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spacy
/
ru_core_news_lg

Token Classification
spaCy
Russian
Eval Results
Model card Files Community
adrianeboyd commited on
Commit
7381706
•
1 Parent(s): ed3a84e

Update spaCy pipeline

Browse files
Files changed (13) hide show
  1. README.md +26 -26
  2. accuracy.json +172 -172
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +6 -5
  5. meta.json +176 -176
  6. morphologizer/model +1 -1
  7. ner/model +2 -2
  8. parser/model +1 -1
  9. ru_core_news_lg-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: 0.9520121233
18
  - name: NER Recall
19
  type: recall
20
- value: 0.9516916344
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.9518518519
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9889933439
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
- value: 0.9889933439
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.9747833538
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: 0.9630346126
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.9520673253
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9987634357
73
  ---
74
  ### Details: https://spacy.io/models/ru#ru_core_news_lg
75
 
@@ -78,8 +78,8 @@ Russian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `ru_core_news_lg` |
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** | 500002 keys, 500002 unique vectors (300 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` | 98.90 |
113
- | `MORPH_ACC` | 97.48 |
114
  | `MORPH_MICRO_P` | 98.97 |
115
- | `MORPH_MICRO_R` | 98.33 |
116
- | `MORPH_MICRO_F` | 98.65 |
117
  | `SENTS_P` | 99.87 |
118
- | `SENTS_R` | 99.89 |
119
- | `SENTS_F` | 99.88 |
120
- | `DEP_UAS` | 96.30 |
121
- | `DEP_LAS` | 95.21 |
122
- | `TAG_ACC` | 98.90 |
123
  | `LEMMA_ACC` | 0.00 |
124
- | `ENTS_P` | 95.20 |
125
- | `ENTS_R` | 95.17 |
126
- | `ENTS_F` | 95.19 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.9524209818
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.9535431745
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.9529817478
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.989280677
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.989280677
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.9749177029
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: 0.962198055
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
+ value: 0.9511948091
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
+ value: 0.9985729236
73
  ---
74
  ### Details: https://spacy.io/models/ru#ru_core_news_lg
75
 
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `ru_core_news_lg` |
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** | 500002 keys, 500002 unique vectors (300 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` | 98.93 |
113
+ | `MORPH_ACC` | 97.49 |
114
  | `MORPH_MICRO_P` | 98.97 |
115
+ | `MORPH_MICRO_R` | 98.30 |
116
+ | `MORPH_MICRO_F` | 98.64 |
117
  | `SENTS_P` | 99.87 |
118
+ | `SENTS_R` | 99.85 |
119
+ | `SENTS_F` | 99.86 |
120
+ | `DEP_UAS` | 96.22 |
121
+ | `DEP_LAS` | 95.12 |
122
+ | `TAG_ACC` | 98.93 |
123
  | `LEMMA_ACC` | 0.00 |
124
+ | `ENTS_P` | 95.24 |
125
+ | `ENTS_R` | 95.35 |
126
+ | `ENTS_F` | 95.30 |
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": 0.9889933439,
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- "morph_acc": 0.9747833538,
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- "morph_micro_p": 0.9896991632,
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- "morph_micro_r": 0.9832782178,
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- "morph_micro_f": 0.9864782422,
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  "morph_per_feat": {
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  "Animacy": {
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- "p": 0.9896970764,
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- "r": 0.980088367,
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- "f": 0.9848692858
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  },
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  "Case": {
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- "p": 0.9789719626,
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- "r": 0.9722662264,
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- "f": 0.9756075718
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  },
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  "Gender": {
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- "p": 0.9880955025,
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- "r": 0.9819453948,
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- "f": 0.9850108489
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  },
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  "Number": {
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- "p": 0.9960197873,
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- "r": 0.9897728557,
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- "f": 0.9928864957
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  },
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  "Degree": {
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- "p": 0.9885778967,
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- "r": 0.9863449692,
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- "f": 0.9874601706
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  },
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  "Aspect": {
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- "p": 0.9905277402,
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- "r": 0.9869662921,
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- "f": 0.9887438091
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  },
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  "Mood": {
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- "p": 0.9986340494,
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- "r": 0.9970245475,
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- "f": 0.9978286494
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  },
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  "Tense": {
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- "p": 0.9932989691,
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- "r": 0.9896261298,
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- "f": 0.991459148
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  },
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  "VerbForm": {
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- "p": 0.9952187641,
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- "r": 0.9916404494,
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- "f": 0.9934263845
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  },
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  "Voice": {
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- "p": 0.9910690122,
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- "r": 0.987505618,
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- "f": 0.9892841063
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  },
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  "StyleVariant": {
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- "p": 0.9931170108,
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- "r": 0.9960552268,
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- "f": 0.9945839488
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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": 0.9997729852,
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- "r": 0.9934581547,
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- "f": 0.9966055669
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  },
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  "Foreign": {
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- "p": 0.9700483092,
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- "r": 0.8685121107,
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- "f": 0.9164764948
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  },
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  "Hyph": {
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  "p": 0.0,
@@ -85,186 +85,186 @@
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  "f": 0.0
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  }
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  },
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- "sents_p": 0.9986684421,
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- "sents_r": 0.9988584475,
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- "sents_f": 0.9987634357,
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- "dep_uas": 0.9630346126,
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- "dep_las": 0.9520673253,
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  "dep_las_per_type": {
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  "case": {
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- "p": 0.9938650307,
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- "r": 0.9893826928,
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- "f": 0.9916187965
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  },
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  "parataxis": {
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  },
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  "nmod": {
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  "advmod": {
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  "obl": {
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  "nsubj": {
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- "p": 0.9899066844,
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- "r": 0.9889649924,
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  "xcomp": {
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- "p": 0.9630188679,
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  "conj": {
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  "fixed": {
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  "aux:pass": {
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  "nsubj:pass": {
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- "p": 0.9588235294,
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  "acl:relcl": {
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- "f": 0.814968815
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  "orphan": {
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- "p": 0.78125,
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  "r": 0.6944444444,
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- "f": 0.7352941176
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  },
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  "discourse": {
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- "p": 0.75,
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  },
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  "csubj": {
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  "expl": {
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  "compound": {
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  "p": 1.0,
@@ -272,9 +272,9 @@
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  "f": 0.4615384615
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  },
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  "csubj:pass": {
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  "r": 0.8181818182,
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  "nummod:entity": {
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  "p": 1.0,
@@ -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": 0.9889933439,
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- "lemma_acc": 2.15292e-05,
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- "ents_p": 0.9520121233,
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- "ents_f": 0.9518518519,
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  "ents_per_type": {
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  "PER": {
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  "LOC": {
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  "ORG": {
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  }
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  },
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- "speed": 3393.7960657989
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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": 0.989280677,
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+ "morph_acc": 0.9749177029,
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+ "morph_micro_p": 0.9897327316,
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+ "morph_micro_r": 0.9829975554,
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+ "morph_micro_f": 0.9863536461,
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  "morph_per_feat": {
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  "Animacy": {
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+ "p": 0.9905472053,
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+ "r": 0.9808150689,
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+ "f": 0.9856571145
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  },
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  "Case": {
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+ "p": 0.9776694449,
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+ "r": 0.9709944443,
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+ "f": 0.9743205122
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  },
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  "Gender": {
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+ "p": 0.9884699976,
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+ "r": 0.982055753,
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+ "f": 0.9852524358
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  },
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  "Number": {
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+ "p": 0.9958673769,
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+ "r": 0.9894338343,
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+ "f": 0.9926401814
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  },
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  "Degree": {
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+ "p": 0.9884927566,
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+ "r": 0.9877823409,
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+ "f": 0.988137421
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  },
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  "Aspect": {
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+ "p": 0.9913263462,
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+ "r": 0.986247191,
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+ "f": 0.988780246
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  },
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  "Mood": {
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+ "p": 0.9990060877,
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+ "f": 0.9979522184
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  },
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  "Tense": {
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+ "p": 0.99442264,
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+ "r": 0.9889071487,
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  },
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  "VerbForm": {
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+ "p": 0.9958438742,
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  },
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  "Voice": {
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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": 0.9995459705,
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+ "r": 0.9932325739,
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+ "f": 0.9963792713
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  },
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  "Foreign": {
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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 = true
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 = true
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 = true
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 = true
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_lg",
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":300,
14
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@@ -953,70 +953,70 @@
953
  "senter"
954
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955
  "performance":{
956
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1026
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