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spacy
/
en_core_web_trf

Token Classification
spaCy
English
Eval Results
Model card Files
xet
adrianeboyd commited on
Commit
a134d22
·
1 Parent(s): 11764b8

Update spaCy pipeline

Browse files
Files changed (10) hide show
  1. README.md +19 -19
  2. accuracy.json +193 -193
  3. config.cfg +1 -0
  4. en_core_web_trf-any-py3-none-any.whl +2 -2
  5. meta.json +197 -197
  6. ner/model +1 -1
  7. parser/model +1 -1
  8. tagger/model +1 -1
  9. tokenizer +0 -0
  10. transformer/model +2 -2
README.md CHANGED
@@ -14,41 +14,41 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.8953563447
18
  - name: NER Recall
19
  type: recall
20
- value: 0.9028445513
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8990848565
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9780884117
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
- value: 0.9532621063
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
- value: 0.9398782759
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
- value: 0.9121217361
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_trf
54
 
@@ -57,8 +57,8 @@ English transformer pipeline (roberta-base). Components: transformer, tagger, pa
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_trf` |
60
- | **Version** | `3.4.1` |
61
- | **spaCy** | `>=3.4.0,<3.5.0` |
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) |
@@ -84,16 +84,16 @@ English transformer pipeline (roberta-base). Components: transformer, tagger, pa
84
 
85
  | Type | Score |
86
  | --- | --- |
87
- | `TOKEN_ACC` | 99.93 |
88
  | `TOKEN_P` | 99.57 |
89
  | `TOKEN_R` | 99.58 |
90
  | `TOKEN_F` | 99.57 |
91
- | `TAG_ACC` | 97.81 |
92
- | `SENTS_P` | 95.86 |
93
- | `SENTS_R` | 86.99 |
94
- | `SENTS_F` | 91.21 |
95
- | `DEP_UAS` | 95.33 |
96
- | `DEP_LAS` | 93.99 |
97
- | `ENTS_P` | 89.54 |
98
- | `ENTS_R` | 90.28 |
99
- | `ENTS_F` | 89.91 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8977938984
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.9048978365
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.9013318701
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9778773818
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
+ value: 0.9527427739
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
+ value: 0.9395456671
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.8969481605
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** | `3.5.0` |
61
+ | **spaCy** | `>=3.5.0,<3.6.0` |
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) |
 
84
 
85
  | Type | Score |
86
  | --- | --- |
87
+ | `TOKEN_ACC` | 99.86 |
88
  | `TOKEN_P` | 99.57 |
89
  | `TOKEN_R` | 99.58 |
90
  | `TOKEN_F` | 99.57 |
91
+ | `TAG_ACC` | 97.79 |
92
+ | `SENTS_P` | 95.04 |
93
+ | `SENTS_R` | 84.92 |
94
+ | `SENTS_F` | 89.69 |
95
+ | `DEP_UAS` | 95.27 |
96
+ | `DEP_LAS` | 93.95 |
97
+ | `ENTS_P` | 89.78 |
98
+ | `ENTS_R` | 90.49 |
99
+ | `ENTS_F` | 90.13 |
accuracy.json CHANGED
@@ -1,330 +1,330 @@
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