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da_core_news_md

Token Classification spaCy Danish Eval Results
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adrianeboyd commited on
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5c06770
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1 Parent(s): 2230db5

Update spaCy pipeline

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Files changed (14) hide show
  1. README.md +28 -28
  2. accuracy.json +157 -157
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +5 -4
  5. da_core_news_md-any-py3-none-any.whl +2 -2
  6. lemmatizer/model +1 -1
  7. meta.json +160 -160
  8. morphologizer/model +1 -1
  9. ner/model +2 -2
  10. parser/model +1 -1
  11. senter/model +1 -1
  12. tok2vec/model +2 -2
  13. tokenizer +0 -0
  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: 0.8063829787
18
  - name: NER Recall
19
  type: recall
20
- value: 0.7895833333
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.7978947368
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9618401937
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
- value: 0.9618401937
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.948377724
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
- value: 0.9497336562
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
- value: 0.8215642458
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.7802234637
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9103942652
73
  ---
74
  ### Details: https://spacy.io/models/da#da_core_news_md
75
 
@@ -78,8 +78,8 @@ Danish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, l
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `da_core_news_md` |
81
- | **Version** | `3.4.0` |
82
- | **spaCy** | `>=3.4.0,<3.5.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
@@ -105,22 +105,22 @@ Danish pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, l
105
 
106
  | Type | Score |
107
  | --- | --- |
108
- | `TOKEN_ACC` | 99.95 |
109
  | `TOKEN_P` | 99.78 |
110
  | `TOKEN_R` | 99.75 |
111
  | `TOKEN_F` | 99.76 |
112
- | `POS_ACC` | 96.18 |
113
- | `MORPH_ACC` | 94.84 |
114
- | `MORPH_MICRO_P` | 96.75 |
115
- | `MORPH_MICRO_R` | 96.22 |
116
- | `MORPH_MICRO_F` | 96.49 |
117
- | `SENTS_P` | 92.03 |
118
- | `SENTS_R` | 90.07 |
119
- | `SENTS_F` | 91.04 |
120
- | `DEP_UAS` | 82.16 |
121
- | `DEP_LAS` | 78.02 |
122
- | `LEMMA_ACC` | 94.97 |
123
- | `TAG_ACC` | 96.18 |
124
- | `ENTS_P` | 80.64 |
125
- | `ENTS_R` | 78.96 |
126
- | `ENTS_F` | 79.79 |
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8020833333
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8020833333
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8020833333
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9634866828
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.9634866828
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.9515738499
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
+ value: 0.9476997579
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
+ value: 0.8226680825
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
+ value: 0.7821616184
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
+ value: 0.9056603774
73
  ---
74
  ### Details: https://spacy.io/models/da#da_core_news_md
75
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `da_core_news_md` |
81
+ | **Version** | `3.5.0` |
82
+ | **spaCy** | `>=3.5.0,<3.6.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
105
 
106
  | Type | Score |
107
  | --- | --- |
108
+ | `TOKEN_ACC` | 99.89 |
109
  | `TOKEN_P` | 99.78 |
110
  | `TOKEN_R` | 99.75 |
111
  | `TOKEN_F` | 99.76 |
112
+ | `POS_ACC` | 96.35 |
113
+ | `MORPH_ACC` | 95.16 |
114
+ | `MORPH_MICRO_P` | 96.91 |
115
+ | `MORPH_MICRO_R` | 96.34 |
116
+ | `MORPH_MICRO_F` | 96.62 |
117
+ | `SENTS_P` | 91.80 |
118
+ | `SENTS_R` | 89.36 |
119
+ | `SENTS_F` | 90.57 |
120
+ | `DEP_UAS` | 82.27 |
121
+ | `DEP_LAS` | 78.22 |
122
+ | `LEMMA_ACC` | 94.77 |
123
+ | `TAG_ACC` | 96.35 |
124
+ | `ENTS_P` | 80.21 |
125
+ | `ENTS_R` | 80.21 |
126
+ | `ENTS_F` | 80.21 |
accuracy.json CHANGED
@@ -1,53 +1,53 @@
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  {
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- "token_acc": 0.9994672349,
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  "token_p": 0.9977732598,
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  "token_r": 0.9974835463,
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  "token_f": 0.997628382,
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- "pos_acc": 0.9618401937,
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- "morph_acc": 0.948377724,
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- "morph_micro_p": 0.9675176369,
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- "morph_micro_r": 0.9622431982,
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- "morph_micro_f": 0.9648732095,
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  "morph_per_feat": {
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  "Mood": {
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- "p": 0.9799235182,
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- "r": 0.9771210677,
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  "Tense": {
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  "Voice": {
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  },
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@@ -55,29 +55,29 @@
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@@ -85,19 +85,19 @@
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  "f": 1.0
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  },
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  "Number[psor]": {
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  "r": 1.0,
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  "Foreign": {
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  "Abbr": {
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  "p": 0.0,
@@ -115,141 +115,141 @@
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  "f": 0.75
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  }
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- "dep_uas": 0.8215642458,
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- "dep_las": 0.7802234637,
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@@ -257,56 +257,56 @@
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- "lemma_acc": 0.9497336562,
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@@ -314,5 +314,5 @@
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  "f": 0.8733624454
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  }
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  },
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- "speed": 12214.1305450038
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  }
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  "token_p": 0.9977732598,
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  "token_r": 0.9974835463,
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  "Tense": {
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  "Voice": {
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  "Definite": {
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  "Gender": {
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  "Reflex": {
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