Update spaCy pipeline

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Files changed (12) hide show

README.md +28 -28
accuracy.json +157 -157
attribute_ruler/patterns +0 -0
ca_core_news_lg-any-py3-none-any.whl +2 -2
config.cfg +5 -4
meta.json +160 -160
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: 0.8483365949
     - name: NER Recall
       type: recall
-      value: 0.8414752507
     - name: NER F Score
       type: f_score
-      value: 0.8448919929
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9851667874
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9851667874
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9822603596
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9759558602
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9191074185
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8895833532
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9880081895
 ---
 ### Details: https://spacy.io/models/ca#ca_core_news_lg
@@ -78,8 +78,8 @@ Catalan pipeline optimized for CPU. Components: tok2vec, morphologizer, parser,
 | Feature | Description |
 | --- | --- |
 | **Name** | `ca_core_news_lg` |
-| **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** | 500000 keys, 500000 unique vectors (300 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` | 98.52 |
-| `MORPH_ACC` | 98.23 |
-| `MORPH_MICRO_P` | 99.57 |
-| `MORPH_MICRO_R` | 99.08 |
-| `MORPH_MICRO_F` | 99.33 |
-| `SENTS_P` | 98.77 |
-| `SENTS_R` | 98.83 |
-| `SENTS_F` | 98.80 |
-| `DEP_UAS` | 91.91 |
-| `DEP_LAS` | 88.96 |
-| `TAG_ACC` | 98.52 |
-| `LEMMA_ACC` | 97.60 |
-| `ENTS_P` | 84.83 |
-| `ENTS_R` | 84.15 |
-| `ENTS_F` | 84.49 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.8481469334
     - name: NER Recall
       type: recall
+      value: 0.8366224523
     - name: NER F Score
       type: f_score
+      value: 0.8423452769
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9846920735
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9846920735
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9818721217
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9805595069
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9176385395
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.8876925862
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9906377999
 ---
 ### Details: https://spacy.io/models/ca#ca_core_news_lg
 | Feature | Description |
 | --- | --- |
 | **Name** | `ca_core_news_lg` |
+| **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** | 500000 keys, 500000 unique vectors (300 dimensions) |
 | Type | Score |
 | --- | --- |
+| `TOKEN_ACC` | 99.93 |
 | `TOKEN_P` | 99.78 |
 | `TOKEN_R` | 99.79 |
 | `TOKEN_F` | 99.79 |
+| `POS_ACC` | 98.47 |
+| `MORPH_ACC` | 98.19 |
+| `MORPH_MICRO_P` | 99.56 |
+| `MORPH_MICRO_R` | 99.05 |
+| `MORPH_MICRO_F` | 99.30 |
+| `SENTS_P` | 99.06 |
+| `SENTS_R` | 99.06 |
+| `SENTS_F` | 99.06 |
+| `DEP_UAS` | 91.76 |
+| `DEP_LAS` | 88.77 |
+| `TAG_ACC` | 98.47 |
+| `LEMMA_ACC` | 98.06 |
+| `ENTS_P` | 84.81 |
+| `ENTS_R` | 83.66 |
+| `ENTS_F` | 84.23 |

accuracy.json CHANGED Viewed

@@ -1,78 +1,78 @@
 {
-  "token_acc": 0.9996638134,
   "token_p": 0.9978112128,
   "token_r": 0.9979488063,
   "token_f": 0.9978800048,
-  "pos_acc": 0.9851667874,
-  "morph_acc": 0.9822603596,
-  "morph_micro_p": 0.9957073404,
-  "morph_micro_r": 0.9908210401,
-  "morph_micro_f": 0.9932581808,
   "morph_per_feat": {
     "Mood": {
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-      "r": 0.9936059678,
-      "f": 0.9928124584
     },
     "Gender": {
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     "NumType": {
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-      "f": 0.9663028002
     },
     "Definite": {
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-      "r": 0.9917501473,
-      "f": 0.9922617732
     },
     "PronType": {
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-      "r": 0.9920608108,
-      "f": 0.9938655498
     },
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-      "r": 0.9976294675,
-      "f": 0.9986310121
     },
     "NumForm": {
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-      "r": 0.981741573,
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     },
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-      "r": 0.9933388843,
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     "PrepCase": {
       "p": 0.9986168741,
@@ -86,23 +86,23 @@
     },
     "Degree": {
       "p": 1.0,
-      "r": 0.9893992933,
-      "f": 0.9946714032
     },
     "Poss": {
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     },
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-      "f": 0.9975845411
     },
     "Number[psor]": {
       "p": 1.0,
@@ -115,136 +115,136 @@
       "f": 1.0
     }
   },
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-  "sents_r": 0.9882972499,
-  "sents_f": 0.9880081895,
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   "dep_las_per_type": {
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@@ -252,14 +252,14 @@
       "f": 0.0
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@@ -272,32 +272,32 @@
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   },
-  "speed": 6379.2212982198
 }

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