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spacy
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de_core_news_lg

Token Classification spaCy German Eval Results
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adrianeboyd commited on
Commit
c7809db
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1 Parent(s): e7d8634

Update spaCy pipeline

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Files changed (14) hide show
  1. README.md +26 -26
  2. accuracy.json +180 -180
  3. config.cfg +5 -4
  4. de_core_news_lg-any-py3-none-any.whl +2 -2
  5. lemmatizer/model +1 -1
  6. meta.json +183 -183
  7. morphologizer/model +1 -1
  8. ner/model +2 -2
  9. parser/model +1 -1
  10. senter/model +1 -1
  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: 0.8528386427
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8461254893
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8494688031
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9799589002
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
- value: 0.9844984802
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.9219424199
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
- value: 0.9790152496
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
- value: 0.9265973031
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.9078315742
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9509285196
73
  ---
74
  ### Details: https://spacy.io/models/de#de_core_news_lg
75
 
@@ -78,8 +78,8 @@ German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, p
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `de_core_news_lg` |
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** | 500000 keys, 500000 unique vectors (300 dimensions) |
@@ -106,22 +106,22 @@ German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, p
106
 
107
  | Type | Score |
108
  | --- | --- |
109
- | `TOKEN_ACC` | 99.98 |
110
  | `TOKEN_P` | 99.92 |
111
  | `TOKEN_R` | 99.90 |
112
  | `TOKEN_F` | 99.91 |
113
- | `TAG_ACC` | 98.00 |
114
- | `POS_ACC` | 98.45 |
115
- | `MORPH_ACC` | 92.19 |
116
- | `MORPH_MICRO_P` | 96.08 |
117
- | `MORPH_MICRO_R` | 96.05 |
118
- | `MORPH_MICRO_F` | 96.06 |
119
- | `SENTS_P` | 95.48 |
120
- | `SENTS_R` | 96.06 |
121
- | `SENTS_F` | 95.09 |
122
  | `DEP_UAS` | 92.66 |
123
  | `DEP_LAS` | 90.78 |
124
- | `LEMMA_ACC` | 97.90 |
125
- | `ENTS_P` | 85.28 |
126
- | `ENTS_R` | 84.61 |
127
- | `ENTS_F` | 84.95 |
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8527131783
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.844401557
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8485370145
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9795559667
31
  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.9841217399
38
  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.9205894013
45
  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
+ value: 0.9790945371
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
+ value: 0.9265658098
59
  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
+ value: 0.9078030166
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
+ value: 0.9541230945
73
  ---
74
  ### Details: https://spacy.io/models/de#de_core_news_lg
75
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `de_core_news_lg` |
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** | 500000 keys, 500000 unique vectors (300 dimensions) |
106
 
107
  | Type | Score |
108
  | --- | --- |
109
+ | `TOKEN_ACC` | 99.96 |
110
  | `TOKEN_P` | 99.92 |
111
  | `TOKEN_R` | 99.90 |
112
  | `TOKEN_F` | 99.91 |
113
+ | `TAG_ACC` | 97.96 |
114
+ | `POS_ACC` | 98.41 |
115
+ | `MORPH_ACC` | 92.06 |
116
+ | `MORPH_MICRO_P` | 96.01 |
117
+ | `MORPH_MICRO_R` | 95.99 |
118
+ | `MORPH_MICRO_F` | 96.00 |
119
+ | `SENTS_P` | 95.18 |
120
+ | `SENTS_R` | 96.48 |
121
+ | `SENTS_F` | 95.41 |
122
  | `DEP_UAS` | 92.66 |
123
  | `DEP_LAS` | 90.78 |
124
+ | `LEMMA_ACC` | 97.91 |
125
+ | `ENTS_P` | 85.27 |
126
+ | `ENTS_R` | 84.44 |
127
+ | `ENTS_F` | 84.85 |
accuracy.json CHANGED
@@ -1,64 +1,64 @@
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  {
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- "token_acc": 0.9998017682,
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  "token_p": 0.9991808044,
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  "token_r": 0.9990356034,
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  "token_f": 0.9991081986,
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- "tag_acc": 0.9799589002,
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- "pos_acc": 0.9844984802,
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- "morph_acc": 0.9219424199,
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- "morph_micro_p": 0.9607921735,
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- "morph_micro_r": 0.9604629689,
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- "morph_micro_f": 0.960627543,
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  "morph_per_feat": {
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  "Case": {
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- "p": 0.9212369357,
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- "r": 0.9228029465,
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- "f": 0.9220192761
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  },
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  "Definite": {
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- "p": 0.996126239,
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- "f": 0.9966372186
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  },
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  "Gender": {
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- "f": 0.9505309797
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  },
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  "Number": {
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- "p": 0.9770990599,
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- "r": 0.9774611999,
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- "f": 0.9772800963
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  },
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  "Degree": {
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  "Mood": {
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  "Tense": {
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  "Reflex": {
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  "p": 1.0,
@@ -66,207 +66,207 @@
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  "f": 0.9964328181
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  },
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  "Poss": {
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- "p": 0.9958847737,
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  "r": 1.0,
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- "f": 0.9979381443
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  "Foreign": {
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- "p": 0.7555555556,
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- "r": 0.1708542714,
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  }
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  },
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- "sents_p": 0.9547916667,
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- "sents_r": 0.9605866756,
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- "sents_f": 0.9509285196,
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- "dep_uas": 0.9265973031,
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- "dep_las": 0.9078315742,
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  "dep_las_per_type": {
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  "cp": {
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  },
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  "ph": {
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  "og": {
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- "lemma_acc": 0.9790152496,
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- "speed": 11363.5362762021,
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- "ents_p": 0.8528386427,
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  "ents_per_type": {
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  "PER": {
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  "ORG": {
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  }
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  }
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  }
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  "token_p": 0.9991808044,
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  "token_f": 0.9991081986,
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+ "tag_acc": 0.9795559667,
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+ "pos_acc": 0.9841217399,
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+ "morph_acc": 0.9205894013,
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  "morph_per_feat": {
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  "Definite": {
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  "Gender": {
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  "Number": {
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  "PronType": {
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  "Degree": {
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  "Tense": {
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  "Reflex": {
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  "Foreign": {
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