Update spaCy pipeline

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Files changed (14) hide show

README.md +27 -27
accuracy.json +277 -277
config.cfg +5 -4
fi_core_news_md-any-py3-none-any.whl +2 -2
lemmatizer/model +1 -1
meta.json +280 -280
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: 0.8186111111
     - name: NER Recall
       type: recall
-      value: 0.8067341911
     - name: NER F Score
       type: f_score
-      value: 0.8126292569
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9671117435
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9598664952
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9197779054
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.8628551194
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.827143951
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.7796664222
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.907606679
 ---
 ### Details: https://spacy.io/models/fi#fi_core_news_md
@@ -78,8 +78,8 @@ Finnish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
 | Feature | Description |
 | --- | --- |
 | **Name** | `fi_core_news_md` |
-| **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** | floret (50000, 300) |
@@ -110,18 +110,18 @@ Finnish pipeline optimized for CPU. Components: tok2vec, tagger, morphologizer,
 | `TOKEN_P` | 99.79 |
 | `TOKEN_R` | 99.90 |
 | `TOKEN_F` | 99.85 |
-| `TAG_ACC` | 96.71 |
-| `POS_ACC` | 95.99 |
-| `MORPH_ACC` | 91.98 |
-| `MORPH_MICRO_P` | 95.98 |
-| `MORPH_MICRO_R` | 94.91 |
-| `MORPH_MICRO_F` | 95.44 |
-| `SENTS_P` | 91.89 |
-| `SENTS_R` | 89.66 |
-| `SENTS_F` | 90.76 |
-| `DEP_UAS` | 82.71 |
-| `DEP_LAS` | 77.97 |
-| `LEMMA_ACC` | 86.29 |
-| `ENTS_P` | 81.86 |
-| `ENTS_R` | 80.67 |
-| `ENTS_F` | 81.26 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.8190770962
     - name: NER Recall
       type: recall
+      value: 0.7968792773
     - name: NER F Score
       type: f_score
+      value: 0.807825725
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9659361405
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9586650253
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9186882914
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.8602402419
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.8321792131
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.7845751467
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.8935543278
 ---
 ### Details: https://spacy.io/models/fi#fi_core_news_md
 | Feature | Description |
 | --- | --- |
 | **Name** | `fi_core_news_md` |
+| **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** | floret (50000, 300) |
 | `TOKEN_P` | 99.79 |
 | `TOKEN_R` | 99.90 |
 | `TOKEN_F` | 99.85 |
+| `TAG_ACC` | 96.59 |
+| `POS_ACC` | 95.87 |
+| `MORPH_ACC` | 91.87 |
+| `MORPH_MICRO_P` | 95.90 |
+| `MORPH_MICRO_R` | 94.93 |
+| `MORPH_MICRO_F` | 95.41 |
+| `SENTS_P` | 89.79 |
+| `SENTS_R` | 88.93 |
+| `SENTS_F` | 89.36 |
+| `DEP_UAS` | 83.22 |
+| `DEP_LAS` | 78.46 |
+| `LEMMA_ACC` | 86.02 |
+| `ENTS_P` | 81.91 |
+| `ENTS_R` | 79.69 |
+| `ENTS_F` | 80.78 |

accuracy.json CHANGED Viewed

@@ -3,456 +3,456 @@
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 }

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config.cfg CHANGED Viewed

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 [components.ner.model.tok2vec.embed]
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