Update spacy pipeline to 3.7.0
Browse files- README.md +21 -21
- hu_core_news_md-any-py3-none-any.whl +2 -2
- lookup_lemmatizer/lookups.bin +2 -2
- meta.json +182 -177
- morphologizer/model +1 -1
- ner/model +1 -1
- parser/model +1 -1
- senter/model +1 -1
- tagger/model +1 -1
- tok2vec/model +1 -1
- trainable_lemmatizer/cfg +453 -457
- trainable_lemmatizer/model +2 -2
- trainable_lemmatizer/trees +0 -0
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,34 +14,34 @@ 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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@@ -55,21 +55,21 @@ model-index:
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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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Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner
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@@ -108,18 +108,18 @@ Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morpholog
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| `TOKEN_P` | 99.86 |
|
109 |
| `TOKEN_R` | 99.93 |
|
110 |
| `TOKEN_F` | 99.89 |
|
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-
| `SENTS_P` | 97.
|
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| `SENTS_R` | 97.33 |
|
113 |
-
| `SENTS_F` | 97.
|
114 |
-
| `TAG_ACC` | 96.
|
115 |
-
| `POS_ACC` | 96.
|
116 |
-
| `MORPH_ACC` | 94.
|
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| `MORPH_MICRO_P` | 97.64 |
|
118 |
-
| `MORPH_MICRO_R` | 96.
|
119 |
-
| `MORPH_MICRO_F` | 97.
|
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| `LEMMA_ACC` | 97.45 |
|
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-
| `DEP_UAS` |
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-
| `DEP_LAS` |
|
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-
| `ENTS_P` | 84.
|
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-
| `ENTS_R` | 83.
|
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-
| `ENTS_F` | 84.
|
|
|
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metrics:
|
15 |
- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.8441212981
|
18 |
- name: NER Recall
|
19 |
type: recall
|
20 |
+
value: 0.8368495077
|
21 |
- name: NER F Score
|
22 |
type: f_score
|
23 |
+
value: 0.8404696742
|
24 |
- task:
|
25 |
name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9696128631
|
31 |
- task:
|
32 |
name: POS
|
33 |
type: token-classification
|
34 |
metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
36 |
type: accuracy
|
37 |
+
value: 0.9688965451
|
38 |
- task:
|
39 |
name: MORPH
|
40 |
type: token-classification
|
41 |
metrics:
|
42 |
- name: Morph (UFeats) Accuracy
|
43 |
type: accuracy
|
44 |
+
value: 0.9451117385
|
45 |
- task:
|
46 |
name: LEMMA
|
47 |
type: token-classification
|
|
|
55 |
metrics:
|
56 |
- name: Unlabeled Attachment Score (UAS)
|
57 |
type: f_score
|
58 |
+
value: 0.8089662094
|
59 |
- task:
|
60 |
name: LABELED_DEPENDENCIES
|
61 |
type: token-classification
|
62 |
metrics:
|
63 |
- name: Labeled Attachment Score (LAS)
|
64 |
type: f_score
|
65 |
+
value: 0.7368831893
|
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- task:
|
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name: SENTS
|
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type: token-classification
|
69 |
metrics:
|
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- name: Sentences F-Score
|
71 |
type: f_score
|
72 |
+
value: 0.9721913237
|
73 |
---
|
74 |
Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner
|
75 |
|
|
|
108 |
| `TOKEN_P` | 99.86 |
|
109 |
| `TOKEN_R` | 99.93 |
|
110 |
| `TOKEN_F` | 99.89 |
|
111 |
+
| `SENTS_P` | 97.11 |
|
112 |
| `SENTS_R` | 97.33 |
|
113 |
+
| `SENTS_F` | 97.22 |
|
114 |
+
| `TAG_ACC` | 96.96 |
|
115 |
+
| `POS_ACC` | 96.89 |
|
116 |
+
| `MORPH_ACC` | 94.51 |
|
117 |
| `MORPH_MICRO_P` | 97.64 |
|
118 |
+
| `MORPH_MICRO_R` | 96.84 |
|
119 |
+
| `MORPH_MICRO_F` | 97.24 |
|
120 |
| `LEMMA_ACC` | 97.45 |
|
121 |
+
| `DEP_UAS` | 80.90 |
|
122 |
+
| `DEP_LAS` | 73.69 |
|
123 |
+
| `ENTS_P` | 84.41 |
|
124 |
+
| `ENTS_R` | 83.68 |
|
125 |
+
| `ENTS_F` | 84.05 |
|
hu_core_news_md-any-py3-none-any.whl
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lookup_lemmatizer/lookups.bin
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7437,
|
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|
trainable_lemmatizer/model
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trainable_lemmatizer/trees
CHANGED
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vocab/strings.json
CHANGED
@@ -1,3 +1,3 @@
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