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spacy
/
sv_core_news_md

Token Classification
spaCy
Swedish
Eval Results
Model card Files Community
1
adrianeboyd commited on
Commit
69e1f38
·
1 Parent(s): ecb4e74

Update spaCy pipeline

Browse files
Files changed (14) hide show
  1. README.md +27 -27
  2. accuracy.json +183 -188
  3. config.cfg +5 -4
  4. lemmatizer/model +1 -1
  5. meta.json +186 -191
  6. morphologizer/model +1 -1
  7. ner/model +2 -2
  8. parser/model +1 -1
  9. senter/model +1 -1
  10. sv_core_news_md-any-py3-none-any.whl +2 -2
  11. tagger/model +1 -1
  12. tok2vec/model +2 -2
  13. tokenizer +1 -1
  14. 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: 0.8477074236
18
  - name: NER Recall
19
  type: recall
20
- value: 0.7557177616
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.7990738359
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9484536082
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
- value: 0.961008472
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.9558027968
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
- value: 0.9550882923
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
- value: 0.8306629678
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.7853705486
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9326829268
73
  ---
74
  ### Details: https://spacy.io/models/sv#sv_core_news_md
75
 
@@ -78,8 +78,8 @@ Swedish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `sv_core_news_md` |
81
- | **Version** | `3.4.0` |
82
- | **spaCy** | `>=3.4.0,<3.5.0` |
83
  | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | floret (50000, 300) |
@@ -110,18 +110,18 @@ Swedish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
110
  | `TOKEN_P` | 99.95 |
111
  | `TOKEN_R` | 99.96 |
112
  | `TOKEN_F` | 99.95 |
113
- | `TAG_ACC` | 94.85 |
114
- | `POS_ACC` | 96.10 |
115
- | `MORPH_ACC` | 95.58 |
116
- | `MORPH_MICRO_P` | 97.47 |
117
- | `MORPH_MICRO_R` | 97.26 |
118
- | `MORPH_MICRO_F` | 97.36 |
119
- | `SENTS_P` | 91.75 |
120
- | `SENTS_R` | 94.84 |
121
- | `SENTS_F` | 93.27 |
122
- | `DEP_UAS` | 83.07 |
123
- | `DEP_LAS` | 78.54 |
124
- | `LEMMA_ACC` | 95.51 |
125
- | `ENTS_P` | 84.77 |
126
- | `ENTS_R` | 75.57 |
127
- | `ENTS_F` | 79.91 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8516666667
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.7459854015
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.7953307393
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9482494641
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.9606001837
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.9541696438
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
+ value: 0.9557007247
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
+ value: 0.8339750849
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
+ value: 0.7849377123
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
+ value: 0.9126213592
73
  ---
74
  ### Details: https://spacy.io/models/sv#sv_core_news_md
75
 
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `sv_core_news_md` |
81
+ | **Version** | `3.5.0` |
82
+ | **spaCy** | `>=3.5.0,<3.6.0` |
83
  | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | floret (50000, 300) |
 
110
  | `TOKEN_P` | 99.95 |
111
  | `TOKEN_R` | 99.96 |
112
  | `TOKEN_F` | 99.95 |
113
+ | `TAG_ACC` | 94.82 |
114
+ | `POS_ACC` | 96.06 |
115
+ | `MORPH_ACC` | 95.42 |
116
+ | `MORPH_MICRO_P` | 97.28 |
117
+ | `MORPH_MICRO_R` | 97.17 |
118
+ | `MORPH_MICRO_F` | 97.23 |
119
+ | `SENTS_P` | 89.35 |
120
+ | `SENTS_R` | 93.25 |
121
+ | `SENTS_F` | 91.26 |
122
+ | `DEP_UAS` | 83.40 |
123
+ | `DEP_LAS` | 78.49 |
124
+ | `LEMMA_ACC` | 95.57 |
125
+ | `ENTS_P` | 85.17 |
126
+ | `ENTS_R` | 74.60 |
127
+ | `ENTS_F` | 79.53 |
accuracy.json CHANGED
@@ -1,69 +1,69 @@
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  {
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- "token_acc": 0.9999489666,
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  "token_p": 0.9994896918,
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  "token_r": 0.9995917117,
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  "token_f": 0.9995406992,
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- "tag_acc": 0.9484536082,
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- "pos_acc": 0.961008472,
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- "morph_acc": 0.9558027968,
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- "morph_micro_p": 0.9747321429,
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- "morph_micro_r": 0.9725612472,
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- "morph_micro_f": 0.9736454849,
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  "morph_per_feat": {
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  "Case": {
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- "p": 0.9841224837,
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  },
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  "Definite": {
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  "p": 0.99,
@@ -71,201 +71,196 @@
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  "f": 0.9801980198
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  },
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  "NumType": {
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- "p": 0.9661016949,
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  }
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  },
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- "dep_uas": 0.8306629678,
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  "csubj:pass": {
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  "p": 0.0,
@@ -288,51 +283,51 @@
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  "f": 0.0
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  }
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  },
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- "lemma_acc": 0.9550882923,
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  }
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  },
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- "speed": 9742.3571021997
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  }
 
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  "token_p": 0.9994896918,
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  "token_r": 0.9995917117,
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+ "tag_acc": 0.9482494641,
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+ "morph_acc": 0.9541696438,
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  "morph_per_feat": {
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  "Definite": {
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  "Poss": {
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  },
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  "Polarity": {
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