adrianeboyd
commited on
Commit
•
11e0b6c
1
Parent(s):
e4670a4
Update spaCy pipeline
Browse files- README.md +27 -27
- accuracy.json +175 -175
- config.cfg +5 -4
- it_core_news_sm-any-py3-none-any.whl +2 -2
- lemmatizer/model +1 -1
- meta.json +178 -178
- morphologizer/model +1 -1
- ner/model +2 -2
- parser/model +1 -1
- senter/model +1 -1
- tagger/model +1 -1
- tok2vec/model +2 -2
- tokenizer +1 -1
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,62 +14,62 @@ 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: 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.
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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 (UPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: MORPH
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type: token-classification
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metrics:
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- name: Morph (UFeats) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: LEMMA
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type: token-classification
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metrics:
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- name: Lemma Accuracy
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type: accuracy
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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 Attachment Score (UAS)
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type: f_score
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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 Attachment Score (LAS)
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type: f_score
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-
value: 0.
|
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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.
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---
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### Details: https://spacy.io/models/it#it_core_news_sm
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@@ -78,8 +78,8 @@ Italian pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger,
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| Feature | Description |
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| --- | --- |
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| **Name** | `it_core_news_sm` |
|
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-
| **Version** | `3.
|
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-
| **spaCy** | `>=3.
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
|
@@ -106,22 +106,22 @@ Italian pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger,
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| Type | Score |
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| --- | --- |
|
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-
| `TOKEN_ACC` | 99.
|
110 |
| `TOKEN_P` | 99.80 |
|
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| `TOKEN_R` | 99.78 |
|
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| `TOKEN_F` | 99.79 |
|
113 |
-
| `POS_ACC` |
|
114 |
-
| `MORPH_ACC` |
|
115 |
-
| `MORPH_MICRO_P` | 98.
|
116 |
-
| `MORPH_MICRO_R` | 97.
|
117 |
-
| `MORPH_MICRO_F` |
|
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-
| `TAG_ACC` | 96.
|
119 |
-
| `SENTS_P` |
|
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| `SENTS_R` | 98.23 |
|
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-
| `SENTS_F` | 97.
|
122 |
-
| `DEP_UAS` | 89.
|
123 |
-
| `DEP_LAS` | 85.
|
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-
| `LEMMA_ACC` |
|
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-
| `ENTS_P` |
|
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-
| `ENTS_R` | 85.
|
127 |
-
| `ENTS_F` | 85.
|
|
|
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metrics:
|
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- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.8600824654
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.8579197692
|
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- name: NER F Score
|
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type: f_score
|
23 |
+
value: 0.858999756
|
24 |
- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9650368506
|
31 |
- task:
|
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name: POS
|
33 |
type: token-classification
|
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metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9701163888
|
38 |
- task:
|
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name: MORPH
|
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type: token-classification
|
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metrics:
|
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- name: Morph (UFeats) Accuracy
|
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type: accuracy
|
44 |
+
value: 0.9701573034
|
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- task:
|
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name: LEMMA
|
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type: token-classification
|
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metrics:
|
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- name: Lemma Accuracy
|
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type: accuracy
|
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+
value: 0.969356578
|
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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: 0.8969952665
|
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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: 0.8575397438
|
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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: 0.9796640141
|
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---
|
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### Details: https://spacy.io/models/it#it_core_news_sm
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|
|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `it_core_news_sm` |
|
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+
| **Version** | `3.5.0` |
|
82 |
+
| **spaCy** | `>=3.5.0,<3.6.0` |
|
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
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| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
|
|
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|
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| Type | Score |
|
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| --- | --- |
|
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+
| `TOKEN_ACC` | 99.93 |
|
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| `TOKEN_P` | 99.80 |
|
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| `TOKEN_R` | 99.78 |
|
112 |
| `TOKEN_F` | 99.79 |
|
113 |
+
| `POS_ACC` | 97.01 |
|
114 |
+
| `MORPH_ACC` | 97.02 |
|
115 |
+
| `MORPH_MICRO_P` | 98.53 |
|
116 |
+
| `MORPH_MICRO_R` | 97.73 |
|
117 |
+
| `MORPH_MICRO_F` | 98.12 |
|
118 |
+
| `TAG_ACC` | 96.50 |
|
119 |
+
| `SENTS_P` | 97.71 |
|
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| `SENTS_R` | 98.23 |
|
121 |
+
| `SENTS_F` | 97.97 |
|
122 |
+
| `DEP_UAS` | 89.70 |
|
123 |
+
| `DEP_LAS` | 85.75 |
|
124 |
+
| `LEMMA_ACC` | 96.94 |
|
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+
| `ENTS_P` | 86.01 |
|
126 |
+
| `ENTS_R` | 85.79 |
|
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+
| `ENTS_F` | 85.90 |
|
accuracy.json
CHANGED
@@ -1,68 +1,68 @@
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@@ -75,77 +75,77 @@
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@@ -153,89 +153,79 @@
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@@ -263,24 +268,14 @@
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"orphan": {
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@@ -288,36 +283,41 @@
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config.cfg
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@@ -81,8 +81,8 @@ nO = null
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|
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[components.ner.model.tok2vec.embed]
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82 |
@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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87 |
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[components.ner.model.tok2vec.encode]
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rows = [5000,1000,2500,2500,50]
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[components.tok2vec.model.encode]
|
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frozen_components = []
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annotating_components = []
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|
214 |
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|
|
81 |
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172 |
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meta.json
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vocab/strings.json
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 2409677
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