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spacy
/
en_core_web_trf

Token Classification
spaCy
English
Eval Results
Model card Files
adrianeboyd commited on
Commit
e8e4307
•
1 Parent(s): a8035b6

Update spaCy pipeline

Browse files
Files changed (9) hide show
  1. README.md +18 -18
  2. accuracy.json +199 -199
  3. attribute_ruler/patterns +0 -0
  4. en_core_web_trf-any-py3-none-any.whl +2 -2
  5. meta.json +202 -202
  6. ner/model +1 -1
  7. parser/model +1 -1
  8. tagger/model +1 -1
  9. transformer/model +2 -2
README.md CHANGED
@@ -14,41 +14,41 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.8994886705
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8985877404
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.8990379798
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.9815755741
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
- value: 0.9505463996
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
- value: 0.9368643771
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
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- value: 0.8881133524
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_trf
54
 
@@ -57,8 +57,8 @@ English transformer pipeline (Transformer(name='roberta-base', piece_encoder='by
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_trf` |
60
- | **Version** | `3.7.2` |
61
- | **spaCy** | `>=3.7.0,<3.8.0` |
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) |
@@ -88,12 +88,12 @@ English transformer pipeline (Transformer(name='roberta-base', piece_encoder='by
88
  | `TOKEN_P` | 99.57 |
89
  | `TOKEN_R` | 99.58 |
90
  | `TOKEN_F` | 99.57 |
91
- | `TAG_ACC` | 98.16 |
92
- | `SENTS_P` | 94.29 |
93
- | `SENTS_R` | 83.94 |
94
- | `SENTS_F` | 88.81 |
95
- | `DEP_UAS` | 95.05 |
96
- | `DEP_LAS` | 93.69 |
97
- | `ENTS_P` | 89.95 |
98
- | `ENTS_R` | 89.86 |
99
- | `ENTS_F` | 89.90 |
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.9008293365
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.9029947917
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.9019107643
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9812819818
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
+ value: 0.9526219812
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
+ value: 0.9390746643
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.9011225055
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** | `3.7.3` |
61
+ | **spaCy** | `>=3.7.2,<3.8.0` |
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) |
88
  | `TOKEN_P` | 99.57 |
89
  | `TOKEN_R` | 99.58 |
90
  | `TOKEN_F` | 99.57 |
91
+ | `TAG_ACC` | 98.13 |
92
+ | `SENTS_P` | 94.89 |
93
+ | `SENTS_R` | 85.79 |
94
+ | `SENTS_F` | 90.11 |
95
+ | `DEP_UAS` | 95.26 |
96
+ | `DEP_LAS` | 93.91 |
97
+ | `ENTS_P` | 90.08 |
98
+ | `ENTS_R` | 90.30 |
99
+ | `ENTS_F` | 90.19 |
accuracy.json CHANGED
@@ -3,328 +3,328 @@
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