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spacy
/
de_dep_news_trf

Token Classification
spaCy
German
Eval Results (legacy)
Model card Files
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 Community
1
adrianeboyd commited on
Commit
d9c0885
·
1 Parent(s): 1038cbb

Update spaCy pipeline

Browse files
Files changed (13) hide show
  1. README.md +18 -18
  2. accuracy.json +145 -145
  3. config.cfg +3 -1
  4. de_dep_news_trf-any-py3-none-any.whl +2 -2
  5. lemmatizer/model +1 -1
  6. meta.json +149 -149
  7. morphologizer/cfg +1 -0
  8. morphologizer/model +1 -1
  9. parser/model +1 -1
  10. tagger/cfg +1 -0
  11. tagger/model +1 -1
  12. transformer/model +2 -2
  13. vocab/strings.json +2 -2
README.md CHANGED
@@ -14,49 +14,49 @@ model-index:
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
- value: 0.990643584
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
- value: 0.9915288956
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
- value: 0.9699941191
32
  - task:
33
  name: LEMMA
34
  type: token-classification
35
  metrics:
36
  - name: Lemma Accuracy
37
  type: accuracy
38
- value: 0.9873800777
39
  - task:
40
  name: UNLABELED_DEPENDENCIES
41
  type: token-classification
42
  metrics:
43
  - name: Unlabeled Attachment Score (UAS)
44
  type: f_score
45
- value: 0.9593756103
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
- value: 0.9480405339
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
- value: 0.9827461515
60
  ---
61
  ### Details: https://spacy.io/models/de#de_dep_news_trf
62
 
@@ -65,8 +65,8 @@ German transformer pipeline (bert-base-german-cased). Components: transformer, t
65
  | Feature | Description |
66
  | --- | --- |
67
  | **Name** | `de_dep_news_trf` |
68
- | **Version** | `3.5.0` |
69
- | **spaCy** | `>=3.5.0,<3.6.0` |
70
  | **Default Pipeline** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler` |
71
  | **Components** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler` |
72
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -98,13 +98,13 @@ German transformer pipeline (bert-base-german-cased). Components: transformer, t
98
  | `TOKEN_F` | 99.91 |
99
  | `TAG_ACC` | 99.06 |
100
  | `POS_ACC` | 99.15 |
101
- | `MORPH_ACC` | 97.00 |
102
- | `MORPH_MICRO_P` | 98.83 |
103
- | `MORPH_MICRO_R` | 98.87 |
104
  | `MORPH_MICRO_F` | 98.85 |
105
- | `SENTS_P` | 98.26 |
106
- | `SENTS_R` | 98.28 |
107
- | `SENTS_F` | 98.27 |
108
- | `DEP_UAS` | 95.94 |
109
- | `DEP_LAS` | 94.80 |
110
- | `LEMMA_ACC` | 98.74 |
 
14
  metrics:
15
  - name: TAG (XPOS) Accuracy
16
  type: accuracy
17
+ value: 0.9905775076
18
  - task:
19
  name: POS
20
  type: token-classification
21
  metrics:
22
  - name: POS (UPOS) Accuracy
23
  type: accuracy
24
+ value: 0.9914628183
25
  - task:
26
  name: MORPH
27
  type: token-classification
28
  metrics:
29
  - name: Morph (UFeats) Accuracy
30
  type: accuracy
31
+ value: 0.9700866279
32
  - task:
33
  name: LEMMA
34
  type: token-classification
35
  metrics:
36
  - name: Lemma Accuracy
37
  type: accuracy
38
+ value: 0.9872611465
39
  - task:
40
  name: UNLABELED_DEPENDENCIES
41
  type: token-classification
42
  metrics:
43
  - name: Unlabeled Attachment Score (UAS)
44
  type: f_score
45
+ value: 0.9592566441
46
  - task:
47
  name: LABELED_DEPENDENCIES
48
  type: token-classification
49
  metrics:
50
  - name: Labeled Attachment Score (LAS)
51
  type: f_score
52
+ value: 0.9484326996
53
  - task:
54
  name: SENTS
55
  type: token-classification
56
  metrics:
57
  - name: Sentences F-Score
58
  type: f_score
59
+ value: 0.9797854785
60
  ---
61
  ### Details: https://spacy.io/models/de#de_dep_news_trf
62
 
 
65
  | Feature | Description |
66
  | --- | --- |
67
  | **Name** | `de_dep_news_trf` |
68
+ | **Version** | `3.6.1` |
69
+ | **spaCy** | `>=3.6.0,<3.7.0` |
70
  | **Default Pipeline** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler` |
71
  | **Components** | `transformer`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler` |
72
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
98
  | `TOKEN_F` | 99.91 |
99
  | `TAG_ACC` | 99.06 |
100
  | `POS_ACC` | 99.15 |
101
+ | `MORPH_ACC` | 97.01 |
102
+ | `MORPH_MICRO_P` | 98.86 |
103
+ | `MORPH_MICRO_R` | 98.84 |
104
  | `MORPH_MICRO_F` | 98.85 |
105
+ | `SENTS_P` | 97.80 |
106
+ | `SENTS_R` | 98.16 |
107
+ | `SENTS_F` | 97.98 |
108
+ | `DEP_UAS` | 95.93 |
109
+ | `DEP_LAS` | 94.84 |
110
+ | `LEMMA_ACC` | 98.73 |
accuracy.json CHANGED
@@ -3,62 +3,62 @@
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  "token_p": 0.9991808044,
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  "token_f": 0.9991081986,
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- "pos_acc": 0.9915288956,
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- "morph_micro_f": 0.9885005414,
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  "morph_per_feat": {
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  "Case": {
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  "Definite": {
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  },
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  "Gender": {
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  },
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  "Mood": {
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  "Reflex": {
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  "p": 0.9976359338,
@@ -71,66 +71,66 @@
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  "f": 1.0
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  },
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  "Foreign": {
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- "sents_p": 0.9826446281,
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- "dep_las": 0.9480405339,
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  "dep_las_per_type": {
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  "cp": {
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@@ -138,84 +138,84 @@
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  "nmc": {
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@@ -223,44 +223,44 @@
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@@ -278,9 +278,9 @@
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@@ -293,6 +293,6 @@
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- "lemma_acc": 0.9873800777,
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- "speed": 5858.0470519607
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  }
 
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