Update spacy pipeline to 3.5.4

README.md

@@ -14,13 +14,13 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.91024526
+      value: 0.9096153846
     - name: NER Recall
       type: recall
-      value: 0.9200070323
+      value: 0.9147327707
     - name: NER F Score
       type: f_score
-      value: 0.9151001137
+      value: 0.9121669004
   - task:
       name: TAG
       type: token-classification
@@ -76,7 +76,7 @@ Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, se
 | Feature | Description |
 | --- | --- |
 | **Name** | `hu_core_news_trf` |
-| **Version** | `3.5.3` |
+| **Version** | `3.5.4` |
 | **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` |
@@ -122,6 +122,6 @@ Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, se
 | `BOUND_DEP_UAS` | 90.11 |
 | `DEP_UAS` | 90.11 |
 | `DEP_LAS` | 86.18 |
-| `ENTS_P` | 91.02 |
-| `ENTS_R` | 92.00 |
-| `ENTS_F` | 91.51 |
+| `ENTS_P` | 90.96 |
+| `ENTS_R` | 91.47 |
+| `ENTS_F` | 91.22 |

config.cfg

@@ -1,8 +1,8 @@
 [paths]
-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"
+tagger_model = "models/hu_core_news_trf-tagger-3.5.4/model-best"
+parser_model = "models/hu_core_news_trf-parser-3.5.4/model-best"
+ner_model = "models/hu_core_news_trf-ner-3.5.4/model-best"
+lemmatizer_lookups = "models/hu_core_news_trf-lookup-lemmatizer-3.5.4"
 train = null
 dev = null
 vectors = null

hu_core_news_trf-any-py3-none-any.whl

@@ -1,3 +1,3 @@
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-size 1266407167
+oid sha256:6528cf2995cdd4eaed50ece5eab4e3134b57bb283f9c8b57c15feca4caf79888
+size 1266409271

meta.json

@@ -1,7 +1,7 @@
 {
   "lang":"hu",
   "name":"core_news_trf",
-  "version":"3.5.3",
+  "version":"3.5.4",
   "description":"Hungarian transformer pipeline (huBERT) for HuSpaCy. Components: transformer, senter, tagger, morphologizer, lemmatizer, parser, ner",
   "author":"SzegedAI, MILAB",
   "email":"[email protected]",
@@ -1614,32 +1614,32 @@
         "f":0.0
       }
     },
-    "ents_p":0.91024526,
-    "ents_r":0.9200070323,
-    "ents_f":0.9151001137,
+    "ents_p":0.9096153846,
+    "ents_r":0.9147327707,
+    "ents_f":0.9121669004,
     "ents_per_type":{
       "ORG":{
-        "p":0.9330524345,
-        "r":0.9239684747,
-        "f":0.9284882367
+        "p":0.9121621622,
+        "r":0.9388038943,
+        "f":0.9252912954
       },
       "PER":{
-        "p":0.9585585586,
-        "r":0.9534050179,
-        "f":0.9559748428
+        "p":0.937866354,
+        "r":0.9557945042,
+        "f":0.9467455621
       },
       "LOC":{
-        "p":0.9201030928,
-        "r":0.9296875,
-        "f":0.9248704663
+        "p":0.9426751592,
+        "r":0.8993055556,
+        "f":0.9204797868
       },
       "MISC":{
-        "p":0.7308673469,
-        "r":0.8127659574,
-        "f":0.7696440564
+        "p":0.7798561151,
+        "r":0.7687943262,
+        "f":0.7742857143
       }
     },
-    "speed":3205.6821561473
+    "speed":3559.6059310631
   },
   "sources":[
     {

ner/model

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trainable_lemmatizer/model

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 size 455946865

transformer/model

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