adrianeboyd commited on
Commit
78c48f8
1 Parent(s): 17c49af

Update spaCy pipeline

Browse files
README.md CHANGED
@@ -14,41 +14,41 @@ model-index:
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  metrics:
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  - name: NER Precision
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  type: precision
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- value: 0.8535469108
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  - name: NER Recall
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  type: recall
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- value: 0.8592748397
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  - name: NER F Score
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  type: f_score
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- value: 0.8564012977
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  - task:
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  name: TAG
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  type: token-classification
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  metrics:
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  - name: TAG (XPOS) Accuracy
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  type: accuracy
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- value: 0.9734404547
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  - task:
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  name: UNLABELED_DEPENDENCIES
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  type: token-classification
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  metrics:
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  - name: Unlabeled Attachment Score (UAS)
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  type: f_score
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- value: 0.9204363007
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  - task:
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  name: LABELED_DEPENDENCIES
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  type: token-classification
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  metrics:
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  - name: Labeled Attachment Score (LAS)
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  type: f_score
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- value: 0.9023174614
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  - task:
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  name: SENTS
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  type: token-classification
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  metrics:
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  - name: Sentences F-Score
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  type: f_score
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- value: 0.90444794
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  ---
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  ### Details: https://spacy.io/models/en#en_core_web_lg
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@@ -57,8 +57,8 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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  | Feature | Description |
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  | --- | --- |
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  | **Name** | `en_core_web_lg` |
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- | **Version** | `3.4.1` |
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- | **spaCy** | `>=3.4.0,<3.5.0` |
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  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
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  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
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  | **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
@@ -84,16 +84,16 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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85
  | Type | Score |
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  | --- | --- |
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- | `TOKEN_ACC` | 99.93 |
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  | `TOKEN_P` | 99.57 |
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  | `TOKEN_R` | 99.58 |
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  | `TOKEN_F` | 99.57 |
91
- | `TAG_ACC` | 97.34 |
92
- | `SENTS_P` | 91.79 |
93
- | `SENTS_R` | 89.14 |
94
- | `SENTS_F` | 90.44 |
95
- | `DEP_UAS` | 92.04 |
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- | `DEP_LAS` | 90.23 |
97
- | `ENTS_P` | 85.35 |
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- | `ENTS_R` | 85.93 |
99
- | `ENTS_F` | 85.64 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8516398746
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8569711538
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8542971968
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9734810915
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
+ value: 0.9208198801
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
+ value: 0.9027174273
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.907098331
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_lg
54
 
 
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `en_core_web_lg` |
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** | 514157 keys, 514157 unique vectors (300 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` | 97.35 |
92
+ | `SENTS_P` | 92.19 |
93
+ | `SENTS_R` | 89.27 |
94
+ | `SENTS_F` | 90.71 |
95
+ | `DEP_UAS` | 92.08 |
96
+ | `DEP_LAS` | 90.27 |
97
+ | `ENTS_P` | 85.16 |
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+ | `ENTS_R` | 85.70 |
99
+ | `ENTS_F` | 85.43 |
accuracy.json CHANGED
@@ -1,330 +1,330 @@
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  }
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- "speed": 9221.3523549505
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