Update spaCy pipeline

README.md

@@ -14,28 +14,28 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.798987704
+      value: 0.7999501539
     - name: NER Recall
       type: recall
-      value: 0.7954112218
+      value: 0.8082591001
     - name: NER F Score
       type: f_score
-      value: 0.7971954516
+      value: 0.8040831626
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9698599662
+      value: 0.9732027902
 ---
 English pipeline for part-of-speech and rhetorical tagging.
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `en_docusco_spacy` |
-| **Version** | `1.3` |
-| **spaCy** | `>=3.5.0,<3.6.0` |
+| **Version** | `1.4` |
+| **spaCy** | `>=3.7.4,<3.8.0` |
 | **Default Pipeline** | `tok2vec`, `tagger`, `ner` |
 | **Components** | `tok2vec`, `tagger`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -47,11 +47,11 @@ English pipeline for part-of-speech and rhetorical tagging.
 
 <details>
 
-<summary>View label scheme (308 labels for 2 components)</summary>
+<summary>View label scheme (314 labels for 2 components)</summary>
 
 | Component | Labels |
 | --- | --- |
-| **`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`, `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`, `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` |
+| **`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` |
 | **`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` |
 
 </details>
@@ -60,10 +60,10 @@ English pipeline for part-of-speech and rhetorical tagging.
 
 | Type | Score |
 | --- | --- |
-| `TAG_ACC` | 96.99 |
-| `ENTS_F` | 79.72 |
-| `ENTS_P` | 79.90 |
-| `ENTS_R` | 79.54 |
-| `TOK2VEC_LOSS` | 20924847.53 |
-| `TAGGER_LOSS` | 1316790.55 |
-| `NER_LOSS` | 5818469.98 |
+| `TAG_ACC` | 97.32 |
+| `ENTS_F` | 80.41 |
+| `ENTS_P` | 80.00 |
+| `ENTS_R` | 80.83 |
+| `TOK2VEC_LOSS` | 297770148.23 |
+| `TAGGER_LOSS` | 4485596.63 |
+| `NER_LOSS` | 21563546.64 |

config.cfg

@@ -1,6 +1,6 @@
 [paths]
-train = "spacy_train_fd.spacy"
-dev = "spacy_test_fd.spacy"
+train = "spacy_train_08.spacy"
+dev = "spacy_dev_08.spacy"
 vectors = null
 init_tok2vec = null
 
@@ -17,6 +17,7 @@ before_creation = null
 after_creation = null
 after_pipeline_creation = null
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+vectors = {"@vectors":"spacy.Vectors.v1"}
 
 [components]
 
@@ -43,6 +44,7 @@ upstream = "*"
 
 [components.tagger]
 factory = "tagger"
+label_smoothing = 0.05
 neg_prefix = "!"
 overwrite = false
 scorer = {"@scorers":"spacy.tagger_scorer.v1"}
@@ -102,10 +104,10 @@ seed = ${system.seed}
 gpu_allocator = ${system.gpu_allocator}
 dropout = 0.1
 accumulate_gradient = 1
-patience = 1600
-max_epochs = 0
-max_steps = 40000
-eval_frequency = 250
+patience = 20000
+max_epochs = -1
+max_steps = 80000
+eval_frequency = 1000
 frozen_components = []
 annotating_components = []
 before_to_disk = null
@@ -140,8 +142,8 @@ eps = 0.00000001
 learn_rate = 0.001
 
 [training.score_weights]
-tag_acc = 0.5
-ents_f = 0.5
+tag_acc = 0.4
+ents_f = 0.6
 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null

en_docusco_spacy-any-py3-none-any.whl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:8d5b44d15d93b41b27c0650f71553ece8709eb2717910922fb129809e9423d54
-size 7501545
+oid sha256:3d9d5411d259b75eabdaf033355056150b158d0d9122a527f5a62b450224f658
+size 8600882

meta.json

@@ -1,14 +1,14 @@
 {
   "lang":"en",
   "name":"docusco_spacy",
-  "version":"1.3",
+  "version":"1.4",
   "description":"English pipeline for part-of-speech and rhetorical tagging.",
   "author":"David Brown",
   "email":"[email protected]",
   "url":"https://docuscope.github.io",
   "license":"MIT",
-  "spacy_version":">=3.5.0,<3.6.0",
-  "spacy_git_version":"Unknown",
+  "spacy_version":">=3.7.4,<3.8.0",
+  "spacy_git_version":"bff8725f4",
   "vectors":{
     "width":0,
     "vectors":0,
@@ -96,6 +96,8 @@
       "JK",
       "MC",
       "MC1",
+      "MC121",
+      "MC122",
       "MC2",
       "MC221",
       "MC222",
@@ -133,6 +135,7 @@
       "NNO2",
       "NNT1",
       "NNT131",
+      "NNT132",
       "NNT133",
       "NNT2",
       "NNU",
@@ -195,6 +198,9 @@
       "RG",
       "RG21",
       "RG22",
+      "RG31",
+      "RG32",
+      "RG33",
       "RG41",
       "RG42",
       "RG43",
@@ -346,195 +352,195 @@
 
   ],
   "performance":{
-    "tag_acc":0.9698599662,
-    "ents_f":0.7971954516,
-    "ents_p":0.798987704,
-    "ents_r":0.7954112218,
+    "tag_acc":0.9732027902,
+    "ents_f":0.8040831626,
+    "ents_p":0.7999501539,
+    "ents_r":0.8082591001,
     "ents_per_type":{
-      "Contingent":{
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-        "r":0.782463929,
-        "f":0.8002270148
-      },
-      "InformationExposition":{
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-        "r":0.857557341,
-        "f":0.8536808374
+      "Reasoning":{
+        "p":0.854002833,
+        "r":0.8306135538,
+        "f":0.8421458246
       },
       "AcademicTerms":{
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+        "p":0.8252578101,
+        "r":0.8253579445,
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-      "ForceStressed":{
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-        "r":0.7950043821,
-        "f":0.7993038804
+      "InformationReportVerbs":{
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+        "r":0.8011000156,
+        "f":0.8019289717
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-      "Character":{
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-        "r":0.8578615428,
-        "f":0.8544137022
+      "Future":{
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+        "r":0.7932351845,
+        "f":0.7791149957
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       "Negative":{
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       "Uncertainty":{
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       "CitationAuthority":{
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