type: precision
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+
value: 0.8259539432
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- name: NER Recall
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type: recall
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value: 0.8094701467
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- name: NER F Score
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type: f_score
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value: 0.8176289731
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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: 0.9767705858
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---
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English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.
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| Feature | Description |
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| --- | --- |
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| **Name** | `en_docusco_spacy_cd` |
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| **Version** | `1.5` |
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| **spaCy** | `>=3.8.6,<3.9.0` |
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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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<details>
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<summary>View label scheme (293 labels for 2 components)</summary>
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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`, `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`, `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`, `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` |
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| **`ner`** | `ActorsAbstractions`, `ActorsFirstPerson`, `ActorsPeople`, `ActorsPublicEntities`, `CitationAuthority`, `CitationControversy`, `CitationNeutral`, `ConfidenceHedged`, `ConfidenceHigh`, `OrganizationNarrative`, `OrganizationReasoning`, `PlanningFuture`, `PlanningStrategy`, `SentimentNegative`, `SentimentPositive`, `SignpostingAcademicWritingMoves`, `SignpostingMetadiscourse`, `StanceEmphatic`, `StanceModerated` |
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</details>
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| Type | Score |
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| --- | --- |
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+
| `TAG_ACC` | 97.68 |
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| `ENTS_F` | 81.76 |
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| `ENTS_P` | 82.60 |
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| `ENTS_R` | 80.95 |
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| 67 |
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| `TOK2VEC_LOSS` | 210102533.04 |
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| `TAGGER_LOSS` | 4732599.11 |
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| `NER_LOSS` | 15047904.69 |
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config.cfg
CHANGED
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@@ -1,6 +1,6 @@
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[paths]
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-
train = "
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-
dev = "
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vectors = null
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init_tok2vec = null
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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 =
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-
eval_frequency =
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frozen_components = []
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annotating_components = []
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before_to_disk = null
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learn_rate = 0.001
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[training.score_weights]
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-
tag_acc = 0.
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-
ents_f = 0.
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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_cd.spacy"
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dev = "spacy_test_cd.spacy"
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vectors = null
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init_tok2vec = null
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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 = 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
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learn_rate = 0.001
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[training.score_weights]
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tag_acc = 0.35
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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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ents_per_type = null
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en_docusco_spacy_cd-any-py3-none-any.whl
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meta.json
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{
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"lang":"en",
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"name":"docusco_spacy_cd",
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-
"version":"1.
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"description":"English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.",
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"author":"David Brown",
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"email":"dwb2@andrew.cmu.edu",
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"url":"https://docuscope.github.io",
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"license":"MIT",
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-
"spacy_version":">=3.
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"spacy_git_version":"
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"vectors":{
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"width":0,
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"vectors":0,
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"JK",
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"MC",
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"MC1",
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"MC121",
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"MC122",
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"MC2",
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"MC221",
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"MC222",
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"NN22",
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"NN221",
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"NN222",
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"NN31",
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"NN32",
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"NN33",
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"RG",
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"RG21",
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"RG22",
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"RG41",
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"RG42",
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"RG43",
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],
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"performance":{
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}
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},
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"tok2vec_loss":
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"tagger_loss":
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"ner_loss":
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},
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"requirements":[
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-
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]
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}
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{
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"lang":"en",
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"name":"docusco_spacy_cd",
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"version":"1.5",
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"description":"English pipeline for part-of-speech and rhetorical tagging using a smaller 'common dictionary'.",
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"author":"David Brown",
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"email":"dwb2@andrew.cmu.edu",
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"url":"https://docuscope.github.io",
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"license":"MIT",
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"spacy_version":">=3.8.6,<3.9.0",
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"spacy_git_version":"911539e",
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"vectors":{
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"width":0,
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"vectors":0,
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"JK",
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"MC",
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"MC1",
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"MC2",
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"MC221",
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"MC222",
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ner/model
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ner/moves
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tagger/cfg
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@@ -77,8 +77,6 @@
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@@ -102,6 +100,9 @@
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| 102 |
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| 104 |
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| 105 |
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| 174 |
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| 176 |
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| 77 |
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| 100 |
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tagger/model
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tok2vec/model
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