adrianeboyd
commited on
Commit
·
639eb72
1
Parent(s):
75d5e95
Update spaCy pipeline
Browse files- README.md +27 -27
- accuracy.json +182 -182
- config.cfg +2 -0
- lemmatizer/model +1 -1
- lemmatizer/trees +0 -0
- meta.json +185 -185
- morphologizer/cfg +1 -0
- morphologizer/model +1 -1
- ner/model +1 -1
- parser/model +1 -1
- senter/model +1 -1
- sv_core_news_lg-any-py3-none-any.whl +2 -2
- tagger/cfg +1 -0
- tagger/model +1 -1
- tok2vec/model +1 -1
- tokenizer +0 -0
- 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/sv#sv_core_news_lg
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@@ -78,8 +78,8 @@ Swedish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
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| Feature | Description |
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| --- | --- |
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| **Name** | `sv_core_news_lg` |
|
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-
| **Version** | `3.
|
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-
| **spaCy** | `>=3.
|
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| **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
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| **Vectors** | floret (200000, 300) |
|
@@ -110,18 +110,18 @@ Swedish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
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| `TOKEN_P` | 99.95 |
|
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| `TOKEN_R` | 99.96 |
|
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| `TOKEN_F` | 99.95 |
|
113 |
-
| `TAG_ACC` | 95.
|
114 |
-
| `POS_ACC` | 96.
|
115 |
-
| `MORPH_ACC` | 95.
|
116 |
-
| `MORPH_MICRO_P` | 97.
|
117 |
-
| `MORPH_MICRO_R` | 97.
|
118 |
-
| `MORPH_MICRO_F` | 97.
|
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-
| `SENTS_P` | 92.
|
120 |
-
| `SENTS_R` |
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-
| `SENTS_F` | 93.
|
122 |
-
| `DEP_UAS` | 83.
|
123 |
-
| `DEP_LAS` | 78.
|
124 |
-
| `LEMMA_ACC` | 95.
|
125 |
-
| `ENTS_P` | 86.
|
126 |
-
| `ENTS_R` | 76.
|
127 |
-
| `ENTS_F` | 80.
|
|
|
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metrics:
|
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- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.8605993951
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.7615571776
|
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- name: NER F Score
|
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type: f_score
|
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+
value: 0.8080547309
|
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- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9534551393
|
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: 0.9635602736
|
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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
|
44 |
+
value: 0.9586608145
|
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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
|
50 |
type: accuracy
|
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+
value: 0.9559048688
|
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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: 0.8310026609
|
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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: 0.7857102417
|
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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: 0.9398058252
|
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---
|
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### Details: https://spacy.io/models/sv#sv_core_news_lg
|
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|
|
|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `sv_core_news_lg` |
|
81 |
+
| **Version** | `3.6.0` |
|
82 |
+
| **spaCy** | `>=3.6.0,<3.7.0` |
|
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| **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | floret (200000, 300) |
|
|
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| `TOKEN_P` | 99.95 |
|
111 |
| `TOKEN_R` | 99.96 |
|
112 |
| `TOKEN_F` | 99.95 |
|
113 |
+
| `TAG_ACC` | 95.35 |
|
114 |
+
| `POS_ACC` | 96.36 |
|
115 |
+
| `MORPH_ACC` | 95.87 |
|
116 |
+
| `MORPH_MICRO_P` | 97.83 |
|
117 |
+
| `MORPH_MICRO_R` | 97.45 |
|
118 |
+
| `MORPH_MICRO_F` | 97.64 |
|
119 |
+
| `SENTS_P` | 92.02 |
|
120 |
+
| `SENTS_R` | 96.03 |
|
121 |
+
| `SENTS_F` | 93.98 |
|
122 |
+
| `DEP_UAS` | 83.10 |
|
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+
| `DEP_LAS` | 78.57 |
|
124 |
+
| `LEMMA_ACC` | 95.59 |
|
125 |
+
| `ENTS_P` | 86.06 |
|
126 |
+
| `ENTS_R` | 76.16 |
|
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+
| `ENTS_F` | 80.81 |
|
accuracy.json
CHANGED
@@ -3,264 +3,264 @@
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@@ -283,51 +283,51 @@
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config.cfg
CHANGED
@@ -46,6 +46,7 @@ upstream = "tok2vec"
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|
46 |
[components.morphologizer]
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47 |
factory = "morphologizer"
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48 |
extend = false
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|
|
49 |
overwrite = true
|
50 |
scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
|
51 |
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@@ -143,6 +144,7 @@ maxout_pieces = 2
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|
143 |
|
144 |
[components.tagger]
|
145 |
factory = "tagger"
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|
146 |
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148 |
scorer = {"@scorers":"spacy.tagger_scorer.v1"}
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|
|
46 |
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47 |
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49 |
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label_smoothing = 0.0
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[components.tagger]
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label_smoothing = 0.0
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148 |
neg_prefix = "!"
|
149 |
overwrite = false
|
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lemmatizer/model
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|
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lemmatizer/trees
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meta.json
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