Update spaCy pipeline

README.md

@@ -14,47 +14,41 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8463095057
+      value: 0.8508041869
     - name: NER Recall
       type: recall
-      value: 0.8377904647
+      value: 0.8344851763
     - name: NER F Score
       type: f_score
-      value: 0.8420284384
+      value: 0.8425656714
   - task:
-      name: POS
+      name: TAG
       type: token-classification
     metrics:
-    - name: POS Accuracy
+    - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9725066923
+      value: 0.9726545475
   - task:
-      name: SENTER
+      name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
-    - name: SENTER Precision
-      type: precision
-      value: 0.9205049471
-    - name: SENTER Recall
-      type: recall
-      value: 0.8899003892
-    - name: SENTER F Score
+    - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.904943986
+      value: 0.9180803841
   - task:
-      name: UNLABELED_DEPENDENCIES
+      name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
-    - name: Unlabeled Dependencies Accuracy
-      type: accuracy
-      value: 0.9166876131
+    - name: Labeled Attachment Score (LAS)
+      type: f_score
+      value: 0.8996666011
   - task:
-      name: LABELED_DEPENDENCIES
+      name: SENTS
       type: token-classification
     metrics:
-    - name: Labeled Dependencies Accuracy
-      type: accuracy
-      value: 0.9166876131
+    - name: Sentences F-Score
+      type: f_score
+      value: 0.9060200669
 ---
 ### Details: https://spacy.io/models/en#en_core_web_sm
 
@@ -63,8 +57,8 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
 | Feature | Description |
 | --- | --- |
 | **Name** | `en_core_web_sm` |
-| **Version** | `3.2.0` |
-| **spaCy** | `>=3.2.0,<3.3.0` |
+| **Version** | `3.3.0` |
+| **spaCy** | `>=3.3.0.dev0,<3.4.0` |
 | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -76,13 +70,12 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
 
 <details>
 
-<summary>View label scheme (114 labels for 4 components)</summary>
+<summary>View label scheme (112 labels for 3 components)</summary>
 
 | Component | Labels |
 | --- | --- |
 | **`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`, ```` |
 | **`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` |
-| **`senter`** | `I`, `S` |
 | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
 
 </details>
@@ -95,12 +88,12 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
 | `TOKEN_P` | 99.57 |
 | `TOKEN_R` | 99.58 |
 | `TOKEN_F` | 99.57 |
-| `TAG_ACC` | 97.25 |
-| `SENTS_P` | 92.05 |
-| `SENTS_R` | 88.99 |
-| `SENTS_F` | 90.49 |
-| `DEP_UAS` | 91.67 |
-| `DEP_LAS` | 89.80 |
-| `ENTS_P` | 84.63 |
-| `ENTS_R` | 83.78 |
-| `ENTS_F` | 84.20 |
+| `TAG_ACC` | 97.27 |
+| `SENTS_P` | 91.89 |
+| `SENTS_R` | 89.35 |
+| `SENTS_F` | 90.60 |
+| `DEP_UAS` | 91.81 |
+| `DEP_LAS` | 89.97 |
+| `ENTS_P` | 85.08 |
+| `ENTS_R` | 83.45 |
+| `ENTS_F` | 84.26 |

accuracy.json

@@ -1,330 +1,330 @@
 {
-  "token_acc": 0.9993053983,
-  "token_p": 0.9956742163,
-  "token_r": 0.9957505887,
-  "token_f": 0.9957124011,
-  "tag_acc": 0.9725066923,
-  "sents_p": 0.9205049471,
-  "sents_r": 0.8899003892,
-  "sents_f": 0.904943986,
-  "dep_uas": 0.9166876131,
-  "dep_las": 0.8979960057,
+  "token_acc": 0.9993092439,
+  "token_p": 0.9956819193,
+  "token_r": 0.9957659295,
+  "token_f": 0.9957239226,
+  "tag_acc": 0.9726545475,
+  "sents_p": 0.9188657486,
+  "sents_r": 0.8935285969,
+  "sents_f": 0.9060200669,
+  "dep_uas": 0.9180803841,
+  "dep_las": 0.8996666011,
   "dep_las_per_type": {
     "prep": {
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-      "r": 0.8605577689,
-      "f": 0.8559944141
+      "p": 0.8545638793,
+      "r": 0.8639347372,
+      "f": 0.8592237589
     },
     "det": {
-      "p": 0.9776402069,
+      "p": 0.9767252604,
       "r": 0.9787164642,
-      "f": 0.9781780395
+      "f": 0.9777198485
     },
     "pobj": {
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-      "r": 0.9679560181,
-      "f": 0.9635667097
+      "p": 0.9624306803,
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+      "f": 0.9650878189
     },
     "nsubj": {
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-      "r": 0.9416429354,
-      "f": 0.9488764293
+      "p": 0.9570163789,
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+      "f": 0.9520642959
     },
     "aux": {
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-      "f": 0.9809307908
+      "p": 0.9800017776,
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+      "f": 0.980786337
     },
     "advmod": {
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-      "f": 0.8553846154
+      "p": 0.8575166709,
+      "r": 0.8547030119,
+      "f": 0.8561075296
     },
     "relcl": {
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-      "r": 0.7772133527,
-      "f": 0.7766497462
+      "p": 0.7630824373,
+      "r": 0.7724963716,
+      "f": 0.7677605481
     },
     "root": {
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     "xcomp": {
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     "amod": {
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     "compound": {
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     "poss": {
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     },
     "ccomp": {
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-      "f": 0.7988338192
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     "attr": {
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     "case": {
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     },
     "mark": {
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     "advcl": {
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     },
     "cc": {
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     "nummod": {
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     "prt": {
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     "expl": {
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     "acl": {
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     "agent": {
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     "oprd": {
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     "meta": {
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   },
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   "ents_per_type": {
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     "GPE": {
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     "ORDINAL": {
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     "FAC": {
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     },
     "CARDINAL": {
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     },
     "PERSON": {
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     },
     "NORP": {
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     },
     "TIME": {
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     },
     "QUANTITY": {
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     },
     "EVENT": {
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-      "f": 0.3849056604
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     },
     "WORK_OF_ART": {
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-    },
-    "MONEY": {
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-      "f": 0.9074626866
+      "p": 0.4926470588,
+      "r": 0.3453608247,
+      "f": 0.4060606061
     },
     "LAW": {
-      "p": 0.5102040816,
-      "r": 0.390625,
-      "f": 0.4424778761
+      "p": 0.58,
+      "r": 0.453125,
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     },
-    "PERCENT": {
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-      "r": 0.8820826953,
-      "f": 0.9021143305
+    "MONEY": {
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+      "r": 0.9079102715,
+      "f": 0.9138443256
     },
-    "PRODUCT": {
-      "p": 0.5185185185,
-      "r": 0.1990521327,
-      "f": 0.2876712329
+    "PERCENT": {
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+      "r": 0.8774885145,
+      "f": 0.8960125098
     },
     "LANGUAGE": {
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+    "PRODUCT": {
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+      "f": 0.3411371237
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   },
-  "speed": 8030.19594793
+  "speed": 9738.3022066337
 }

config.cfg

@@ -55,7 +55,7 @@ nO = null
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,2500,2500,2500,100]
+rows = [5000,1000,2500,2500,50]
 include_static_vectors = false
 
 [components.ner.model.tok2vec.encode]
@@ -93,8 +93,9 @@ overwrite = false
 scorer = {"@scorers":"spacy.senter_scorer.v1"}
 
 [components.senter.model]
-@architectures = "spacy.Tagger.v1"
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 
 [components.senter.model.tok2vec]
 @architectures = "spacy.Tok2Vec.v2"
@@ -115,12 +116,14 @@ maxout_pieces = 2
 
 [components.tagger]
 factory = "tagger"
+neg_prefix = "!"
 overwrite = false
 scorer = {"@scorers":"spacy.tagger_scorer.v1"}
 
 [components.tagger.model]
-@architectures = "spacy.Tagger.v1"
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 
 [components.tagger.model.tok2vec]
 @architectures = "spacy.Tok2VecListener.v1"
@@ -137,7 +140,7 @@ factory = "tok2vec"
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode:width}
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,2500,2500,2500,100]
+rows = [5000,1000,2500,2500,50]
 include_static_vectors = false
 
 [components.tok2vec.model.encode]
@@ -174,7 +177,7 @@ dropout = 0.1
 accumulate_gradient = 1
 patience = 5000
 max_epochs = 0
-max_steps = 0
+max_steps = 100000
 eval_frequency = 1000
 frozen_components = []
 before_to_disk = null

en_core_web_sm-any-py3-none-any.whl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5e02939fb7fbae6dbcc9c5a1355f5e4e02939b649a1f0846ee844ac1d479bbeb
-size 13900196
+oid sha256:84d7d8059bfbf53c09b39139782f76cd6ac7064851e7799dcc685c06ebf5fd4f
+size 12799907

meta.json

@@ -1,14 +1,14 @@
 {
   "lang":"en",
   "name":"core_web_sm",
-  "version":"3.2.0",
+  "version":"3.3.0",
   "description":"English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.",
   "author":"Explosion",
   "email":"contact@explosion.ai",
   "url":"https://explosion.ai",
   "license":"MIT",
-  "spacy_version":">=3.2.0,<3.3.0",
-  "spacy_git_version":"bb26550e2",
+  "spacy_version":">=3.3.0.dev0,<3.4.0",
+  "spacy_git_version":"849bef2de",
   "vectors":{
     "width":0,
     "vectors":0,
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       "relcl",
       "xcomp"
     ],
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-      "S"
-    ],
     "attribute_ruler":[
 
     ],
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     "senter"
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ner/model

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parser/model

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parser/moves

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