Update spaCy pipeline

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Files changed (14) hide show

README.md +26 -26
accuracy.json +180 -180
config.cfg +5 -4
de_core_news_lg-any-py3-none-any.whl +2 -2
lemmatizer/model +1 -1
meta.json +183 -183
morphologizer/model +1 -1
ner/model +2 -2
parser/model +1 -1
senter/model +1 -1
tagger/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: 0.8528386427
     - name: NER Recall
       type: recall
-      value: 0.8461254893
     - name: NER F Score
       type: f_score
-      value: 0.8494688031
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9799589002
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9844984802
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9219424199
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9790152496
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9265973031
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.9078315742
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9509285196
 ---
 ### Details: https://spacy.io/models/de#de_core_news_lg
@@ -78,8 +78,8 @@ German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, p
 | Feature | Description |
 | --- | --- |
 | **Name** | `de_core_news_lg` |
-| **Version** | `3.4.0` |
-| **spaCy** | `>=3.4.0,<3.5.0` |
 | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
 | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
@@ -106,22 +106,22 @@ German pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer, p
 | Type | Score |
 | --- | --- |
-| `TOKEN_ACC` | 99.98 |
 | `TOKEN_P` | 99.92 |
 | `TOKEN_R` | 99.90 |
 | `TOKEN_F` | 99.91 |
-| `TAG_ACC` | 98.00 |
-| `POS_ACC` | 98.45 |
-| `MORPH_ACC` | 92.19 |
-| `MORPH_MICRO_P` | 96.08 |
-| `MORPH_MICRO_R` | 96.05 |
-| `MORPH_MICRO_F` | 96.06 |
-| `SENTS_P` | 95.48 |
-| `SENTS_R` | 96.06 |
-| `SENTS_F` | 95.09 |
 | `DEP_UAS` | 92.66 |
 | `DEP_LAS` | 90.78 |
-| `LEMMA_ACC` | 97.90 |
-| `ENTS_P` | 85.28 |
-| `ENTS_R` | 84.61 |
-| `ENTS_F` | 84.95 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.8527131783
     - name: NER Recall
       type: recall
+      value: 0.844401557
     - name: NER F Score
       type: f_score
+      value: 0.8485370145
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9795559667
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9841217399
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9205894013
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9790945371
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9265658098
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.9078030166
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9541230945
 ---
 ### Details: https://spacy.io/models/de#de_core_news_lg
 | Feature | Description |
 | --- | --- |
 | **Name** | `de_core_news_lg` |
+| **Version** | `3.5.0` |
+| **spaCy** | `>=3.5.0,<3.6.0` |
 | **Default Pipeline** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Components** | `tok2vec`, `tagger`, `morphologizer`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
 | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
 | Type | Score |
 | --- | --- |
+| `TOKEN_ACC` | 99.96 |
 | `TOKEN_P` | 99.92 |
 | `TOKEN_R` | 99.90 |
 | `TOKEN_F` | 99.91 |
+| `TAG_ACC` | 97.96 |
+| `POS_ACC` | 98.41 |
+| `MORPH_ACC` | 92.06 |
+| `MORPH_MICRO_P` | 96.01 |
+| `MORPH_MICRO_R` | 95.99 |
+| `MORPH_MICRO_F` | 96.00 |
+| `SENTS_P` | 95.18 |
+| `SENTS_R` | 96.48 |
+| `SENTS_F` | 95.41 |
 | `DEP_UAS` | 92.66 |
 | `DEP_LAS` | 90.78 |
+| `LEMMA_ACC` | 97.91 |
+| `ENTS_P` | 85.27 |
+| `ENTS_R` | 84.44 |
+| `ENTS_F` | 84.85 |

accuracy.json CHANGED Viewed

@@ -1,64 +1,64 @@
 {
-  "token_acc": 0.9998017682,
   "token_p": 0.9991808044,
   "token_r": 0.9990356034,
   "token_f": 0.9991081986,
-  "tag_acc": 0.9799589002,
-  "pos_acc": 0.9844984802,
-  "morph_acc": 0.9219424199,
-  "morph_micro_p": 0.9607921735,
-  "morph_micro_r": 0.9604629689,
-  "morph_micro_f": 0.960627543,
   "morph_per_feat": {
     "Case": {
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-      "r": 0.9228029465,
-      "f": 0.9220192761
     },
     "Definite": {
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-      "r": 0.9971487226,
-      "f": 0.9966372186
     },
     "Gender": {
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-      "r": 0.9536294875,
-      "f": 0.9505309797
     },
     "Number": {
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-      "r": 0.9774611999,
-      "f": 0.9772800963
     },
     "PronType": {
-      "p": 0.9926052332,
-      "r": 0.9904321738,
-      "f": 0.9915175129
     },
     "Degree": {
-      "p": 0.9846830986,
-      "r": 0.9762611276,
-      "f": 0.9804540275
     },
     "VerbForm": {
-      "p": 0.9638193106,
-      "r": 0.9668205734,
-      "f": 0.9653176092
     },
     "Mood": {
-      "p": 0.9755525787,
-      "r": 0.9660089537,
-      "f": 0.9707573107
     },
     "Person": {
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-      "r": 0.9747237569,
-      "f": 0.9787116011
     },
     "Tense": {
-      "p": 0.9783302537,
-      "r": 0.9688903677,
-      "f": 0.973587429
     },
     "Reflex": {
       "p": 1.0,
@@ -66,207 +66,207 @@
       "f": 0.9964328181
     },
     "Poss": {
-      "p": 0.9958847737,
       "r": 1.0,
-      "f": 0.9979381443
     },
     "Foreign": {
-      "p": 0.7555555556,
-      "r": 0.1708542714,
-      "f": 0.2786885246
     }
   },
-  "sents_p": 0.9547916667,
-  "sents_r": 0.9605866756,
-  "sents_f": 0.9509285196,
-  "dep_uas": 0.9265973031,
-  "dep_las": 0.9078315742,
   "dep_las_per_type": {
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     "ams": {
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     "oa2": {
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@@ -278,41 +278,41 @@
       "f": 0.0
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-  "lemma_acc": 0.9790152496,
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   }
 }

 {
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   "token_p": 0.9991808044,
   "token_r": 0.9990356034,
   "token_f": 0.9991081986,
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