Update spaCy pipeline

Browse files

Files changed (14) hide show

README.md +27 -27
accuracy.json +79 -79
attribute_ruler/patterns +0 -0
config.cfg +5 -4
el_core_news_md-any-py3-none-any.whl +2 -2
lemmatizer/model +1 -1
meta.json +82 -82
morphologizer/model +1 -1
ner/model +2 -2
parser/model +1 -1
senter/model +1 -1
tok2vec/model +2 -2
tokenizer +1 -1
vocab/strings.json +2 -2

README.md CHANGED Viewed

@@ -14,62 +14,62 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.7601626016
     - name: NER Recall
       type: recall
-      value: 0.7857142857
     - name: NER F Score
       type: f_score
-      value: 0.7727272727
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9308287729
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9608046147
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9030222354
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.8919785042
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.8767108228
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8412026604
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9308641975
 ---
 ### Details: https://spacy.io/models/el#el_core_news_md
@@ -78,8 +78,8 @@ Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, le
 | Feature | Description |
 | --- | --- |
 | **Name** | `el_core_news_md` |
-| **Version** | `3.4.0` |
-| **spaCy** | `>=3.4.0,<3.5.0` |
 | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
 | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
@@ -109,18 +109,18 @@ Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, le
 | `TOKEN_P` | 99.90 |
 | `TOKEN_R` | 99.95 |
 | `TOKEN_F` | 99.93 |
-| `POS_ACC` | 96.08 |
-| `MORPH_ACC` | 90.30 |
-| `MORPH_MICRO_P` | 95.79 |
-| `MORPH_MICRO_R` | 95.80 |
-| `MORPH_MICRO_F` | 95.79 |
-| `SENTS_P` | 92.63 |
-| `SENTS_R` | 93.55 |
-| `SENTS_F` | 93.09 |
-| `DEP_UAS` | 87.67 |
-| `DEP_LAS` | 84.12 |
-| `LEMMA_ACC` | 89.20 |
-| `TAG_ACC` | 93.08 |
-| `ENTS_P` | 76.02 |
-| `ENTS_R` | 78.57 |
-| `ENTS_F` | 77.27 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.7594936709
     - name: NER Recall
       type: recall
+      value: 0.756302521
     - name: NER F Score
       type: f_score
+      value: 0.7578947368
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9324064488
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9623822906
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9064734014
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.8884287334
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.8759067927
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.836887228
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9511889862
 ---
 ### Details: https://spacy.io/models/el#el_core_news_md
 | Feature | Description |
 | --- | --- |
 | **Name** | `el_core_news_md` |
+| **Version** | `3.5.0` |
+| **spaCy** | `>=3.5.0,<3.6.0` |
 | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `tok2vec`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
 | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
 | `TOKEN_P` | 99.90 |
 | `TOKEN_R` | 99.95 |
 | `TOKEN_F` | 99.93 |
+| `POS_ACC` | 96.24 |
+| `MORPH_ACC` | 90.65 |
+| `MORPH_MICRO_P` | 96.02 |
+| `MORPH_MICRO_R` | 95.85 |
+| `MORPH_MICRO_F` | 95.93 |
+| `SENTS_P` | 95.96 |
+| `SENTS_R` | 94.29 |
+| `SENTS_F` | 95.12 |
+| `DEP_UAS` | 87.59 |
+| `DEP_LAS` | 83.69 |
+| `LEMMA_ACC` | 88.84 |
+| `TAG_ACC` | 93.24 |
+| `ENTS_P` | 75.95 |
+| `ENTS_R` | 75.63 |
+| `ENTS_F` | 75.79 |

accuracy.json CHANGED Viewed

@@ -3,129 +3,129 @@
   "token_p": 0.9990295973,
   "token_r": 0.9995068547,
   "token_f": 0.9992604644,
-  "pos_acc": 0.9608046147,
-  "morph_acc": 0.9030222354,
-  "morph_micro_p": 0.9578601214,
-  "morph_micro_r": 0.9579900315,
-  "morph_micro_f": 0.957925072,
   "morph_per_feat": {
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-      "f": 0.9265536723
     },
     "Case": {
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-      "f": 0.9336552069
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     "Person": {
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-  "sents_f": 0.9308641975,
-  "dep_uas": 0.8767108228,
-  "dep_las": 0.8412026604,
   "dep_las_per_type": {},
-  "lemma_acc": 0.8919785042,
-  "tag_acc": 0.9308287729,
-  "ents_p": 0.7601626016,
-  "ents_r": 0.7857142857,
-  "ents_f": 0.7727272727,
   "ents_per_type": {
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-    "GPE": {
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-      "f": 0.8695652174
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     "EVENT": {
-      "p": 0.5,
       "r": 0.5,
-      "f": 0.5
     },
     "LOC": {
       "p": 0.0,
@@ -133,5 +133,5 @@
       "f": 0.0
     }
   },
-  "speed": 10712.4782215407
 }

   "token_p": 0.9990295973,
   "token_r": 0.9995068547,
   "token_f": 0.9992604644,
+  "pos_acc": 0.9623822906,
+  "morph_acc": 0.9064734014,
+  "morph_micro_p": 0.9601915696,
+  "morph_micro_r": 0.9584986268,
+  "morph_micro_f": 0.9593443513,
   "morph_per_feat": {
     "Abbr": {
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+      "r": 0.8494623656,
+      "f": 0.908045977
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     "Case": {
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+  "sents_f": 0.9511889862,
+  "dep_uas": 0.8759067927,
+  "dep_las": 0.836887228,
   "dep_las_per_type": {},
+  "lemma_acc": 0.8884287334,
+  "tag_acc": 0.9324064488,
+  "ents_p": 0.7594936709,
+  "ents_r": 0.756302521,
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   "ents_per_type": {
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     "ORG": {
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+    "GPE": {
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+      "r": 0.8735632184,
+      "f": 0.8491620112
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     "PRODUCT": {
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     "EVENT": {
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     "LOC": {
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       "f": 0.0
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 }

attribute_ruler/patterns CHANGED Viewed

Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ

config.cfg CHANGED Viewed

@@ -81,8 +81,8 @@ nO = null
 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,1000,2500,2500,50]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
@@ -150,8 +150,8 @@ factory = "tok2vec"
 [components.tok2vec.model.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode:width}
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,1000,2500,2500,50]
 include_static_vectors = true
 [components.tok2vec.model.encode]
@@ -193,6 +193,7 @@ eval_frequency = 1000
 frozen_components = []
 before_to_disk = null
 annotating_components = []
 [training.batcher]
 @batchers = "spacy.batch_by_words.v1"

 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,1000,2500,2500]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
 [components.tok2vec.model.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode:width}
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
+rows = [5000,1000,2500,2500,50,50]
 include_static_vectors = true
 [components.tok2vec.model.encode]
 frozen_components = []
 before_to_disk = null
 annotating_components = []
+before_update = null
 [training.batcher]
 @batchers = "spacy.batch_by_words.v1"

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meta.json CHANGED Viewed

@@ -1,14 +1,14 @@
 {
   "lang":"el",
   "name":"core_news_md",
-  "version":"3.4.0",
   "description":"Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler.",
   "author":"Explosion",
   "email":"contact@explosion.ai",
   "url":"https://explosion.ai",
   "license":"CC BY-NC-SA 3.0",
-  "spacy_version":">=3.4.0,<3.5.0",
-  "spacy_git_version":"dd038b536",
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@@ -449,131 +449,131 @@
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@@ -581,7 +581,7 @@
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     {

 {
   "lang":"el",
   "name":"core_news_md",
+  "version":"3.5.0",
   "description":"Greek pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, lemmatizer (trainable_lemmatizer), senter, ner, attribute_ruler.",
   "author":"Explosion",
   "email":"contact@explosion.ai",
   "url":"https://explosion.ai",
   "license":"CC BY-NC-SA 3.0",
+  "spacy_version":">=3.5.0,<3.6.0",
+  "spacy_git_version":"9e0322de1",
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