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en_core_web_sm

Token Classification
spaCy
English
Eval Results
Model card Files
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adrianeboyd commited on
Commit
582cb9c
·
1 Parent(s): c0f7334

Update spaCy pipeline

Browse files
Files changed (12) hide show
  1. README.md +19 -19
  2. accuracy.json +201 -201
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +5 -4
  5. en_core_web_sm-any-py3-none-any.whl +2 -2
  6. meta.json +204 -204
  7. ner/model +2 -2
  8. parser/model +1 -1
  9. senter/model +1 -1
  10. tagger/model +1 -1
  11. tok2vec/model +2 -2
  12. tokenizer +0 -0
README.md CHANGED
@@ -14,41 +14,41 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.8410860451
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8439503205
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8425157484
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9726250474
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
- value: 0.9165718428
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
- value: 0.8978441095
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
- value: 0.9038596962
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_sm
54
 
@@ -57,8 +57,8 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_sm` |
60
- | **Version** | `3.4.1` |
61
- | **spaCy** | `>=3.4.0,<3.5.0` |
62
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
63
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
64
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -84,16 +84,16 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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` | 97.26 |
92
- | `SENTS_P` | 91.92 |
93
- | `SENTS_R` | 88.90 |
94
- | `SENTS_F` | 90.39 |
95
- | `DEP_UAS` | 91.66 |
96
- | `DEP_LAS` | 89.78 |
97
- | `ENTS_P` | 84.11 |
98
- | `ENTS_R` | 84.40 |
99
- | `ENTS_F` | 84.25 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8454836771
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8456530449
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8455683525
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.97246532
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
+ value: 0.9175304332
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
+ value: 0.89874821
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.9059485531
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_sm
54
 
 
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_sm` |
60
+ | **Version** | `3.5.0` |
61
+ | **spaCy** | `>=3.5.0,<3.6.0` |
62
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
63
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `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` | 97.25 |
92
+ | `SENTS_P` | 92.02 |
93
+ | `SENTS_R` | 89.21 |
94
+ | `SENTS_F` | 90.59 |
95
+ | `DEP_UAS` | 91.75 |
96
+ | `DEP_LAS` | 89.87 |
97
+ | `ENTS_P` | 84.55 |
98
+ | `ENTS_R` | 84.57 |
99
+ | `ENTS_F` | 84.56 |
accuracy.json CHANGED
@@ -1,330 +1,330 @@
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