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spacy
/
en_core_web_trf

Token Classification
spaCy
English
Eval Results
Model card Files
xet
EC2 Default User commited on
Commit
de00f6d
·
1 Parent(s): 796dea5

Update spaCy pipeline

Browse files
Files changed (14) hide show
  1. README.md +27 -33
  2. accuracy.json +201 -201
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +3 -1
  5. en_core_web_trf-any-py3-none-any.whl +2 -2
  6. meta.json +204 -204
  7. ner/model +1 -1
  8. parser/model +1 -1
  9. parser/moves +1 -1
  10. tagger/cfg +1 -0
  11. tagger/model +2 -2
  12. tokenizer +0 -0
  13. transformer/model +2 -2
  14. vocab/strings.json +2 -2
README.md CHANGED
@@ -14,47 +14,41 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.898708838
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8993389423
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8990237797
24
  - task:
25
- name: POS
26
  type: token-classification
27
  metrics:
28
- - name: POS Accuracy
29
  type: accuracy
30
- value: 0.9780627094
31
  - task:
32
- name: SENTER
33
  type: token-classification
34
  metrics:
35
- - name: SENTER Precision
36
- type: precision
37
- value: 0.9568827385
38
- - name: SENTER Recall
39
- type: recall
40
- value: 0.8666798601
41
- - name: SENTER F Score
42
  type: f_score
43
- value: 0.9095503479
44
  - task:
45
- name: UNLABELED_DEPENDENCIES
46
  type: token-classification
47
  metrics:
48
- - name: Unlabeled Dependencies Accuracy
49
- type: accuracy
50
- value: 0.9527056513
51
  - task:
52
- name: LABELED_DEPENDENCIES
53
  type: token-classification
54
  metrics:
55
- - name: Labeled Dependencies Accuracy
56
- type: accuracy
57
- value: 0.9527056513
58
  ---
59
  ### Details: https://spacy.io/models/en#en_core_web_trf
60
 
@@ -63,8 +57,8 @@ English transformer pipeline (roberta-base). Components: transformer, tagger, pa
63
  | Feature | Description |
64
  | --- | --- |
65
  | **Name** | `en_core_web_trf` |
66
- | **Version** | `3.2.0` |
67
- | **spaCy** | `>=3.2.0,<3.3.0` |
68
  | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
69
  | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
70
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -95,11 +89,11 @@ English transformer pipeline (roberta-base). Components: transformer, tagger, pa
95
  | `TOKEN_R` | 99.58 |
96
  | `TOKEN_F` | 99.57 |
97
  | `TAG_ACC` | 97.81 |
98
- | `SENTS_P` | 95.69 |
99
- | `SENTS_R` | 86.67 |
100
- | `SENTS_F` | 90.96 |
101
- | `DEP_UAS` | 95.27 |
102
- | `DEP_LAS` | 93.93 |
103
- | `ENTS_P` | 89.87 |
104
- | `ENTS_R` | 89.93 |
105
- | `ENTS_F` | 89.90 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.9010175297
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8957832532
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8983927675
24
  - task:
25
+ name: TAG
26
  type: token-classification
27
  metrics:
28
+ - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9781090037
31
  - task:
32
+ name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
+ - name: Unlabeled Attachment Score (UAS)
 
 
 
 
 
 
36
  type: f_score
37
+ value: 0.9523761283
38
  - task:
39
+ name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
+ - name: Labeled Attachment Score (LAS)
43
+ type: f_score
44
+ value: 0.9391113934
45
  - task:
46
+ name: SENTS
47
  type: token-classification
48
  metrics:
49
+ - name: Sentences F-Score
50
+ type: f_score
51
+ value: 0.8975616543
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_trf
54
 
 
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_trf` |
60
+ | **Version** | `3.3.0` |
61
+ | **spaCy** | `>=3.3.0.dev0,<3.4.0` |
62
  | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
63
  | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
64
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
89
  | `TOKEN_R` | 99.58 |
90
  | `TOKEN_F` | 99.57 |
91
  | `TAG_ACC` | 97.81 |
92
+ | `SENTS_P` | 94.94 |
93
+ | `SENTS_R` | 85.11 |
94
+ | `SENTS_F` | 89.76 |
95
+ | `DEP_UAS` | 95.24 |
96
+ | `DEP_LAS` | 93.91 |
97
+ | `ENTS_P` | 90.10 |
98
+ | `ENTS_R` | 89.58 |
99
+ | `ENTS_F` | 89.84 |
accuracy.json CHANGED
@@ -1,330 +1,330 @@
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