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spacy
/
ru_core_news_sm

Token Classification
spaCy
Russian
Eval Results
Model card Files Community
adrianeboyd commited on
Commit
5fcae88
•
1 Parent(s): aaa3c94

Update spaCy pipeline

Browse files
Files changed (13) hide show
  1. README.md +28 -28
  2. accuracy.json +167 -167
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +6 -5
  5. meta.json +171 -171
  6. morphologizer/model +1 -1
  7. ner/model +2 -2
  8. parser/model +1 -1
  9. ru_core_news_sm-any-py3-none-any.whl +2 -2
  10. senter/model +1 -1
  11. tok2vec/model +2 -2
  12. tokenizer +0 -0
  13. vocab/strings.json +2 -2
README.md CHANGED
@@ -14,62 +14,62 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.943812709
18
  - name: NER Recall
19
  type: recall
20
- value: 0.9500084161
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.9469004278
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9880060539
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
- value: 0.9880060539
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.9711357536
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
- value: 2.15292e-05
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
- value: 0.9592758407
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.9473147719
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9986681887
73
  ---
74
  ### Details: https://spacy.io/models/ru#ru_core_news_sm
75
 
@@ -78,8 +78,8 @@ Russian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `ru_core_news_sm` |
81
- | **Version** | `3.4.0` |
82
- | **spaCy** | `>=3.4.0,<3.5.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
85
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -105,22 +105,22 @@ Russian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
105
 
106
  | Type | Score |
107
  | --- | --- |
108
- | `TOKEN_ACC` | 99.84 |
109
  | `TOKEN_P` | 97.28 |
110
- | `TOKEN_R` | 98.32 |
111
  | `TOKEN_F` | 97.79 |
112
- | `POS_ACC` | 98.80 |
113
- | `MORPH_ACC` | 97.11 |
114
- | `MORPH_MICRO_P` | 98.75 |
115
- | `MORPH_MICRO_R` | 98.06 |
116
- | `MORPH_MICRO_F` | 98.40 |
117
- | `SENTS_P` | 99.87 |
118
- | `SENTS_R` | 99.87 |
119
- | `SENTS_F` | 99.87 |
120
- | `DEP_UAS` | 95.93 |
121
- | `DEP_LAS` | 94.73 |
122
- | `TAG_ACC` | 98.80 |
123
  | `LEMMA_ACC` | 0.00 |
124
- | `ENTS_P` | 94.38 |
125
- | `ENTS_R` | 95.00 |
126
- | `ENTS_F` | 94.69 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.9487739335
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.9508500252
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.9498108449
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.987696514
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.987696514
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.9702812464
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
+ value: 2.15295e-05
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
+ value: 0.9586955101
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
+ value: 0.946180635
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
+ value: 0.9988584475
73
  ---
74
  ### Details: https://spacy.io/models/ru#ru_core_news_sm
75
 
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `ru_core_news_sm` |
81
+ | **Version** | `3.5.0` |
82
+ | **spaCy** | `>=3.5.0,<3.6.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
85
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
105
 
106
  | Type | Score |
107
  | --- | --- |
108
+ | `TOKEN_ACC` | 99.68 |
109
  | `TOKEN_P` | 97.28 |
110
+ | `TOKEN_R` | 98.31 |
111
  | `TOKEN_F` | 97.79 |
112
+ | `POS_ACC` | 98.77 |
113
+ | `MORPH_ACC` | 97.03 |
114
+ | `MORPH_MICRO_P` | 98.68 |
115
+ | `MORPH_MICRO_R` | 97.98 |
116
+ | `MORPH_MICRO_F` | 98.33 |
117
+ | `SENTS_P` | 99.89 |
118
+ | `SENTS_R` | 99.89 |
119
+ | `SENTS_F` | 99.89 |
120
+ | `DEP_UAS` | 95.87 |
121
+ | `DEP_LAS` | 94.62 |
122
+ | `TAG_ACC` | 98.77 |
123
  | `LEMMA_ACC` | 0.00 |
124
+ | `ENTS_P` | 94.88 |
125
+ | `ENTS_R` | 95.09 |
126
+ | `ENTS_F` | 94.98 |
accuracy.json CHANGED
@@ -1,68 +1,68 @@
1
  {
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- "token_acc": 0.9984047451,
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- "token_p": 0.9727635194,
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- "token_r": 0.9831678569,
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- "token_f": 0.9779380158,
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- "pos_acc": 0.9880060539,
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- "morph_acc": 0.9711357536,
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- "morph_micro_p": 0.9875020482,
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- "morph_micro_r": 0.9805651482,
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- "morph_micro_f": 0.9840213729,
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  "morph_per_feat": {
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  "Animacy": {
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- "p": 0.9879047647,
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- "r": 0.9781698738,
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- "f": 0.9830132184
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  },
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  "Case": {
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- "p": 0.9752914486,
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- "r": 0.9687632477,
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- "f": 0.9720163872
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  },
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  "Gender": {
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- "r": 0.9804665946,
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- "f": 0.9836581045
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  },
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  "Number": {
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- "p": 0.9951099318,
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- "r": 0.9888499642,
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- "f": 0.991970072
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  },
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  "Degree": {
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- "p": 0.983003993,
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- "r": 0.9857289528,
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- "f": 0.9843645871
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  },
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  "Aspect": {
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- "p": 0.9826197158,
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- "r": 0.9757303371,
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- "f": 0.9791629082
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  },
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  "Mood": {
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- "p": 0.9988819876,
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- "r": 0.9969005703,
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- "f": 0.9978902954
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  },
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  "Tense": {
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- "p": 0.9901676671,
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- "r": 0.982641742,
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- "f": 0.9863903495
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  },
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  "VerbForm": {
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- "p": 0.9945686612,
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- "r": 0.9875955056,
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- "f": 0.9910698178
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  },
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  "Voice": {
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- "p": 0.9888657554,
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- "r": 0.9819325843,
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- "f": 0.9853869746
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  },
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  "StyleVariant": {
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- "p": 0.986287953,
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- "r": 0.9930966469,
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- "f": 0.9896805897
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  },
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  "Polarity": {
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  "p": 1.0,
@@ -70,14 +70,14 @@
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  "f": 1.0
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  },
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  "Person": {
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- "p": 0.9997725722,
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- "r": 0.9916535078,
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- "f": 0.9956964892
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  },
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  "Foreign": {
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- "p": 0.970703125,
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- "r": 0.8598615917,
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- "f": 0.9119266055
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  },
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  "Hyph": {
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  "p": 0.0,
@@ -85,111 +85,111 @@
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  "f": 0.0
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  }
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  },
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- "sents_p": 0.9986681887,
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- "sents_r": 0.9986681887,
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- "sents_f": 0.9986681887,
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- "dep_uas": 0.9592758407,
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- "dep_las": 0.9473147719,
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  "dep_las_per_type": {
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  "case": {
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- "p": 0.9918071381,
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- "r": 0.9895706098,
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- "f": 0.9906876117
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  },
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  "parataxis": {
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  "nmod": {
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  "advmod": {
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  "nsubj": {
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- "p": 0.9887640449,
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  "xcomp": {
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- "p": 0.9502262443,
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  "ccomp": {
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  "nummod:gov": {
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  "nummod": {
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  "appos": {
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  "aux": {
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@@ -197,79 +197,79 @@
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  "f": 0.9767981439
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  },
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  "flat:name": {
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  "iobj": {
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  "acl": {
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  "obl:agent": {
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  "r": 0.7236842105,
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  "advcl": {
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  "cop": {
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  "flat:foreign": {
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  "aux:pass": {
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  "nsubj:pass": {
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- "p": 0.9460641399,
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  "acl:relcl": {
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  "orphan": {
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- "p": 0.8285714286,
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  },
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  "discourse": {
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  },
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  "csubj": {
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  "expl": {
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  "p": 0.9,
@@ -287,27 +287,27 @@
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  "f": 0.0
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  }
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  },
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- "tag_acc": 0.9880060539,
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- "lemma_acc": 2.15292e-05,
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- "ents_p": 0.943812709,
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  "ents_per_type": {
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  "LOC": {
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  "ORG": {
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  }
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  },
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- "speed": 3573.1911564665
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  }
 
1
  {
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+ "token_acc": 0.9968038482,
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+ "token_p": 0.9727525387,
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+ "token_r": 0.9831462495,
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+ "token_f": 0.9779217779,
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+ "pos_acc": 0.987696514,
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+ "morph_acc": 0.9702812464,
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+ "morph_micro_p": 0.9868284669,
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+ "morph_micro_r": 0.9797638369,
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+ "morph_micro_f": 0.9832834627,
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  "morph_per_feat": {
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  "Animacy": {
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+ "p": 0.9862354357,
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+ "r": 0.9768036742,
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+ "f": 0.9814968967
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  },
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  "Case": {
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+ "r": 0.9683393204,
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+ "f": 0.9716127877
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  },
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  "Gender": {
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+ "f": 0.9834054754
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  },
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  "Number": {
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+ "p": 0.9948064748,
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  },
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  "Degree": {
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+ "p": 0.9814985178,
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+ "r": 0.9858316222,
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+ "f": 0.9836602981
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  },
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  "Aspect": {
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+ "p": 0.9809575626,
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+ "r": 0.9724044944,
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+ "f": 0.9766623031
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  },
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  "Mood": {
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+ "p": 0.9982615174,
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+ "r": 0.9966526159,
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+ "f": 0.9974564179
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  },
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  "Tense": {
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+ "p": 0.9893164609,
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+ "r": 0.979663106,
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  },
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  "VerbForm": {
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+ "p": 0.994377947,
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  },
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  "Voice": {
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+ "p": 0.9889372506,
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  },
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  "StyleVariant": {
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  },
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  "Polarity": {
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  "p": 1.0,
 
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  "f": 1.0
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  },
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  "Person": {
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+ "p": 0.9988641527,
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+ "r": 0.9918790887,
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  },
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  "Foreign": {
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+ "p": 0.9661181026,
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+ "f": 0.9118318867
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  },
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  "Hyph": {
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  "p": 0.0,
 
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attribute_ruler/patterns CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
 
config.cfg CHANGED
@@ -27,7 +27,7 @@ validate = false
27
 
28
  [components.lemmatizer]
29
  factory = "lemmatizer"
30
- mode = "pymorphy2"
31
  model = null
32
  overwrite = false
33
  scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
@@ -70,8 +70,8 @@ nO = null
70
  [components.ner.model.tok2vec.embed]
71
  @architectures = "spacy.MultiHashEmbed.v2"
72
  width = 96
73
- attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
74
- rows = [5000,1000,2500,2500,50]
75
  include_static_vectors = false
76
 
77
  [components.ner.model.tok2vec.encode]
@@ -139,8 +139,8 @@ factory = "tok2vec"
139
  [components.tok2vec.model.embed]
140
  @architectures = "spacy.MultiHashEmbed.v2"
141
  width = ${components.tok2vec.model.encode:width}
142
- attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
143
- rows = [5000,1000,2500,2500,50]
144
  include_static_vectors = false
145
 
146
  [components.tok2vec.model.encode]
@@ -182,6 +182,7 @@ eval_frequency = 1000
182
  frozen_components = []
183
  before_to_disk = null
184
  annotating_components = []
 
185
 
186
  [training.batcher]
187
  @batchers = "spacy.batch_by_words.v1"
 
27
 
28
  [components.lemmatizer]
29
  factory = "lemmatizer"
30
+ mode = "pymorphy3"
31
  model = null
32
  overwrite = false
33
  scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
 
70
  [components.ner.model.tok2vec.embed]
71
  @architectures = "spacy.MultiHashEmbed.v2"
72
  width = 96
73
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
74
+ rows = [5000,1000,2500,2500]
75
  include_static_vectors = false
76
 
77
  [components.ner.model.tok2vec.encode]
 
139
  [components.tok2vec.model.embed]
140
  @architectures = "spacy.MultiHashEmbed.v2"
141
  width = ${components.tok2vec.model.encode:width}
142
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
143
+ rows = [5000,1000,2500,2500,50,50]
144
  include_static_vectors = false
145
 
146
  [components.tok2vec.model.encode]
 
182
  frozen_components = []
183
  before_to_disk = null
184
  annotating_components = []
185
+ before_update = null
186
 
187
  [training.batcher]
188
  @batchers = "spacy.batch_by_words.v1"
meta.json CHANGED
@@ -1,14 +1,14 @@
1
  {
2
  "lang":"ru",
3
  "name":"core_news_sm",
4
- "version":"3.4.0",
5
  "description":"Russian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.",
6
  "author":"Explosion",
7
  "email":"contact@explosion.ai",
8
  "url":"https://explosion.ai",
9
  "license":"MIT",
10
- "spacy_version":">=3.4.0,<3.5.0",
11
- "spacy_git_version":"dd038b536",
12
  "vectors":{
13
  "width":0,
14
  "vectors":0,
@@ -953,70 +953,70 @@
953
  "senter"
954
  ],
955
  "performance":{
956
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1021
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1025
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1026
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1031
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1036
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1037
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1040
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1041
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1042
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1123
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@@ -1241,29 +1241,29 @@
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