Update spacy pipeline to 3.5.3

README.md

@@ -14,74 +14,74 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.909059294
+      value: 0.9121680264
     - name: NER Recall
       type: recall
-      value: 0.9191279887
+      value: 0.9238748242
     - name: NER F Score
       type: f_score
-      value: 0.9140659149
+      value: 0.9179841034
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9817207388
+      value: 0.9831092397
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.979902383
+      value: 0.9825350495
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9645403646
+      value: 0.9674610011
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.986030045
+      value: 0.9882307913
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9078903297
+      value: 0.8952581463
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8674641148
+      value: 0.8520574163
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9966555184
+      value: 0.9933184855
 ---
 Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `hu_core_news_trf` |
-| **Version** | `3.5.2` |
+| **Version** | `3.5.3` |
 | **spaCy** | `>=3.5.0,<3.6.0` |
 | **Default Pipeline** | `transformer`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `trainable_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
 | **Components** | `transformer`, `senter`, `tagger`, `morphologizer`, `lookup_lemmatizer`, `trainable_lemmatizer`, `experimental_arc_predicter`, `experimental_arc_labeler`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
-| **Sources** | [UD Hungarian Szeged](https://universaldependencies.org/treebanks/hu_szeged/index.html) (Richárd Farkas, Katalin Simkó, Zsolt Szántó, Viktor Varga, Veronika Vincze (MTA-SZTE Research Group on Artificial Intelligence))<br />[NYTK-NerKor Corpus](https://github.com/nytud/NYTK-NerKor) (Eszter Simon, Noémi Vadász (Department of Language Technology and Applied Linguistics))<br />[hunNERwiki](http://hlt.sztaki.hu/resources/hunnerwiki.html) (Eszter Simon, Dávid Márk Nemeskey (HLT Group, Budapest University of Technology and Economics))<br />[Szeged NER Corpus](https://rgai.inf.u-szeged.hu/node/130) (György Szarvas, Richárd Farkas, László Felföldi, András Kocsor, János Csirik (MTA-SZTE Research Group on Artificial Intelligence))<br />[huBERT base model (cased)](https://huggingface.co/SZTAKI-HLT/hubert-base-cc) (Dávid Márk Nemeskey (SZTAKI-HLT)) |
+| **Sources** | [UD Hungarian Szeged](https://universaldependencies.org/treebanks/hu_szeged/index.html) (Richárd Farkas, Katalin Simkó, Zsolt Szántó, Viktor Varga, Veronika Vincze (MTA-SZTE Research Group on Artificial Intelligence))<br />[NYTK-NerKor Corpus](https://github.com/nytud/NYTK-NerKor) (Eszter Simon, Noémi Vadász (Department of Language Technology and Applied Linguistics))<br />[Szeged NER Corpus](https://rgai.inf.u-szeged.hu/node/130) (György Szarvas, Richárd Farkas, László Felföldi, András Kocsor, János Csirik (MTA-SZTE Research Group on Artificial Intelligence))<br />[huBERT base model (cased)](https://huggingface.co/SZTAKI-HLT/hubert-base-cc) (Dávid Márk Nemeskey (SZTAKI-HLT)) |
 | **License** | `cc-by-sa-4.0` |
 | **Author** | [SzegedAI, MILAB](https://github.com/huspacy/huspacy) |
 
@@ -108,20 +108,20 @@ Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, se
 | `TOKEN_P` | 99.86 |
 | `TOKEN_R` | 99.93 |
 | `TOKEN_F` | 99.89 |
-| `SENTS_P` | 99.78 |
-| `SENTS_R` | 99.55 |
-| `SENTS_F` | 99.67 |
-| `TAG_ACC` | 98.17 |
-| `POS_ACC` | 97.99 |
-| `MORPH_ACC` | 96.45 |
-| `MORPH_MICRO_P` | 98.67 |
-| `MORPH_MICRO_R` | 98.29 |
-| `MORPH_MICRO_F` | 98.48 |
-| `LEMMA_ACC` | 98.60 |
-| `BOUND_DEP_LAS` | 86.74 |
-| `BOUND_DEP_UAS` | 90.77 |
-| `DEP_UAS` | 90.79 |
-| `DEP_LAS` | 86.75 |
-| `ENTS_P` | 90.91 |
-| `ENTS_R` | 91.91 |
-| `ENTS_F` | 91.41 |
+| `SENTS_P` | 99.33 |
+| `SENTS_R` | 99.33 |
+| `SENTS_F` | 99.33 |
+| `TAG_ACC` | 98.31 |
+| `POS_ACC` | 98.25 |
+| `MORPH_ACC` | 96.75 |
+| `MORPH_MICRO_P` | 98.81 |
+| `MORPH_MICRO_R` | 98.58 |
+| `MORPH_MICRO_F` | 98.69 |
+| `LEMMA_ACC` | 98.82 |
+| `BOUND_DEP_LAS` | 85.22 |
+| `BOUND_DEP_UAS` | 89.54 |
+| `DEP_UAS` | 89.53 |
+| `DEP_LAS` | 85.21 |
+| `ENTS_P` | 91.22 |
+| `ENTS_R` | 92.39 |
+| `ENTS_F` | 91.80 |

config.cfg

@@ -1,8 +1,8 @@
 [paths]
-tagger_model = "models/hu_core_news_trf-tagger-3.5.2/model-best"
-parser_model = "models/hu_core_news_trf-parser-3.5.2/model-best"
-ner_model = "models/hu_core_news_trf-ner-3.5.2/model-best"
-lemmatizer_lookups = "models/hu_core_news_trf-lookup-lemmatizer-3.5.2"
+tagger_model = "models/hu_core_news_trf-tagger-3.5.3/model-best"
+parser_model = "models/hu_core_news_trf-parser-3.5.3/model-best"
+ner_model = "models/hu_core_news_trf-ner-3.5.3/model-best"
+lemmatizer_lookups = "models/hu_core_news_trf-lookup-lemmatizer-3.5.3"
 train = null
 dev = null
 vectors = null

experimental_arc_labeler/model

@@ -1,3 +1,3 @@
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experimental_arc_predicter/model

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hu_core_news_trf-any-py3-none-any.whl

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meta.json

@@ -1,7 +1,7 @@
 {
   "lang":"hu",
   "name":"core_news_trf",
-  "version":"3.5.2",
+  "version":"3.5.3",
   "description":"Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner",
   "author":"SzegedAI, MILAB",
   "email":"[email protected]",
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