Update spaCy pipeline

Browse files

Files changed (15) hide show

README.md +21 -18
accuracy.json +102 -99
attribute_ruler/patterns +0 -0
config.cfg +36 -32
meta.json +105 -102
mk_core_news_md-any-py3-none-any.whl +2 -2
morphologizer/cfg +3 -1
morphologizer/model +0 -0
ner/model +0 -0
parser/model +0 -0
senter/cfg +1 -1
senter/model +0 -0
tokenizer +2 -2
vocab/strings.json +2 -2
vocab/vectors.cfg +3 -0

README.md CHANGED Viewed

@@ -4,7 +4,7 @@ tags:
 - token-classification
 language:
 - mk
-license: CC-BY-SA-4.0
 model-index:
 - name: mk_core_news_md
   results:
@@ -14,40 +14,40 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.7577586207
     - name: NER Recall
       type: recall
       value: 0.7480851064
     - name: NER F Score
       type: f_score
-      value: 0.7528907923
   - task:
       name: SENTER
       type: token-classification
     metrics:
     - name: SENTER Precision
       type: precision
-      value: 0.768115942
     - name: SENTER Recall
       type: recall
-      value: 0.6883116883
     - name: SENTER F Score
       type: f_score
-      value: 0.7260273973
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Dependencies Accuracy
       type: accuracy
-      value: 0.68633235
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Dependencies Accuracy
       type: accuracy
-      value: 0.68633235
 ---
 ### Details: https://spacy.io/models/mk#mk_core_news_md
@@ -56,8 +56,8 @@ Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
 | Feature | Description |
 | --- | --- |
 | **Name** | `mk_core_news_md` |
-| **Version** | `3.1.0` |
-| **spaCy** | `>=3.1.0,<3.2.0` |
 | **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 274587 keys, 20000 unique vectors (300 dimensions) |
@@ -85,12 +85,15 @@ Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
 | Type | Score |
 | --- | --- |
 | `TOKEN_ACC` | 100.00 |
-| `POS_ACC` | 93.15 |
-| `SENTS_P` | 76.81 |
-| `SENTS_R` | 68.83 |
-| `SENTS_F` | 72.60 |
-| `DEP_UAS` | 68.63 |
-| `DEP_LAS` | 53.29 |
-| `ENTS_P` | 75.78 |
 | `ENTS_R` | 74.81 |
-| `ENTS_F` | 75.29 |

 - token-classification
 language:
 - mk
+license: cc-by-sa-4.0
 model-index:
 - name: mk_core_news_md
   results:
     metrics:
     - name: NER Precision
       type: precision
+      value: 0.7643478261
     - name: NER Recall
       type: recall
       value: 0.7480851064
     - name: NER F Score
       type: f_score
+      value: 0.7561290323
   - task:
       name: SENTER
       type: token-classification
     metrics:
     - name: SENTER Precision
       type: precision
+      value: 0.8125
     - name: SENTER Recall
       type: recall
+      value: 0.6753246753
     - name: SENTER F Score
       type: f_score
+      value: 0.7375886525
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Dependencies Accuracy
       type: accuracy
+      value: 0.700686948
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Dependencies Accuracy
       type: accuracy
+      value: 0.700686948
 ---
 ### Details: https://spacy.io/models/mk#mk_core_news_md
 | Feature | Description |
 | --- | --- |
 | **Name** | `mk_core_news_md` |
+| **Version** | `3.2.0` |
+| **spaCy** | `>=3.2.0,<3.3.0` |
 | **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 274587 keys, 20000 unique vectors (300 dimensions) |
 | Type | Score |
 | --- | --- |
 | `TOKEN_ACC` | 100.00 |
+| `TOKEN_P` | 100.00 |
+| `TOKEN_R` | 100.00 |
+| `TOKEN_F` | 100.00 |
+| `SENTS_P` | 81.25 |
+| `SENTS_R` | 67.53 |
+| `SENTS_F` | 73.76 |
+| `DEP_UAS` | 70.07 |
+| `DEP_LAS` | 53.19 |
+| `ENTS_P` | 76.43 |
 | `ENTS_R` | 74.81 |
+| `ENTS_F` | 75.61 |
+| `POS_ACC` | 93.07 |

accuracy.json CHANGED Viewed

@@ -1,37 +1,38 @@
 {
   "token_acc": 1.0,
-  "pos_acc": 0.9314809819,
-  "sents_p": 0.768115942,
-  "sents_r": 0.6883116883,
-  "sents_f": 0.7260273973,
-  "speed": 2817.6117268563,
-  "dep_uas": 0.68633235,
-  "dep_las": 0.5329400197,
   "dep_las_per_type": {
     "nsubj": {
-      "p": 0.6216216216,
-      "r": 0.6052631579,
-      "f": 0.6133333333
     },
     "root": {
-      "p": 0.7536231884,
       "r": 0.7428571429,
-      "f": 0.7482014388
     },
     "cc": {
-      "p": 0.9473684211,
       "r": 0.6428571429,
-      "f": 0.7659574468
     },
     "relcl": {
-      "p": 0.4230769231,
       "r": 0.4230769231,
-      "f": 0.4230769231
     },
     "pozm": {
-      "p": 0.6666666667,
-      "r": 0.3636363636,
-      "f": 0.4705882353
     },
     "poss": {
       "p": 0.0,
@@ -39,24 +40,24 @@
       "f": 0.0
     },
     "aux": {
-      "p": 0.5714285714,
-      "r": 0.6060606061,
-      "f": 0.5882352941
     },
     "prep": {
-      "p": 0.696969697,
-      "r": 0.7666666667,
-      "f": 0.7301587302
     },
     "iobj": {
-      "p": 0.1666666667,
-      "r": 0.125,
-      "f": 0.1428571429
     },
     "pozv": {
-      "p": 0.3636363636,
-      "r": 0.2666666667,
-      "f": 0.3076923077
     },
     "quantmod": {
       "p": 0.0,
@@ -64,9 +65,9 @@
       "f": 0.0
     },
     "att": {
-      "p": 0.7872340426,
-      "r": 0.7115384615,
-      "f": 0.7474747475
     },
     "det": {
       "p": 0.0,
@@ -84,24 +85,24 @@
       "f": 0.0
     },
     "dobj": {
-      "p": 0.4202898551,
-      "r": 0.4833333333,
-      "f": 0.4496124031
     },
     "ppdo": {
-      "p": 0.7142857143,
       "r": 0.3333333333,
-      "f": 0.4545454545
     },
     "neg": {
-      "p": 0.4,
-      "r": 0.3636363636,
-      "f": 0.380952381
     },
     "pobj": {
-      "p": 0.4473684211,
       "r": 0.53125,
-      "f": 0.4857142857
     },
     "mwe": {
       "p": 0.0,
@@ -113,16 +114,16 @@
       "r": 0.0,
       "f": 0.0
     },
-    "advmod": {
-      "p": 0.0,
-      "r": 0.0,
-      "f": 0.0
-    },
     "appos": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     },
     "advcl": {
       "p": 0.0,
       "r": 0.0,
@@ -159,29 +160,35 @@
       "f": 0.0
     }
   },
-  "ents_p": 0.7577586207,
   "ents_r": 0.7480851064,
-  "ents_f": 0.7528907923,
   "ents_per_type": {
     "GPE": {
-      "p": 0.8639455782,
       "r": 0.8985849057,
-      "f": 0.8809248555
     },
     "LOC": {
-      "p": 0.7777777778,
       "r": 0.5632183908,
-      "f": 0.6533333333
     },
     "QUANTITY": {
-      "p": 0.7027027027,
-      "r": 0.6341463415,
-      "f": 0.6666666667
     },
     "CARDINAL": {
-      "p": 0.6960784314,
-      "r": 0.7553191489,
-      "f": 0.7244897959
     },
     "NORP": {
       "p": 0.4666666667,
@@ -189,39 +196,34 @@
       "f": 0.448
     },
     "DATE": {
-      "p": 0.7755102041,
-      "r": 0.8028169014,
-      "f": 0.7889273356
-    },
-    "PERCENT": {
-      "p": 0.9411764706,
-      "r": 1.0,
-      "f": 0.9696969697
     },
     "PERSON": {
-      "p": 0.7785234899,
-      "r": 0.7733333333,
-      "f": 0.7759197324
     },
-    "ORG": {
-      "p": 0.546875,
-      "r": 0.7142857143,
-      "f": 0.6194690265
     },
     "MONEY": {
-      "p": 0.5,
-      "r": 0.5,
-      "f": 0.5
     },
     "ORDINAL": {
-      "p": 0.4615384615,
       "r": 0.5454545455,
-      "f": 0.5
     },
-    "EVENT": {
-      "p": 0.6111111111,
-      "r": 0.6470588235,
-      "f": 0.6285714286
     },
     "LANGUAGE": {
       "p": 0.0,
@@ -229,29 +231,30 @@
       "f": 0.0
     },
     "WORK_OF_ART": {
-      "p": 0.5862068966,
-      "r": 0.4146341463,
-      "f": 0.4857142857
     },
     "TIME": {
-      "p": 1.0,
-      "r": 0.8333333333,
-      "f": 0.9090909091
     },
-    "FAC": {
-      "p": 0.2222222222,
-      "r": 0.1,
-      "f": 0.1379310345
     },
     "LAW": {
-      "p": 0.5,
-      "r": 0.3333333333,
-      "f": 0.4
     },
     "PRODUCT": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     }
-  }
 }

 {
   "token_acc": 1.0,
+  "token_p": 1.0,
+  "token_r": 1.0,
+  "token_f": 1.0,
+  "sents_p": 0.8125,
+  "sents_r": 0.6753246753,
+  "sents_f": 0.7375886525,
+  "dep_uas": 0.700686948,
+  "dep_las": 0.5318940137,
   "dep_las_per_type": {
     "nsubj": {
+      "p": 0.7297297297,
+      "r": 0.7105263158,
+      "f": 0.72
     },
     "root": {
+      "p": 0.8125,
       "r": 0.7428571429,
+      "f": 0.776119403
     },
     "cc": {
+      "p": 0.8181818182,
       "r": 0.6428571429,
+      "f": 0.72
     },
     "relcl": {
+      "p": 0.4074074074,
       "r": 0.4230769231,
+      "f": 0.4150943396
     },
     "pozm": {
+      "p": 0.8333333333,
+      "r": 0.4545454545,
+      "f": 0.5882352941
     },
     "poss": {
       "p": 0.0,
       "f": 0.0
     },
     "aux": {
+      "p": 0.6111111111,
+      "r": 0.6666666667,
+      "f": 0.6376811594
     },
     "prep": {
+      "p": 0.6875,
+      "r": 0.7333333333,
+      "f": 0.7096774194
     },
     "iobj": {
+      "p": 0.0,
+      "r": 0.0,
+      "f": 0.0
     },
     "pozv": {
+      "p": 0.2,
+      "r": 0.1333333333,
+      "f": 0.16
     },
     "quantmod": {
       "p": 0.0,
       "f": 0.0
     },
     "att": {
+      "p": 0.693877551,
+      "r": 0.6538461538,
+      "f": 0.6732673267
     },
     "det": {
       "p": 0.0,
       "f": 0.0
     },
     "dobj": {
+      "p": 0.40625,
+      "r": 0.4333333333,
+      "f": 0.4193548387
     },
     "ppdo": {
+      "p": 0.625,
       "r": 0.3333333333,
+      "f": 0.4347826087
     },
     "neg": {
+      "p": 0.6363636364,
+      "r": 0.6363636364,
+      "f": 0.6363636364
     },
     "pobj": {
+      "p": 0.425,
       "r": 0.53125,
+      "f": 0.4722222222
     },
     "mwe": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     },
     "appos": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     },
+    "advmod": {
+      "p": 0.3333333333,
+      "r": 0.5,
+      "f": 0.4
+    },
     "advcl": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     }
   },
+  "speed": 2294.6132988248,
+  "ents_p": 0.7643478261,
   "ents_r": 0.7480851064,
+  "ents_f": 0.7561290323,
   "ents_per_type": {
+    "ORG": {
+      "p": 0.5409836066,
+      "r": 0.6734693878,
+      "f": 0.6
+    },
     "GPE": {
+      "p": 0.8718535469,
       "r": 0.8985849057,
+      "f": 0.8850174216
     },
     "LOC": {
+      "p": 0.8305084746,
       "r": 0.5632183908,
+      "f": 0.6712328767
     },
     "QUANTITY": {
+      "p": 0.7142857143,
+      "r": 0.6097560976,
+      "f": 0.6578947368
     },
     "CARDINAL": {
+      "p": 0.7040816327,
+      "r": 0.7340425532,
+      "f": 0.71875
     },
     "NORP": {
       "p": 0.4666666667,
       "f": 0.448
     },
     "DATE": {
+      "p": 0.7887323944,
+      "r": 0.7887323944,
+      "f": 0.7887323944
     },
     "PERSON": {
+      "p": 0.8255033557,
+      "r": 0.82,
+      "f": 0.8227424749
     },
+    "FAC": {
+      "p": 0.1666666667,
+      "r": 0.1,
+      "f": 0.125
     },
     "MONEY": {
+      "p": 0.6666666667,
+      "r": 1.0,
+      "f": 0.8
     },
     "ORDINAL": {
+      "p": 0.5,
       "r": 0.5454545455,
+      "f": 0.5217391304
     },
+    "PERCENT": {
+      "p": 1.0,
+      "r": 1.0,
+      "f": 1.0
     },
     "LANGUAGE": {
       "p": 0.0,
       "f": 0.0
     },
     "WORK_OF_ART": {
+      "p": 0.5625,
+      "r": 0.4390243902,
+      "f": 0.4931506849
     },
     "TIME": {
+      "p": 0.5714285714,
+      "r": 0.6666666667,
+      "f": 0.6153846154
     },
+    "EVENT": {
+      "p": 0.5789473684,
+      "r": 0.6470588235,
+      "f": 0.6111111111
     },
     "LAW": {
+      "p": 0.0,
+      "r": 0.0,
+      "f": 0.0
     },
     "PRODUCT": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     }
+  },
+  "pos_acc": 0.9306717022
 }

attribute_ruler/patterns CHANGED Viewed

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

config.cfg CHANGED Viewed

@@ -1,10 +1,8 @@
 [paths]
-train = "corpus/mk-tag-news/train.spacy"
-dev = "corpus/mk-tag-news/dev.spacy"
-vectors = "corpus/mk_vectors"
-raw = null
 init_tok2vec = null
-vocab_data = null
 [system]
 gpu_allocator = null
@@ -24,6 +22,7 @@ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
 [components.attribute_ruler]
 factory = "attribute_ruler"
 validate = false
 [components.lemmatizer]
@@ -31,9 +30,13 @@ factory = "lemmatizer"
 mode = "rule"
 model = null
 overwrite = false
 [components.morphologizer]
 factory = "morphologizer"
 [components.morphologizer.model]
 @architectures = "spacy.Tagger.v1"
@@ -45,8 +48,8 @@ nO = null
 [components.morphologizer.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.morphologizer.model.tok2vec.encode:width}
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [5000,2500,2500,2500]
 include_static_vectors = true
 [components.morphologizer.model.tok2vec.encode]
@@ -60,6 +63,7 @@ maxout_pieces = 3
 factory = "ner"
 incorrect_spans_key = null
 moves = null
 update_with_oracle_cut_size = 100
 [components.ner.model]
@@ -77,8 +81,8 @@ nO = null
 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [5000,2500,2500,2500]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
@@ -93,6 +97,7 @@ factory = "parser"
 learn_tokens = false
 min_action_freq = 30
 moves = null
 update_with_oracle_cut_size = 100
 [components.parser.model]
@@ -110,8 +115,8 @@ nO = null
 [components.parser.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [5000,2500,2500,2500]
 include_static_vectors = true
 [components.parser.model.tok2vec.encode]
@@ -123,6 +128,8 @@ maxout_pieces = 3
 [components.senter]
 factory = "senter"
 [components.senter.model]
 @architectures = "spacy.Tagger.v1"
@@ -134,8 +141,8 @@ nO = null
 [components.senter.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 16
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [1000,500,500,500]
 include_static_vectors = true
 [components.senter.model.tok2vec.encode]
@@ -149,22 +156,19 @@ maxout_pieces = 2
 [corpora.dev]
 @readers = "spacy.Corpus.v1"
-limit = 0
-max_length = 0
-path = ${paths:dev}
 gold_preproc = false
 augmenter = null
 [corpora.train]
 @readers = "spacy.Corpus.v1"
-path = ${paths:train}
-max_length = 5000
 gold_preproc = false
 limit = 0
-[corpora.train.augmenter]
-@augmenters = "spacy.lower_case.v1"
-level = 0.1
 [training]
 train_corpus = "corpora.train"
@@ -195,9 +199,8 @@ compound = 1.001
 t = 0.0
 [training.logger]
-@loggers = "spacy.WandbLogger.v1"
-project_name = "spacy-v3.0.0a2"
-remove_config_values = []
 [training.optimizer]
 @optimizers = "Adam.v1"
@@ -211,25 +214,26 @@ eps = 0.00000001
 learn_rate = 0.001
 [training.score_weights]
-pos_acc = 0.2
 morph_acc = null
 morph_per_feat = null
-dep_uas = 0.1
-dep_las = 0.1
 dep_las_per_type = null
 sents_p = 0.0
 sents_r = 0.0
-sents_f = 0.2
-lemma_acc = 0.2
-ents_f = 0.2
 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null
 [pretraining]
 [initialize]
-vocab_data = ${paths.vocab_data}
 vectors = ${paths.vectors}
 init_tok2vec = ${paths.init_tok2vec}
 before_init = null

 [paths]
+train = null
+dev = null
+vectors = null
 init_tok2vec = null
 [system]
 gpu_allocator = null
 [components.attribute_ruler]
 factory = "attribute_ruler"
+scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
 validate = false
 [components.lemmatizer]
 mode = "rule"
 model = null
 overwrite = false
+scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
 [components.morphologizer]
 factory = "morphologizer"
+extend = false
+overwrite = true
+scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
 [components.morphologizer.model]
 @architectures = "spacy.Tagger.v1"
 [components.morphologizer.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.morphologizer.model.tok2vec.encode:width}
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
+rows = [5000,2500,2500,2500,100]
 include_static_vectors = true
 [components.morphologizer.model.tok2vec.encode]
 factory = "ner"
 incorrect_spans_key = null
 moves = null
+scorer = {"@scorers":"spacy.ner_scorer.v1"}
 update_with_oracle_cut_size = 100
 [components.ner.model]
 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
+rows = [5000,2500,2500,2500,100]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
 learn_tokens = false
 min_action_freq = 30
 moves = null
+scorer = {"@scorers":"spacy.parser_scorer.v1"}
 update_with_oracle_cut_size = 100
 [components.parser.model]
 [components.parser.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
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 include_static_vectors = true
 [components.parser.model.tok2vec.encode]
 [components.senter]
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 [components.senter.model]
 @architectures = "spacy.Tagger.v1"
 [components.senter.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 16
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 include_static_vectors = true
 [components.senter.model.tok2vec.encode]
 [corpora.dev]
 @readers = "spacy.Corpus.v1"
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 gold_preproc = false
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 augmenter = null
 [corpora.train]
 @readers = "spacy.Corpus.v1"
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 gold_preproc = false
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 limit = 0
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 [training]
 train_corpus = "corpora.train"
 t = 0.0
 [training.logger]
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 learn_rate = 0.001
 [training.score_weights]
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 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null
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 [pretraining]
 [initialize]
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 vectors = ${paths.vectors}
 init_tok2vec = ${paths.init_tok2vec}
 before_init = null

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@@ -1,14 +1,14 @@
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 {
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   "author":"Explosion",
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