EC2 Default User
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Commit
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Parent(s):
1d33edc
Update spaCy pipeline
Browse files- .gitattributes +1 -0
- README.md +29 -36
- accuracy.json +205 -205
- attribute_ruler/patterns +0 -0
- config.cfg +8 -5
- en_core_web_md-any-py3-none-any.whl +2 -2
- meta.json +208 -212
- ner/model +2 -2
- parser/model +1 -1
- parser/moves +1 -1
- senter/model +2 -2
- tagger/cfg +1 -0
- tagger/model +2 -2
- tok2vec/model +2 -2
- tokenizer +0 -0
- vocab/key2row +0 -0
- vocab/strings.json +2 -2
- vocab/vectors +1 -1
.gitattributes
CHANGED
@@ -19,3 +19,4 @@
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*strings.json filter=lfs diff=lfs merge=lfs -text
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vectors filter=lfs diff=lfs merge=lfs -text
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model filter=lfs diff=lfs merge=lfs -text
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*strings.json filter=lfs diff=lfs merge=lfs -text
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vectors filter=lfs diff=lfs merge=lfs -text
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model filter=lfs diff=lfs merge=lfs -text
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+
*key2row filter=lfs diff=lfs merge=lfs -text
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README.md
CHANGED
@@ -14,47 +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.
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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:
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type: token-classification
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metrics:
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-
- name:
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type: accuracy
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-
value: 0.
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- task:
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-
name:
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type: token-classification
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metrics:
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-
- name:
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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.
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- task:
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-
name:
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type: token-classification
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metrics:
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-
- name:
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-
type:
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-
value: 0.
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- task:
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-
name:
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type: token-classification
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metrics:
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-
- name:
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type:
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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 +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_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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@@ -76,13 +70,12 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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<details>
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-
<summary>View label scheme (
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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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@@ -95,12 +88,12 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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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.
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-
| `SENTS_P` | 91.
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| `SENTS_R` | 89.
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| `SENTS_F` | 90.
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| `DEP_UAS` | 91.
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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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metrics:
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- name: NER Precision
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type: precision
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+
value: 0.8511198946
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- name: NER Recall
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type: recall
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value: 0.8411458333
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- name: NER F Score
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type: f_score
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value: 0.8461034709
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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: 0.9730543186
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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: 0.9190946961
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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: 0.9007569337
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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: 0.9055959278
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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** | `3.3.0` |
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| **spaCy** | `>=3.3.0.dev0,<3.4.0` |
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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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<details>
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<summary>View label scheme (112 labels for 3 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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| **`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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| `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` | 97.31 |
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+
| `SENTS_P` | 91.97 |
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+
| `SENTS_R` | 89.19 |
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| `SENTS_F` | 90.56 |
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+
| `DEP_UAS` | 91.91 |
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+
| `DEP_LAS` | 90.08 |
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+
| `ENTS_P` | 85.11 |
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| `ENTS_R` | 84.11 |
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| `ENTS_F` | 84.61 |
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accuracy.json
CHANGED
@@ -1,330 +1,330 @@
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{
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-
"token_acc": 0.
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"dep_las": 0.
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"dep_las_per_type": {
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"ents_per_type": {
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"DATE": {
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"GPE": {
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"ORDINAL": {
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"PERSON": {
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"ORG": {
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|
attribute_ruler/patterns
CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
|
|
config.cfg
CHANGED
@@ -55,7 +55,7 @@ nO = null
|
|
55 |
@architectures = "spacy.MultiHashEmbed.v2"
|
56 |
width = 96
|
57 |
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
58 |
-
rows = [5000,
|
59 |
include_static_vectors = true
|
60 |
|
61 |
[components.ner.model.tok2vec.encode]
|
@@ -93,8 +93,9 @@ overwrite = false
|
|
93 |
scorer = {"@scorers":"spacy.senter_scorer.v1"}
|
94 |
|
95 |
[components.senter.model]
|
96 |
-
@architectures = "spacy.Tagger.
|
97 |
nO = null
|
|
|
98 |
|
99 |
[components.senter.model.tok2vec]
|
100 |
@architectures = "spacy.Tok2Vec.v2"
|
@@ -115,12 +116,14 @@ maxout_pieces = 2
|
|
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.
|
123 |
nO = null
|
|
|
124 |
|
125 |
[components.tagger.model.tok2vec]
|
126 |
@architectures = "spacy.Tok2VecListener.v1"
|
@@ -137,7 +140,7 @@ factory = "tok2vec"
|
|
137 |
@architectures = "spacy.MultiHashEmbed.v2"
|
138 |
width = ${components.tok2vec.model.encode:width}
|
139 |
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
140 |
-
rows = [5000,
|
141 |
include_static_vectors = true
|
142 |
|
143 |
[components.tok2vec.model.encode]
|
@@ -174,7 +177,7 @@ dropout = 0.1
|
|
174 |
accumulate_gradient = 1
|
175 |
patience = 5000
|
176 |
max_epochs = 0
|
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