Update spaCy pipeline

Browse files

Files changed (12) hide show

README.md +27 -27
accuracy.json +152 -152
attribute_ruler/patterns +0 -0
ca_core_news_sm-any-py3-none-any.whl +2 -2
config.cfg +5 -4
meta.json +155 -155
morphologizer/model +1 -1
ner/model +2 -2
parser/model +1 -1
senter/model +1 -1
tok2vec/model +2 -2
tokenizer +1 -1

README.md CHANGED Viewed

@@ -14,62 +14,62 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8035598706
     - name: NER Recall
       type: recall
-      value: 0.8032999029
     - name: NER F Score
       type: f_score
-      value: 0.8034298657
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9813205009
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9813205009
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9778103575
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.973955774
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9113135278
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8791219261
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9903536977
 ---
 ### Details: https://spacy.io/models/ca#ca_core_news_sm
@@ -78,8 +78,8 @@ Catalan pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
 | Feature | Description |
 | --- | --- |
 | **Name** | `ca_core_news_sm` |
-| **Version** | `3.4.0` |
-| **spaCy** | `>=3.4.0,<3.5.0` |
 | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
@@ -105,22 +105,22 @@ Catalan pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
 | Type | Score |
 | --- | --- |
-| `TOKEN_ACC` | 99.97 |
 | `TOKEN_P` | 99.78 |
 | `TOKEN_R` | 99.79 |
 | `TOKEN_F` | 99.79 |
-| `POS_ACC` | 98.13 |
-| `MORPH_ACC` | 97.78 |
-| `MORPH_MICRO_P` | 99.37 |
-| `MORPH_MICRO_R` | 98.72 |
-| `MORPH_MICRO_F` | 99.04 |
 | `SENTS_P` | 98.95 |
-| `SENTS_R` | 99.12 |
-| `SENTS_F` | 99.04 |
-| `DEP_UAS` | 91.13 |
-| `DEP_LAS` | 87.91 |
-| `TAG_ACC` | 98.13 |
-| `LEMMA_ACC` | 97.40 |
-| `ENTS_P` | 80.36 |
-| `ENTS_R` | 80.33 |
-| `ENTS_F` | 80.34 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.813976378
     - name: NER Recall
       type: recall
+      value: 0.8026528632
     - name: NER F Score
       type: f_score
+      value: 0.8082749633
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9819323347
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9819323347
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9783531116
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9790422001
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9122178499
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.880572414
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9897630886
 ---
 ### Details: https://spacy.io/models/ca#ca_core_news_sm
 | Feature | Description |
 | --- | --- |
 | **Name** | `ca_core_news_sm` |
+| **Version** | `3.5.0` |
+| **spaCy** | `>=3.5.0,<3.6.0` |
 | **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 | Type | Score |
 | --- | --- |
+| `TOKEN_ACC` | 99.93 |
 | `TOKEN_P` | 99.78 |
 | `TOKEN_R` | 99.79 |
 | `TOKEN_F` | 99.79 |
+| `POS_ACC` | 98.19 |
+| `MORPH_ACC` | 97.84 |
+| `MORPH_MICRO_P` | 99.39 |
+| `MORPH_MICRO_R` | 98.74 |
+| `MORPH_MICRO_F` | 99.06 |
 | `SENTS_P` | 98.95 |
+| `SENTS_R` | 99.01 |
+| `SENTS_F` | 98.98 |
+| `DEP_UAS` | 91.22 |
+| `DEP_LAS` | 88.06 |
+| `TAG_ACC` | 98.19 |
+| `LEMMA_ACC` | 97.90 |
+| `ENTS_P` | 81.40 |
+| `ENTS_R` | 80.27 |
+| `ENTS_F` | 80.83 |

accuracy.json CHANGED Viewed

@@ -1,68 +1,68 @@
 {
-  "token_acc": 0.9996638134,
   "token_p": 0.9978112128,
   "token_r": 0.9979488063,
   "token_f": 0.9978800048,
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-  "morph_acc": 0.9778103575,
-  "morph_micro_p": 0.993700189,
-  "morph_micro_r": 0.9871653504,
-  "morph_micro_f": 0.9904219906,
   "morph_per_feat": {
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@@ -70,9 +70,9 @@
       "f": 0.9886178862
     },
     "Case": {
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-      "r": 0.9850124896,
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@@ -85,19 +85,19 @@
       "f": 0.9979064899
     },
     "Degree": {
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-      "r": 0.9964664311,
-      "f": 0.9964664311
     },
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@@ -115,136 +115,136 @@
       "f": 0.8571428571
     }
   },
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@@ -252,14 +252,14 @@
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@@ -272,32 +272,32 @@
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-  "speed": 6421.3346218742
 }

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