adrianeboyd
commited on
Commit
•
0ff593c
1
Parent(s):
1f12b7f
Update spaCy pipeline
Browse files- README.md +28 -28
- accuracy.json +218 -218
- attribute_ruler/patterns +0 -0
- config.cfg +5 -4
- lemmatizer/model +1 -1
- meta.json +221 -221
- ner/model +2 -2
- parser/model +1 -1
- ro_core_news_lg-any-py3-none-any.whl +2 -2
- 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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14 |
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/ro#ro_core_news_lg
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|
@@ -78,8 +78,8 @@ Romanian pipeline optimized for CPU. Components: tok2vec, tagger, parser, lemmat
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| Feature | Description |
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| --- | --- |
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| **Name** | `ro_core_news_lg` |
|
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-
| **Version** | `3.
|
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-
| **spaCy** | `>=3.
|
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| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
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| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
|
@@ -105,22 +105,22 @@ Romanian pipeline optimized for CPU. Components: tok2vec, tagger, parser, lemmat
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| Type | Score |
|
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| --- | --- |
|
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-
| `TOKEN_ACC` | 99.
|
109 |
| `TOKEN_P` | 99.67 |
|
110 |
| `TOKEN_R` | 99.57 |
|
111 |
| `TOKEN_F` | 99.59 |
|
112 |
-
| `TAG_ACC` | 96.
|
113 |
-
| `SENTS_P` | 97.
|
114 |
-
| `SENTS_R` | 96.
|
115 |
-
| `SENTS_F` |
|
116 |
-
| `DEP_UAS` | 88.
|
117 |
-
| `DEP_LAS` | 83.
|
118 |
-
| `LEMMA_ACC` | 95.
|
119 |
-
| `POS_ACC` | 93.
|
120 |
-
| `MORPH_ACC` | 95.
|
121 |
-
| `MORPH_MICRO_P` | 99.
|
122 |
-
| `MORPH_MICRO_R` | 95.
|
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-
| `MORPH_MICRO_F` | 97.
|
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-
| `ENTS_P` | 75.
|
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-
| `ENTS_R` |
|
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-
| `ENTS_F` |
|
|
|
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metrics:
|
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- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.7502799552
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.7721859393
|
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- name: NER F Score
|
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type: f_score
|
23 |
+
value: 0.7610753502
|
24 |
- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9657255109
|
31 |
- task:
|
32 |
name: POS
|
33 |
type: token-classification
|
34 |
metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9395242502
|
38 |
- task:
|
39 |
name: MORPH
|
40 |
type: token-classification
|
41 |
metrics:
|
42 |
- name: Morph (UFeats) Accuracy
|
43 |
type: accuracy
|
44 |
+
value: 0.9499516228
|
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- task:
|
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name: LEMMA
|
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type: token-classification
|
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metrics:
|
49 |
- name: Lemma Accuracy
|
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type: accuracy
|
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+
value: 0.9575746914
|
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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)
|
57 |
type: f_score
|
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+
value: 0.8875784191
|
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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: 0.8359473024
|
66 |
- 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: 0.9699799867
|
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---
|
74 |
### Details: https://spacy.io/models/ro#ro_core_news_lg
|
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|
|
|
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| Feature | Description |
|
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| --- | --- |
|
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| **Name** | `ro_core_news_lg` |
|
81 |
+
| **Version** | `3.5.0` |
|
82 |
+
| **spaCy** | `>=3.5.0,<3.6.0` |
|
83 |
| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
|
84 |
| **Components** | `tok2vec`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
|
85 |
| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
|
|
|
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|
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| Type | Score |
|
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| --- | --- |
|
108 |
+
| `TOKEN_ACC` | 99.80 |
|
109 |
| `TOKEN_P` | 99.67 |
|
110 |
| `TOKEN_R` | 99.57 |
|
111 |
| `TOKEN_F` | 99.59 |
|
112 |
+
| `TAG_ACC` | 96.57 |
|
113 |
+
| `SENTS_P` | 97.32 |
|
114 |
+
| `SENTS_R` | 96.68 |
|
115 |
+
| `SENTS_F` | 97.00 |
|
116 |
+
| `DEP_UAS` | 88.76 |
|
117 |
+
| `DEP_LAS` | 83.59 |
|
118 |
+
| `LEMMA_ACC` | 95.76 |
|
119 |
+
| `POS_ACC` | 93.95 |
|
120 |
+
| `MORPH_ACC` | 95.00 |
|
121 |
+
| `MORPH_MICRO_P` | 99.05 |
|
122 |
+
| `MORPH_MICRO_R` | 95.76 |
|
123 |
+
| `MORPH_MICRO_F` | 97.04 |
|
124 |
+
| `ENTS_P` | 75.03 |
|
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+
| `ENTS_R` | 77.22 |
|
126 |
+
| `ENTS_F` | 76.11 |
|
accuracy.json
CHANGED
@@ -1,129 +1,129 @@
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@@ -304,14 +304,14 @@
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vocab/strings.json
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