a100
commited on
Commit
•
6598217
1
Parent(s):
b8dc3de
Update spacy pipeline to 3.2.1
Browse files- README.md +28 -28
- config.cfg +3 -3
- experimental_arc_labeler/model +1 -1
- experimental_arc_predicter/model +1 -1
- experimental_edit_tree_lemmatizer/model +1 -1
- hu_core_news_trf-any-py3-none-any.whl +2 -2
- meta.json +179 -179
- morphologizer/model +1 -1
- ner/model +1 -1
- senter/model +1 -1
- tagger/model +1 -1
- transformer/model +1 -1
- vocab/strings.json +2 -2
README.md
CHANGED
@@ -14,69 +14,69 @@ model-index:
|
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14 |
metrics:
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15 |
- 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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Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner
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|
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| Feature | Description |
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| --- | --- |
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| **Name** | `hu_core_news_trf` |
|
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-
| **Version** | `3.2.
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| **spaCy** | `>=3.2.4,<3.3.0` |
|
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| **Default Pipeline** | `transformer`, `senter`, `tagger`, `morphologizer`, `experimental_edit_tree_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
|
82 |
| **Components** | `transformer`, `senter`, `tagger`, `morphologizer`, `experimental_edit_tree_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
|
@@ -109,20 +109,20 @@ Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, se
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| `TOKEN_P` | 99.86 |
|
110 |
| `TOKEN_R` | 99.93 |
|
111 |
| `TOKEN_F` | 99.89 |
|
112 |
-
| `SENTS_P` | 98.
|
113 |
-
| `SENTS_R` | 98.
|
114 |
-
| `SENTS_F` | 98.
|
115 |
-
| `TAG_ACC` | 97.
|
116 |
-
| `POS_ACC` | 97.
|
117 |
-
| `MORPH_ACC` | 93.
|
118 |
-
| `MORPH_MICRO_P` | 97.
|
119 |
-
| `MORPH_MICRO_R` |
|
120 |
-
| `MORPH_MICRO_F` | 97.
|
121 |
-
| `LEMMA_ACC` | 98.
|
122 |
-
| `BOUND_DEP_LAS` | 87.
|
123 |
-
| `BOUND_DEP_UAS` | 91.
|
124 |
-
| `DEP_UAS` | 91.
|
125 |
-
| `DEP_LAS` | 87.
|
126 |
-
| `ENTS_P` | 90.
|
127 |
-
| `ENTS_R` | 91.
|
128 |
-
| `ENTS_F` |
|
|
|
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metrics:
|
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- name: NER Precision
|
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type: precision
|
17 |
+
value: 0.9078212291
|
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- name: NER Recall
|
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type: recall
|
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+
value: 0.9142053446
|
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- name: NER F Score
|
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type: f_score
|
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+
value: 0.9110021023
|
24 |
- task:
|
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name: TAG
|
26 |
type: token-classification
|
27 |
metrics:
|
28 |
- name: TAG (XPOS) Accuracy
|
29 |
type: accuracy
|
30 |
+
value: 0.9738730979
|
31 |
- task:
|
32 |
name: POS
|
33 |
type: token-classification
|
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metrics:
|
35 |
- name: POS (UPOS) Accuracy
|
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type: accuracy
|
37 |
+
value: 0.973777395
|
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: 0.9364532491
|
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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
|
51 |
+
value: 0.9863170988
|
52 |
- task:
|
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name: UNLABELED_DEPENDENCIES
|
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type: token-classification
|
55 |
metrics:
|
56 |
- name: Unlabeled Attachment Score (UAS)
|
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type: f_score
|
58 |
+
value: 0.911718264
|
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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: 0.8713458686
|
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
|
72 |
+
value: 0.986636971
|
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---
|
74 |
Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner
|
75 |
|
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| Feature | Description |
|
77 |
| --- | --- |
|
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| **Name** | `hu_core_news_trf` |
|
79 |
+
| **Version** | `3.2.1` |
|
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| **spaCy** | `>=3.2.4,<3.3.0` |
|
81 |
| **Default Pipeline** | `transformer`, `senter`, `tagger`, `morphologizer`, `experimental_edit_tree_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
|
82 |
| **Components** | `transformer`, `senter`, `tagger`, `morphologizer`, `experimental_edit_tree_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
|
|
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| `TOKEN_P` | 99.86 |
|
110 |
| `TOKEN_R` | 99.93 |
|
111 |
| `TOKEN_F` | 99.89 |
|
112 |
+
| `SENTS_P` | 98.66 |
|
113 |
+
| `SENTS_R` | 98.66 |
|
114 |
+
| `SENTS_F` | 98.66 |
|
115 |
+
| `TAG_ACC` | 97.39 |
|
116 |
+
| `POS_ACC` | 97.38 |
|
117 |
+
| `MORPH_ACC` | 93.65 |
|
118 |
+
| `MORPH_MICRO_P` | 97.75 |
|
119 |
+
| `MORPH_MICRO_R` | 97.09 |
|
120 |
+
| `MORPH_MICRO_F` | 97.42 |
|
121 |
+
| `LEMMA_ACC` | 98.63 |
|
122 |
+
| `BOUND_DEP_LAS` | 87.15 |
|
123 |
+
| `BOUND_DEP_UAS` | 91.19 |
|
124 |
+
| `DEP_UAS` | 91.17 |
|
125 |
+
| `DEP_LAS` | 87.13 |
|
126 |
+
| `ENTS_P` | 90.78 |
|
127 |
+
| `ENTS_R` | 91.42 |
|
128 |
+
| `ENTS_F` | 91.10 |
|
config.cfg
CHANGED
@@ -1,7 +1,7 @@
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[paths]
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-
tagger_model = "models/hu_core_news_trf-tagger-3.2.
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-
parser_model = "models/hu_core_news_trf-parser-3.2.
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-
ner_model = "models/hu_core_news_trf-ner-3.2.
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train = null
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dev = null
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vectors = null
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[paths]
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+
tagger_model = "models/hu_core_news_trf-tagger-3.2.1/model-best"
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+
parser_model = "models/hu_core_news_trf-parser-3.2.1/model-best"
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ner_model = "models/hu_core_news_trf-ner-3.2.1/model-best"
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train = null
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dev = null
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vectors = null
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experimental_arc_labeler/model
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experimental_arc_predicter/model
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meta.json
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{
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"lang":"hu",
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"name":"core_news_trf",
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"version":"3.2.
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"description":"Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner",
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"author":"SzegedAI, MILAB",
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