adrianeboyd commited on
Commit
65f400a
1 Parent(s): 3da1f9e

Update spaCy pipeline

Browse files
README.md CHANGED
@@ -14,62 +14,62 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.7117117117
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  - name: NER Recall
19
  type: recall
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- value: 0.6638655462
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  - name: NER F Score
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  type: f_score
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- value: 0.6869565217
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  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
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- value: 0.9136715476
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  - task:
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  name: POS
33
  type: token-classification
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  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
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- value: 0.9436473894
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  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
- value: 0.8869496623
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  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
- value: 0.8857664054
52
  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
55
  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
57
  type: f_score
58
- value: 0.8457438039
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  - task:
60
  name: LABELED_DEPENDENCIES
61
  type: token-classification
62
  metrics:
63
  - name: Labeled Attachment Score (LAS)
64
  type: f_score
65
- value: 0.8013408804
66
  - task:
67
  name: SENTS
68
  type: token-classification
69
  metrics:
70
  - name: Sentences F-Score
71
  type: f_score
72
- value: 0.9287469287
73
  ---
74
  ### Details: https://spacy.io/models/el#el_core_news_sm
75
 
@@ -78,8 +78,8 @@ Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, le
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `el_core_news_sm` |
81
- | **Version** | `3.4.0` |
82
- | **spaCy** | `>=3.4.0,<3.5.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -109,18 +109,18 @@ Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, le
109
  | `TOKEN_P` | 99.90 |
110
  | `TOKEN_R` | 99.95 |
111
  | `TOKEN_F` | 99.93 |
112
- | `POS_ACC` | 94.36 |
113
- | `MORPH_ACC` | 88.69 |
114
- | `MORPH_MICRO_P` | 94.65 |
115
- | `MORPH_MICRO_R` | 94.41 |
116
- | `MORPH_MICRO_F` | 94.53 |
117
- | `SENTS_P` | 91.97 |
118
- | `SENTS_R` | 93.80 |
119
- | `SENTS_F` | 92.87 |
120
- | `DEP_UAS` | 84.57 |
121
- | `DEP_LAS` | 80.13 |
122
- | `LEMMA_ACC` | 88.58 |
123
- | `TAG_ACC` | 91.37 |
124
- | `ENTS_P` | 71.17 |
125
- | `ENTS_R` | 66.39 |
126
- | `ENTS_F` | 68.70 |
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.742081448
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.6890756303
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.7145969499
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9127841049
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  - task:
32
  name: POS
33
  type: token-classification
34
  metrics:
35
  - name: POS (UPOS) Accuracy
36
  type: accuracy
37
+ value: 0.9427599468
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  - task:
39
  name: MORPH
40
  type: token-classification
41
  metrics:
42
  - name: Morph (UFeats) Accuracy
43
  type: accuracy
44
+ value: 0.8905980378
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  - task:
46
  name: LEMMA
47
  type: token-classification
48
  metrics:
49
  - name: Lemma Accuracy
50
  type: accuracy
51
+ value: 0.8865552433
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  - task:
53
  name: UNLABELED_DEPENDENCIES
54
  type: token-classification
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  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
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  type: f_score
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+ value: 0.8463356974
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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: 0.8032327231
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  - task:
67
  name: SENTS
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  type: token-classification
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  metrics:
70
  - name: Sentences F-Score
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  type: f_score
72
+ value: 0.9372693727
73
  ---
74
  ### Details: https://spacy.io/models/el#el_core_news_sm
75
 
 
78
  | Feature | Description |
79
  | --- | --- |
80
  | **Name** | `el_core_news_sm` |
81
+ | **Version** | `3.5.0` |
82
+ | **spaCy** | `>=3.5.0,<3.6.0` |
83
  | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
84
  | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
85
  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 
109
  | `TOKEN_P` | 99.90 |
110
  | `TOKEN_R` | 99.95 |
111
  | `TOKEN_F` | 99.93 |
112
+ | `POS_ACC` | 94.28 |
113
+ | `MORPH_ACC` | 89.06 |
114
+ | `MORPH_MICRO_P` | 94.85 |
115
+ | `MORPH_MICRO_R` | 94.52 |
116
+ | `MORPH_MICRO_F` | 94.69 |
117
+ | `SENTS_P` | 92.93 |
118
+ | `SENTS_R` | 94.54 |
119
+ | `SENTS_F` | 93.73 |
120
+ | `DEP_UAS` | 84.63 |
121
+ | `DEP_LAS` | 80.32 |
122
+ | `LEMMA_ACC` | 88.66 |
123
+ | `TAG_ACC` | 91.28 |
124
+ | `ENTS_P` | 74.21 |
125
+ | `ENTS_R` | 68.91 |
126
+ | `ENTS_F` | 71.46 |
accuracy.json CHANGED
@@ -3,124 +3,124 @@
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  "dep_las_per_type": {},
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@@ -133,5 +133,5 @@
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attribute_ruler/patterns CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
 
config.cfg CHANGED
@@ -81,8 +81,8 @@ nO = null
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  [components.ner.model.tok2vec.embed]
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  @architectures = "spacy.MultiHashEmbed.v2"
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  width = 96
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- attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
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- rows = [5000,1000,2500,2500,50]
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  include_static_vectors = false
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88
  [components.ner.model.tok2vec.encode]
@@ -150,8 +150,8 @@ factory = "tok2vec"
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  [components.tok2vec.model.embed]
151
  @architectures = "spacy.MultiHashEmbed.v2"
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  width = ${components.tok2vec.model.encode:width}
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- attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
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- rows = [5000,1000,2500,2500,50]
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  include_static_vectors = false
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157
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@@ -193,6 +193,7 @@ eval_frequency = 1000
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  frozen_components = []
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  before_to_disk = null
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  annotating_components = []
 
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  [training.batcher]
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  @batchers = "spacy.batch_by_words.v1"
 
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  @architectures = "spacy.MultiHashEmbed.v2"
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  width = 96
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+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
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+ rows = [5000,1000,2500,2500]
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  include_static_vectors = false
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  [components.ner.model.tok2vec.encode]
 
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  [components.tok2vec.model.embed]
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  @architectures = "spacy.MultiHashEmbed.v2"
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  width = ${components.tok2vec.model.encode:width}
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  {
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  "lang":"el",
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  "description":"Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler.",
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  "author":"Explosion",
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  "email":"contact@explosion.ai",
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