adrianeboyd commited on
Commit
a8035b6
1 Parent(s): 383907d

Update spaCy pipeline

Browse files
README.md CHANGED
@@ -14,51 +14,51 @@ model-index:
14
  metrics:
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  - name: NER Precision
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  type: precision
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- value: 0.8998444478
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  - name: NER Recall
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  type: recall
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- value: 0.8980869391
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  - name: NER F Score
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  type: f_score
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- value: 0.8989648344
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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: 0.9780283894
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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: 0.9514229828
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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: 0.9379149652
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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: 0.897621366
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  ---
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  ### Details: https://spacy.io/models/en#en_core_web_trf
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- English transformer pipeline (roberta-base). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.
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  | Feature | Description |
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  | --- | --- |
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  | **Name** | `en_core_web_trf` |
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- | **Version** | `3.6.1` |
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- | **spaCy** | `>=3.6.0,<3.7.0` |
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  | **Default Pipeline** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
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  | **Components** | `transformer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
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  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -88,12 +88,12 @@ English transformer pipeline (roberta-base). Components: transformer, tagger, pa
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  | `TOKEN_P` | 99.57 |
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  | `TOKEN_R` | 99.58 |
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  | `TOKEN_F` | 99.57 |
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- | `TAG_ACC` | 97.80 |
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- | `SENTS_P` | 94.92 |
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- | `SENTS_R` | 85.14 |
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- | `SENTS_F` | 89.76 |
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- | `DEP_UAS` | 95.14 |
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- | `DEP_LAS` | 93.79 |
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- | `ENTS_P` | 89.98 |
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- | `ENTS_R` | 89.81 |
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  | `ENTS_F` | 89.90 |
 
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
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  - 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
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  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.8881133524
52
  ---
53
  ### Details: https://spacy.io/models/en#en_core_web_trf
54
 
55
+ English transformer pipeline (Transformer(name='roberta-base', piece_encoder='byte-bpe', stride=104, type='roberta', width=768, window=144, vocab_size=50265)). Components: transformer, tagger, parser, ner, attribute_ruler, lemmatizer.
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57
  | Feature | Description |
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  | --- | --- |
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  | **Name** | `en_core_web_trf` |
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+ | **Version** | `3.7.2` |
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+ | **spaCy** | `>=3.7.0,<3.8.0` |
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  | **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` | 98.16 |
92
+ | `SENTS_P` | 94.29 |
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+ | `SENTS_R` | 83.94 |
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+ | `SENTS_F` | 88.81 |
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+ | `DEP_UAS` | 95.05 |
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+ | `DEP_LAS` | 93.69 |
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+ | `ENTS_P` | 89.95 |
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+ | `ENTS_R` | 89.86 |
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  | `ENTS_F` | 89.90 |
accuracy.json CHANGED
@@ -3,328 +3,328 @@
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