a100 commited on
Commit
6598217
1 Parent(s): b8dc3de

Update spacy pipeline to 3.2.1

Browse files
README.md CHANGED
@@ -14,69 +14,69 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.9073426573
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  - name: NER Recall
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  type: recall
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- value: 0.9124472574
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  - name: NER F Score
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  type: f_score
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- value: 0.909887798
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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: 0.9726289597
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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: 0.9720547421
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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: 0.9359747344
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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: 0.9856473065
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  - task:
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  name: UNLABELED_DEPENDENCIES
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  type: token-classification
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  metrics:
56
  - name: Unlabeled Attachment Score (UAS)
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  type: f_score
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- value: 0.9141544645
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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: 0.8754485861
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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: 0.9888641425
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  ---
74
  Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner
75
 
76
  | Feature | Description |
77
  | --- | --- |
78
  | **Name** | `hu_core_news_trf` |
79
- | **Version** | `3.2.0b4` |
80
  | **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` |
@@ -109,20 +109,20 @@ Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, se
109
  | `TOKEN_P` | 99.86 |
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  | `TOKEN_R` | 99.93 |
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  | `TOKEN_F` | 99.89 |
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- | `SENTS_P` | 98.89 |
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- | `SENTS_R` | 98.89 |
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- | `SENTS_F` | 98.89 |
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- | `TAG_ACC` | 97.26 |
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- | `POS_ACC` | 97.21 |
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- | `MORPH_ACC` | 93.60 |
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- | `MORPH_MICRO_P` | 97.69 |
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- | `MORPH_MICRO_R` | 96.98 |
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- | `MORPH_MICRO_F` | 97.33 |
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- | `LEMMA_ACC` | 98.56 |
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- | `BOUND_DEP_LAS` | 87.53 |
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- | `BOUND_DEP_UAS` | 91.40 |
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- | `DEP_UAS` | 91.42 |
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- | `DEP_LAS` | 87.54 |
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- | `ENTS_P` | 90.73 |
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- | `ENTS_R` | 91.24 |
128
- | `ENTS_F` | 90.99 |
 
14
  metrics:
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  - name: NER Precision
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  type: precision
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+ 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
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  - task:
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  name: TAG
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  type: token-classification
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  metrics:
28
  - name: TAG (XPOS) Accuracy
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  type: accuracy
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+ value: 0.9738730979
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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: 0.973777395
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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: 0.9364532491
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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: 0.9863170988
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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: 0.911718264
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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
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  - task:
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  name: SENTS
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  type: token-classification
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  metrics:
70
  - name: Sentences F-Score
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  type: f_score
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+ value: 0.986636971
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  ---
74
  Hungarian transformer pipeline (huBert) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner
75
 
76
  | Feature | Description |
77
  | --- | --- |
78
  | **Name** | `hu_core_news_trf` |
79
+ | **Version** | `3.2.1` |
80
  | **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` |
 
109
  | `TOKEN_P` | 99.86 |
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  | `TOKEN_R` | 99.93 |
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  | `TOKEN_F` | 99.89 |
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+ | `SENTS_P` | 98.66 |
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+ | `SENTS_R` | 98.66 |
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+ | `SENTS_F` | 98.66 |
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+ | `TAG_ACC` | 97.39 |
116
+ | `POS_ACC` | 97.38 |
117
+ | `MORPH_ACC` | 93.65 |
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+ | `MORPH_MICRO_P` | 97.75 |
119
+ | `MORPH_MICRO_R` | 97.09 |
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+ | `MORPH_MICRO_F` | 97.42 |
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+ | `LEMMA_ACC` | 98.63 |
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+ | `BOUND_DEP_LAS` | 87.15 |
123
+ | `BOUND_DEP_UAS` | 91.19 |
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+ | `DEP_UAS` | 91.17 |
125
+ | `DEP_LAS` | 87.13 |
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+ | `ENTS_P` | 90.78 |
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+ | `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-3.2.0b4/model-best"
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- parser_model = "models/hu_core_news_trf-parser-3.2.0b4/model-best"
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- ner_model = "models/hu_core_news_trf-ner-3.2.0b4/model-best"
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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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  dev = null
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meta.json CHANGED
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  "lang":"hu",
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  "name":"core_news_trf",
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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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  "email":"[email protected]",
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