Update spaCy pipeline

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Files changed (14) hide show

README.md +28 -28
accuracy.json +193 -193
attribute_ruler/patterns +0 -0
config.cfg +5 -4
lemmatizer/model +1 -1
meta.json +196 -196
morphologizer/model +1 -1
nb_core_news_md-any-py3-none-any.whl +2 -2
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: 0.8307228916
     - name: NER Recall
       type: recall
-      value: 0.816943128
     - name: NER F Score
       type: f_score
-      value: 0.8237753883
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9726155711
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9726155711
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9588648574
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9712137072
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.8923091347
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8610490461
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9326446281
 ---
 ### Details: https://spacy.io/models/nb#nb_core_news_md
@@ -78,8 +78,8 @@ Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologiz
 | Feature | Description |
 | --- | --- |
 | **Name** | `nb_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) |
@@ -105,22 +105,22 @@ Norwegian (Bokmål) pipeline optimized for CPU. Components: tok2vec, morphologiz
 | Type | Score |
 | --- | --- |
-| `TOKEN_ACC` | 99.90 |
 | `TOKEN_P` | 99.71 |
 | `TOKEN_R` | 99.53 |
 | `TOKEN_F` | 99.62 |
-| `POS_ACC` | 97.26 |
-| `MORPH_ACC` | 95.89 |
-| `MORPH_MICRO_P` | 97.63 |
-| `MORPH_MICRO_R` | 96.78 |
-| `MORPH_MICRO_F` | 97.20 |
-| `SENTS_P` | 92.84 |
-| `SENTS_R` | 93.69 |
-| `SENTS_F` | 93.26 |
-| `DEP_UAS` | 89.23 |
-| `DEP_LAS` | 86.10 |
-| `LEMMA_ACC` | 97.12 |
-| `TAG_ACC` | 97.26 |
-| `ENTS_P` | 83.07 |
-| `ENTS_R` | 81.69 |
-| `ENTS_F` | 82.38 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.811827957
     - name: NER Recall
       type: recall
+      value: 0.8050947867
     - name: NER F Score
       type: f_score
+      value: 0.8084473528
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9728910684
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9728910684
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9586576479
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.970965787
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.8936788796
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.8623767174
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9485952133
 ---
 ### Details: https://spacy.io/models/nb#nb_core_news_md
 | Feature | Description |
 | --- | --- |
 | **Name** | `nb_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) |
 | Type | Score |
 | --- | --- |
+| `TOKEN_ACC` | 99.81 |
 | `TOKEN_P` | 99.71 |
 | `TOKEN_R` | 99.53 |
 | `TOKEN_F` | 99.62 |
+| `POS_ACC` | 97.29 |
+| `MORPH_ACC` | 95.87 |
+| `MORPH_MICRO_P` | 97.59 |
+| `MORPH_MICRO_R` | 96.65 |
+| `MORPH_MICRO_F` | 97.12 |
+| `SENTS_P` | 95.12 |
+| `SENTS_R` | 94.60 |
+| `SENTS_F` | 94.86 |
+| `DEP_UAS` | 89.37 |
+| `DEP_LAS` | 86.24 |
+| `LEMMA_ACC` | 97.10 |
+| `TAG_ACC` | 97.29 |
+| `ENTS_P` | 81.18 |
+| `ENTS_R` | 80.51 |
+| `ENTS_F` | 80.84 |

accuracy.json CHANGED Viewed

@@ -1,63 +1,63 @@
 {
-  "token_acc": 0.9990350152,
   "token_p": 0.997080292,
   "token_r": 0.9953256895,
   "token_f": 0.9962022181,
-  "pos_acc": 0.9726155711,
-  "morph_acc": 0.9588648574,
-  "morph_micro_p": 0.9762975408,
-  "morph_micro_r": 0.9677851253,
-  "morph_micro_f": 0.9720226967,
   "morph_per_feat": {
     "Definite": {
-      "p": 0.9811364159,
-      "r": 0.9674492458,
-      "f": 0.9742447604
     },
     "Gender": {
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-      "r": 0.9418571564,
-      "f": 0.9454891692
     },
     "Number": {
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-      "r": 0.9662246318,
-      "f": 0.9719929245
     },
     "Mood": {
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-      "r": 0.9812453113,
-      "f": 0.9833354216
     },
     "Tense": {
-      "p": 0.9850897144,
-      "r": 0.9816167212,
-      "f": 0.9833501514
     },
     "VerbForm": {
-      "p": 0.9756774404,
-      "r": 0.9740873533,
-      "f": 0.9748817485
     },
     "Degree": {
-      "p": 0.9691934926,
-      "r": 0.9618687736,
-      "f": 0.9655172414
     },
     "PronType": {
-      "p": 0.9909130247,
-      "r": 0.9879206212,
-      "f": 0.9894145604
     },
     "Poss": {
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-      "r": 0.9881422925,
-      "f": 0.9920634921
     },
     "Case": {
-      "p": 0.9916294643,
       "r": 0.9839424142,
-      "f": 0.9877709839
     },
     "Reflex": {
       "p": 1.0,
@@ -65,191 +65,186 @@
       "f": 1.0
     },
     "NumType": {
-      "p": 0.9977375566,
-      "r": 0.9074074074,
-      "f": 0.9504310345
     },
     "Polarity": {
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       "r": 1.0,
-      "f": 0.9968454259
     },
     "Person": {
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-      "r": 0.9900332226,
-      "f": 0.9909738717
     },
     "Animacy": {
-      "p": 0.9982935154,
-      "r": 0.996592845,
-      "f": 0.9974424552
     },
     "Voice": {
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-      "r": 0.9347826087,
-      "f": 0.9416058394
     },
     "Abbr": {
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-      "r": 0.83125,
-      "f": 0.9016949153
     }
   },
-  "sents_p": 0.9284245167,
-  "sents_r": 0.9369032794,
-  "sents_f": 0.9326446281,
-  "dep_uas": 0.8923091347,
-  "dep_las": 0.8610490461,
   "dep_las_per_type": {
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-      "r": 0.23,
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     },
     "ccomp": {
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     "expl": {
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     "csubj": {
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     "aux:pass": {
-      "p": 0.9464285714,
-      "r": 0.8833333333,
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-    },
-    "parataxis": {
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-    },
-    "acl": {
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     "acl:cleft": {
-      "p": 0.4285714286,
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     "orphan": {
       "p": 0.0,
@@ -261,25 +256,30 @@
       "r": 0.0,
       "f": 0.0
     },
     "reparandum": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     },
     "compound": {
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     "csubj:pass": {
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@@ -287,52 +287,52 @@
       "f": 0.0
     }
   },
-  "lemma_acc": 0.9712137072,
-  "tag_acc": 0.9726155711,
-  "ents_p": 0.8307228916,
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   },
-  "speed": 9847.9572403325
 }

 {
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