Update spacy pipeline to 3.2.3

README.md

@@ -14,73 +14,73 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8500891266
+      value: 0.8669194655
     - name: NER Recall
       type: recall
-      value: 0.8384317862
+      value: 0.8440576653
     - name: NER F Score
       type: f_score
-      value: 0.844220216
+      value: 0.8553358275
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.969328676
+      value: 0.9645437581
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9660749318
+      value: 0.9641609646
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9291798258
+      value: 0.9311895875
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9654578509
+      value: 0.9638312123
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.8102173426
+      value: 0.8157554644
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.7343303646
+      value: 0.7455189077
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9766407119
+      value: 0.9776785714
 ---
 Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `hu_core_news_lg` |
-| **Version** | `3.2.1b1` |
+| **Version** | `3.2.3` |
 | **spaCy** | `>=3.2.4,<3.3.0` |
 | **Default Pipeline** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lemmatizer`, `parser`, `ner` |
 | **Components** | `tok2vec`, `senter`, `tagger`, `morphologizer`, `lemmatizer`, `parser`, `ner` |
-| **Vectors** | 1140008 keys, 1140008 unique vectors (300 dimensions) |
+| **Vectors** | 0 keys, 200000 unique vectors (300 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 />[Webcorpuswiki word2vec model](https://github.com/oroszgy/hunlp-resources/releases/tag/webcorpuswiki_word2vec_v0.1) (György Orosz) |
 | **License** | `cc-by-sa-4.0` |
 | **Author** | [SzegedAI, MILAB](https://github.com/huspacy/huspacy) |
@@ -108,18 +108,18 @@ Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morpholog
 | `TOKEN_P` | 99.86 |
 | `TOKEN_R` | 99.93 |
 | `TOKEN_F` | 99.89 |
-| `SENTS_P` | 97.56 |
-| `SENTS_R` | 97.77 |
-| `SENTS_F` | 97.66 |
-| `TAG_ACC` | 96.93 |
-| `POS_ACC` | 96.61 |
-| `MORPH_ACC` | 92.92 |
-| `MORPH_MICRO_P` | 96.82 |
-| `MORPH_MICRO_R` | 95.61 |
-| `MORPH_MICRO_F` | 96.21 |
-| `LEMMA_ACC` | 96.55 |
-| `DEP_UAS` | 81.02 |
-| `DEP_LAS` | 73.43 |
-| `ENTS_P` | 85.01 |
-| `ENTS_R` | 83.84 |
-| `ENTS_F` | 84.42 |
+| `SENTS_P` | 0.00 |
+| `SENTS_R` | 0.00 |
+| `SENTS_F` | 0.00 |
+| `TAG_ACC` | 96.17 |
+| `POS_ACC` | 96.21 |
+| `MORPH_ACC` | 92.98 |
+| `MORPH_MICRO_P` | 96.80 |
+| `MORPH_MICRO_R` | 95.85 |
+| `MORPH_MICRO_F` | 96.32 |
+| `LEMMA_ACC` | 96.01 |
+| `DEP_UAS` | 75.78 |
+| `DEP_LAS` | 68.82 |
+| `ENTS_P` | 85.95 |
+| `ENTS_R` | 85.53 |
+| `ENTS_F` | 85.74 |

config.cfg

@@ -1,7 +1,7 @@
 [paths]
-parser_model = "models/hu_core_news_lg-parser-3.2.1b1/model-best"
-lemmy_model = "models/lemmy-3.2.1b1.bin"
-ner_model = "models/hu_core_news_lg-ner_merged-3.2.1b1/model-best"
+parser_model = "models/hu_core_news_lg-parser-3.2.3/model-best"
+lemmy_model = "models/lemmy-3.2.3.bin"
+ner_model = "models/hu_core_news_lg-ner-3.2.3/model-best"
 train = null
 dev = null
 vectors = null
@@ -59,10 +59,10 @@ use_upper = true
 nO = null
 
 [components.ner.model.tok2vec]
-@architectures = "spacy.Tok2Vec.v1"
+@architectures = "spacy.Tok2Vec.v2"
 
 [components.ner.model.tok2vec.embed]
-@architectures = "spacy.MultiHashEmbed.v1"
+@architectures = "spacy.MultiHashEmbed.v2"
 width = 300
 attrs = ["LOWER","PREFIX","SUFFIX","SHAPE"]
 rows = [5000,2500,2500,2500]
@@ -130,10 +130,10 @@ upstream = "*"
 factory = "tok2vec"
 
 [components.tok2vec.model]
-@architectures = "spacy.Tok2Vec.v1"
+@architectures = "spacy.Tok2Vec.v2"
 
 [components.tok2vec.model.embed]
-@architectures = "spacy.MultiHashEmbed.v1"
+@architectures = "spacy.MultiHashEmbed.v2"
 width = 300
 attrs = ["LOWER","PREFIX","SUFFIX","SHAPE"]
 rows = [5000,2500,2500,2500]

hu_core_news_lg-any-py3-none-any.whl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2ebfc080595d1da2061f10af9b8727480859466641719a316ec6fea20c669c3f
-size 1417819569
+oid sha256:459eb3ac9d28ffbcc116cb696829d2e592178ef88376588e71ce3d6e43331f7d
+size 343229002

meta.json

@@ -1,7 +1,7 @@
 {
   "lang":"hu",
   "name":"core_news_lg",
-  "version":"3.2.1b1",
+  "version":"3.2.3",
   "description":"Core Hungarian model for HuSpaCy. Components: tok2vec, senter, tagger, morphologizer, lemmatizer, parser, ner",
   "author":"SzegedAI, MILAB",
   "email":"gyorgy@orosz.link",
@@ -11,8 +11,8 @@
   "spacy_git_version":"b50fe5ec6",
   "vectors":{
     "width":300,
-    "vectors":1140008,
-    "keys":1140008,
+    "vectors":200000,
+    "keys":0,
     "name":"hu_core_news_lg.vectors"
   },
   "labels":{
@@ -1270,90 +1270,90 @@
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-    "pos_acc":0.9660749318,
-    "morph_acc":0.9291798258,
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+    "tag_acc":0.9645437581,
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+    "morph_micro_p":0.9655590694,
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@@ -1366,114 +1366,114 @@
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