osanseviero
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Commit
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Parent(s):
b7db18e
Update spaCy pipeline
Browse files- README.md +38 -19
- accuracy.json +204 -201
- attribute_ruler/patterns +0 -0
- config.cfg +29 -31
- en_core_web_md-any-py3-none-any.whl +2 -2
- meta.json +207 -204
- ner/model +2 -2
- parser/model +1 -1
- senter/cfg +1 -1
- senter/model +2 -2
- tagger/cfg +2 -1
- tagger/model +1 -1
- tok2vec/model +2 -2
- tokenizer +0 -0
- vocab/strings.json +2 -2
- vocab/vectors.cfg +3 -0
README.md
CHANGED
@@ -14,47 +14,47 @@ 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.
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- name: NER Recall
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type: recall
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value: 0.
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- name: NER F Score
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type: f_score
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value: 0.
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS Accuracy
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type: accuracy
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value: 0.
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- task:
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name: SENTER
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type: token-classification
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metrics:
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- name: SENTER Precision
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type: precision
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value: 0.
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- name: SENTER Recall
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type: recall
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-
value: 0.
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- name: SENTER F Score
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type: f_score
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value: 0.
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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 Dependencies Accuracy
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type: accuracy
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value: 0.
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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 Dependencies Accuracy
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type: accuracy
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value: 0.
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---
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### Details: https://spacy.io/models/en#en_core_web_md
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@@ -63,8 +63,8 @@ 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_md` |
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| **Version** | `3.
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| **spaCy** | `>=3.
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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** | 684830 keys, 20000 unique vectors (300 dimensions) |
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| **License** | `MIT` |
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| **Author** | [Explosion](https://explosion.ai) |
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### Accuracy
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| Type | Score |
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| --- | --- |
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| `TOKEN_ACC` | 99.93 |
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| `
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| `DEP_UAS` | 91.87 |
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| `DEP_LAS` | 90.
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| `ENTS_P` | 85.
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| `ENTS_R` | 84.
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| `ENTS_F` | 84.
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| `SENTS_P` | 90.49 |
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| `SENTS_R` | 88.01 |
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| `SENTS_F` | 89.24 |
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metrics:
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- name: NER Precision
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type: precision
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value: 0.8531330602
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- name: NER Recall
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type: recall
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value: 0.8448016827
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- name: NER F Score
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type: f_score
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value: 0.8489469314
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS Accuracy
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type: accuracy
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+
value: 0.9736958159
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- task:
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name: SENTER
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type: token-classification
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metrics:
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- name: SENTER Precision
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type: precision
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+
value: 0.9144345238
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- name: SENTER Recall
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type: recall
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+
value: 0.8918134442
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- name: SENTER F Score
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type: f_score
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value: 0.9029823331
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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 Dependencies Accuracy
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type: accuracy
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value: 0.9186827918
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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 Dependencies Accuracy
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type: accuracy
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value: 0.9186827918
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---
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### Details: https://spacy.io/models/en#en_core_web_md
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| Feature | Description |
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| --- | --- |
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| **Name** | `en_core_web_md` |
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| **Version** | `3.2.0` |
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| **spaCy** | `>=3.2.0,<3.3.0` |
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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** | 684830 keys, 20000 unique vectors (300 dimensions) |
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| **License** | `MIT` |
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| **Author** | [Explosion](https://explosion.ai) |
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### Label Scheme
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<details>
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<summary>View label scheme (114 labels for 4 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`tagger`** | `$`, `''`, `,`, `-LRB-`, `-RRB-`, `.`, `:`, `ADD`, `AFX`, `CC`, `CD`, `DT`, `EX`, `FW`, `HYPH`, `IN`, `JJ`, `JJR`, `JJS`, `LS`, `MD`, `NFP`, `NN`, `NNP`, `NNPS`, `NNS`, `PDT`, `POS`, `PRP`, `PRP$`, `RB`, `RBR`, `RBS`, `RP`, `SYM`, `TO`, `UH`, `VB`, `VBD`, `VBG`, `VBN`, `VBP`, `VBZ`, `WDT`, `WP`, `WP$`, `WRB`, `XX`, ```` |
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| **`parser`** | `ROOT`, `acl`, `acomp`, `advcl`, `advmod`, `agent`, `amod`, `appos`, `attr`, `aux`, `auxpass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `csubj`, `csubjpass`, `dative`, `dep`, `det`, `dobj`, `expl`, `intj`, `mark`, `meta`, `neg`, `nmod`, `npadvmod`, `nsubj`, `nsubjpass`, `nummod`, `oprd`, `parataxis`, `pcomp`, `pobj`, `poss`, `preconj`, `predet`, `prep`, `prt`, `punct`, `quantmod`, `relcl`, `xcomp` |
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| **`senter`** | `I`, `S` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
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</details>
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### Accuracy
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| 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 |
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| `TAG_ACC` | 97.37 |
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| `SENTS_P` | 91.44 |
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| `SENTS_R` | 89.18 |
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| `SENTS_F` | 90.30 |
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| `DEP_UAS` | 91.87 |
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| `DEP_LAS` | 90.07 |
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| `ENTS_P` | 85.31 |
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| `ENTS_R` | 84.48 |
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| `ENTS_F` | 84.89 |
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accuracy.json
CHANGED
@@ -1,327 +1,330 @@
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{
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"token_acc": 0.9993053983,
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"speed": 9590.7931710533,
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"CARDINAL": {
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|
attribute_ruler/patterns
CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
|
|
config.cfg
CHANGED
@@ -1,10 +1,8 @@
|
|
1 |
[paths]
|
2 |
-
train =
|
3 |
-
dev =
|
4 |
-
vectors =
|
5 |
-
raw = null
|
6 |
init_tok2vec = null
|
7 |
-
vocab_data = null
|
8 |
|
9 |
[system]
|
10 |
gpu_allocator = null
|
@@ -24,6 +22,7 @@ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
|
|
24 |
|
25 |
[components.attribute_ruler]
|
26 |
factory = "attribute_ruler"
|
|
|
27 |
validate = false
|
28 |
|
29 |
[components.lemmatizer]
|
@@ -31,11 +30,13 @@ factory = "lemmatizer"
|
|
31 |
mode = "rule"
|
32 |
model = null
|
33 |
overwrite = false
|
|
|
34 |
|
35 |
[components.ner]
|
36 |
factory = "ner"
|
37 |
incorrect_spans_key = null
|
38 |
moves = null
|
|
|
39 |
update_with_oracle_cut_size = 100
|
40 |
|
41 |
[components.ner.model]
|
@@ -53,8 +54,8 @@ nO = null
|
|
53 |
[components.ner.model.tok2vec.embed]
|
54 |
@architectures = "spacy.MultiHashEmbed.v2"
|
55 |
width = 96
|
56 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
|
57 |
-
rows = [5000,2500,2500,2500]
|
58 |
include_static_vectors = true
|
59 |
|
60 |
[components.ner.model.tok2vec.encode]
|
@@ -69,6 +70,7 @@ factory = "parser"
|
|
69 |
learn_tokens = false
|
70 |
min_action_freq = 30
|
71 |
moves = null
|
|
|
72 |
update_with_oracle_cut_size = 100
|
73 |
|
74 |
[components.parser.model]
|
@@ -87,6 +89,8 @@ upstream = "tok2vec"
|
|
87 |
|
88 |
[components.senter]
|
89 |
factory = "senter"
|
|
|
|
|
90 |
|
91 |
[components.senter.model]
|
92 |
@architectures = "spacy.Tagger.v1"
|
@@ -98,8 +102,8 @@ nO = null
|
|
98 |
[components.senter.model.tok2vec.embed]
|
99 |
@architectures = "spacy.MultiHashEmbed.v2"
|
100 |
width = 16
|
101 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
|
102 |
-
rows = [1000,500,500,500]
|
103 |
include_static_vectors = true
|
104 |
|
105 |
[components.senter.model.tok2vec.encode]
|
@@ -111,6 +115,8 @@ maxout_pieces = 2
|
|
111 |
|
112 |
[components.tagger]
|
113 |
factory = "tagger"
|
|
|
|
|
114 |
|
115 |
[components.tagger.model]
|
116 |
@architectures = "spacy.Tagger.v1"
|
@@ -130,8 +136,8 @@ factory = "tok2vec"
|
|
130 |
[components.tok2vec.model.embed]
|
131 |
@architectures = "spacy.MultiHashEmbed.v2"
|
132 |
width = ${components.tok2vec.model.encode:width}
|
133 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
|
134 |
-
rows = [5000,2500,2500,2500]
|
135 |
include_static_vectors = true
|
136 |
|
137 |
[components.tok2vec.model.encode]
|
@@ -145,27 +151,19 @@ maxout_pieces = 3
|
|
145 |
|
146 |
[corpora.dev]
|
147 |
@readers = "spacy.Corpus.v1"
|
148 |
-
|
149 |
-
max_length = 0
|
150 |
-
path = ${paths:dev}
|
151 |
gold_preproc = false
|
|
|
|
|
152 |
augmenter = null
|
153 |
|
154 |
[corpora.train]
|
155 |
@readers = "spacy.Corpus.v1"
|
156 |
-
path = ${paths
|
157 |
-
max_length = 5000
|
158 |
gold_preproc = false
|
|
|
159 |
limit = 0
|
160 |
-
|
161 |
-
[corpora.train.augmenter]
|
162 |
-
@augmenters = "spacy.orth_variants.v1"
|
163 |
-
level = 0.2
|
164 |
-
lower = 0.5
|
165 |
-
|
166 |
-
[corpora.train.augmenter.orth_variants]
|
167 |
-
@readers = "srsly.read_json.v1"
|
168 |
-
path = "assets/orth_variants.json"
|
169 |
|
170 |
[training]
|
171 |
train_corpus = "corpora.train"
|
@@ -196,9 +194,8 @@ compound = 1.001
|
|
196 |
t = 0.0
|
197 |
|
198 |
[training.logger]
|
199 |
-
@loggers = "spacy.
|
200 |
-
|
201 |
-
remove_config_values = []
|
202 |
|
203 |
[training.optimizer]
|
204 |
@optimizers = "Adam.v1"
|
@@ -219,16 +216,17 @@ dep_las_per_type = null
|
|
219 |
sents_p = null
|
220 |
sents_r = null
|
221 |
sents_f = 0.02
|
222 |
-
lemma_acc = 0.
|
223 |
-
ents_f = 0.
|
224 |
ents_p = 0.0
|
225 |
ents_r = 0.0
|
226 |
ents_per_type = null
|
|
|
227 |
|
228 |
[pretraining]
|
229 |
|
230 |
[initialize]
|
231 |
-
vocab_data =
|
232 |
vectors = ${paths.vectors}
|
233 |
init_tok2vec = ${paths.init_tok2vec}
|
234 |
before_init = null
|
|
|
1 |
[paths]
|
2 |
+
train = null
|
3 |
+
dev = null
|
4 |
+
vectors = null
|
|
|
5 |
init_tok2vec = null
|
|
|
6 |
|
7 |
[system]
|
8 |
gpu_allocator = null
|
|
|
22 |
|
23 |
[components.attribute_ruler]
|
24 |
factory = "attribute_ruler"
|
25 |
+
scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
|
26 |
validate = false
|
27 |
|
28 |
[components.lemmatizer]
|
|
|
30 |
mode = "rule"
|
31 |
model = null
|
32 |
overwrite = false
|
33 |
+
scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
|
34 |
|
35 |
[components.ner]
|
36 |
factory = "ner"
|
37 |
incorrect_spans_key = null
|
38 |
moves = null
|
39 |
+
scorer = {"@scorers":"spacy.ner_scorer.v1"}
|
40 |
update_with_oracle_cut_size = 100
|
41 |
|
42 |
[components.ner.model]
|
|
|
54 |
[components.ner.model.tok2vec.embed]
|
55 |
@architectures = "spacy.MultiHashEmbed.v2"
|
56 |
width = 96
|
57 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
58 |
+
rows = [5000,2500,2500,2500,100]
|
59 |
include_static_vectors = true
|
60 |
|
61 |
[components.ner.model.tok2vec.encode]
|
|
|
70 |
learn_tokens = false
|
71 |
min_action_freq = 30
|
72 |
moves = null
|
73 |
+
scorer = {"@scorers":"spacy.parser_scorer.v1"}
|
74 |
update_with_oracle_cut_size = 100
|
75 |
|
76 |
[components.parser.model]
|
|
|
89 |
|
90 |
[components.senter]
|
91 |
factory = "senter"
|
92 |
+
overwrite = false
|
93 |
+
scorer = {"@scorers":"spacy.senter_scorer.v1"}
|
94 |
|
95 |
[components.senter.model]
|
96 |
@architectures = "spacy.Tagger.v1"
|
|
|
102 |
[components.senter.model.tok2vec.embed]
|
103 |
@architectures = "spacy.MultiHashEmbed.v2"
|
104 |
width = 16
|
105 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
106 |
+
rows = [1000,500,500,500,50]
|
107 |
include_static_vectors = true
|
108 |
|
109 |
[components.senter.model.tok2vec.encode]
|
|
|
115 |
|
116 |
[components.tagger]
|
117 |
factory = "tagger"
|
118 |
+
overwrite = false
|
119 |
+
scorer = {"@scorers":"spacy.tagger_scorer.v1"}
|
120 |
|
121 |
[components.tagger.model]
|
122 |
@architectures = "spacy.Tagger.v1"
|
|
|
136 |
[components.tok2vec.model.embed]
|
137 |
@architectures = "spacy.MultiHashEmbed.v2"
|
138 |
width = ${components.tok2vec.model.encode:width}
|
139 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
140 |
+
rows = [5000,2500,2500,2500,100]
|
141 |
include_static_vectors = true
|
142 |
|
143 |
[components.tok2vec.model.encode]
|
|
|
151 |
|
152 |
[corpora.dev]
|
153 |
@readers = "spacy.Corpus.v1"
|
154 |
+
path = ${paths.dev}
|
|
|
|
|
155 |
gold_preproc = false
|
156 |
+
max_length = 0
|
157 |
+
limit = 0
|
158 |
augmenter = null
|
159 |
|
160 |
[corpora.train]
|
161 |
@readers = "spacy.Corpus.v1"
|
162 |
+
path = ${paths.train}
|
|
|
163 |
gold_preproc = false
|
164 |
+
max_length = 0
|
165 |
limit = 0
|
166 |
+
augmenter = null
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
167 |
|
168 |
[training]
|
169 |
train_corpus = "corpora.train"
|
|
|
194 |
t = 0.0
|
195 |
|
196 |
[training.logger]
|
197 |
+
@loggers = "spacy.ConsoleLogger.v1"
|
198 |
+
progress_bar = false
|
|
|
199 |
|
200 |
[training.optimizer]
|
201 |
@optimizers = "Adam.v1"
|
|
|
216 |
sents_p = null
|
217 |
sents_r = null
|
218 |
sents_f = 0.02
|
219 |
+
lemma_acc = 0.5
|
220 |
+
ents_f = 0.16
|
221 |
ents_p = 0.0
|
222 |
ents_r = 0.0
|
223 |
ents_per_type = null
|
224 |
+
speed = 0.0
|
225 |
|
226 |
[pretraining]
|
227 |
|
228 |
[initialize]
|
229 |
+
vocab_data = null
|
230 |
vectors = ${paths.vectors}
|
231 |
init_tok2vec = ${paths.init_tok2vec}
|
232 |
before_init = null
|
en_core_web_md-any-py3-none-any.whl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
-
size
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9728ab892904819567e70720a3887b59ded8721f14cc27b3d13273ad2b8ba458
|
3 |
+
size 45684441
|
meta.json
CHANGED
@@ -1,14 +1,14 @@
|
|
1 |
{
|
2 |
"lang":"en",
|
3 |
"name":"core_web_md",
|
4 |
-
"version":"3.
|
5 |
"description":"English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.",
|
6 |
"author":"Explosion",
|
7 |
"email":"contact@explosion.ai",
|
8 |
"url":"https://explosion.ai",
|
9 |
"license":"MIT",
|
10 |
-
"spacy_version":">=3.
|
11 |
-
"spacy_git_version":"
|
12 |
"vectors":{
|
13 |
"width":300,
|
14 |
"vectors":20000,
|
@@ -170,330 +170,333 @@
|
|
170 |
],
|
171 |
"performance":{
|
172 |
"token_acc":0.9993053983,
|
173 |
-
"
|
174 |
-
"
|
175 |
-
"
|
176 |
-
"
|
177 |
-
"
|
178 |
-
"
|
179 |
-
"
|
180 |
-
"
|
181 |
-
"
|
182 |
-
"speed":9590.7931710533,
|
183 |
"dep_las_per_type":{
|
184 |
"prep":{
|
185 |
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"p":0.
|
186 |
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187 |
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"f":0.
|
188 |
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|
189 |
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190 |
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191 |
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"r":0.
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192 |
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|
193 |
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|
194 |
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195 |
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"p":0.
|
196 |
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|
197 |
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|
198 |
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|
199 |
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|
200 |
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"p":0.
|
201 |
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|
202 |
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|
203 |
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|
204 |
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205 |
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206 |
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207 |
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208 |
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209 |
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|
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214 |
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215 |
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216 |
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217 |
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|
218 |
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|
219 |
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220 |
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221 |
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222 |
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223 |
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|
224 |
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225 |
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226 |
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|
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|
229 |
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231 |
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232 |
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|
234 |
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235 |
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236 |
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|
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|
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|
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"EVENT":{
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|
|
1 |
+
{
|
2 |
+
"mode":"default"
|
3 |
+
}
|