Update spaCy pipeline

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Files changed (14) hide show

README.md +25 -25
accuracy.json +156 -156
attribute_ruler/patterns +0 -0
config.cfg +5 -4
lemmatizer/model +1 -1
meta.json +159 -159
morphologizer/model +1 -1
ner/model +2 -2
parser/model +1 -1
pt_core_news_lg-any-py3-none-any.whl +2 -2
senter/model +1 -1
tok2vec/model +2 -2
tokenizer +2 -1
vocab/strings.json +2 -2

README.md CHANGED Viewed

@@ -14,34 +14,34 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.9000117772
     - name: NER Recall
       type: recall
-      value: 0.9023675044
     - name: NER F Score
       type: f_score
-      value: 0.9011881013
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.8953833961
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9695858926
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9582445886
   - task:
       name: LEMMA
       type: token-classification
@@ -55,21 +55,21 @@ model-index:
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9012559051
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8612743404
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9457198725
 ---
 ### Details: https://spacy.io/models/pt#pt_core_news_lg
@@ -78,8 +78,8 @@ Portuguese pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
 | Feature | Description |
 | --- | --- |
 | **Name** | `pt_core_news_lg` |
-| **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, 500000 unique vectors (300 dimensions) |
@@ -109,18 +109,18 @@ Portuguese pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
 | `TOKEN_P` | 99.88 |
 | `TOKEN_R` | 99.95 |
 | `TOKEN_F` | 99.92 |
-| `POS_ACC` | 96.96 |
-| `MORPH_ACC` | 95.82 |
-| `MORPH_MICRO_P` | 98.15 |
-| `MORPH_MICRO_R` | 97.83 |
-| `MORPH_MICRO_F` | 97.99 |
-| `SENTS_P` | 93.23 |
-| `SENTS_R` | 95.96 |
-| `SENTS_F` | 94.57 |
-| `DEP_UAS` | 90.13 |
-| `DEP_LAS` | 86.13 |
 | `LEMMA_ACC` | 97.30 |
-| `TAG_ACC` | 89.54 |
-| `ENTS_P` | 90.00 |
-| `ENTS_R` | 90.24 |
-| `ENTS_F` | 90.12 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.9016596045
     - name: NER Recall
       type: recall
+      value: 0.9045519847
     - name: NER F Score
       type: f_score
+      value: 0.9031034788
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.8951305295
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9694357755
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.958640844
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9021776702
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.8624265468
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9512921022
 ---
 ### Details: https://spacy.io/models/pt#pt_core_news_lg
 | Feature | Description |
 | --- | --- |
 | **Name** | `pt_core_news_lg` |
+| **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, 500000 unique vectors (300 dimensions) |
 | `TOKEN_P` | 99.88 |
 | `TOKEN_R` | 99.95 |
 | `TOKEN_F` | 99.92 |
+| `POS_ACC` | 96.94 |
+| `MORPH_ACC` | 95.86 |
+| `MORPH_MICRO_P` | 98.21 |
+| `MORPH_MICRO_R` | 97.69 |
+| `MORPH_MICRO_F` | 97.95 |
+| `SENTS_P` | 93.99 |
+| `SENTS_R` | 96.30 |
+| `SENTS_F` | 95.13 |
+| `DEP_UAS` | 90.22 |
+| `DEP_LAS` | 86.24 |
 | `LEMMA_ACC` | 97.30 |
+| `TAG_ACC` | 89.51 |
+| `ENTS_P` | 90.17 |
+| `ENTS_R` | 90.46 |
+| `ENTS_F` | 90.31 |

accuracy.json CHANGED Viewed

@@ -3,61 +3,61 @@
   "token_p": 0.9988117635,
   "token_r": 0.9995045581,
   "token_f": 0.9991580407,
-  "pos_acc": 0.9695858926,
-  "morph_acc": 0.9582445886,
-  "morph_micro_p": 0.981544665,
-  "morph_micro_r": 0.9783079143,
-  "morph_micro_f": 0.9799236168,
   "morph_per_feat": {
     "Mood": {
-      "p": 0.9854191981,
-      "r": 0.9806529625,
-      "f": 0.983030303
     },
     "Number": {
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-      "r": 0.9890982713,
-      "f": 0.9912595599
     },
     "Person": {
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       "r": 0.9722518677,
-      "f": 0.9717333333
     },
     "Tense": {
-      "p": 0.9438058748,
-      "r": 0.9723684211,
-      "f": 0.9578742709
     },
     "VerbForm": {
-      "p": 0.9708890637,
-      "r": 0.9778129952,
-      "f": 0.9743387288
     },
     "Gender": {
-      "p": 0.9708381615,
-      "r": 0.9613692867,
-      "f": 0.9660805227
     },
     "PronType": {
-      "p": 0.9906396256,
-      "r": 0.984496124,
-      "f": 0.9875583204
     },
     "Definite": {
-      "p": 0.9972807614,
       "r": 0.993902439,
-      "f": 0.9955887343
     },
     "NumType": {
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-      "r": 0.9737704918,
-      "f": 0.9705882353
     },
     "Voice": {
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-      "r": 0.9186046512,
-      "f": 0.9239766082
     },
     "Polarity": {
       "p": 1.0,
@@ -65,151 +65,146 @@
       "f": 1.0
     },
     "Case": {
-      "p": 0.94,
-      "r": 0.9591836735,
-      "f": 0.9494949495
     }
   },
-  "sents_p": 0.93225058,
-  "sents_r": 0.9595840835,
-  "sents_f": 0.9457198725,
-  "dep_uas": 0.9012559051,
-  "dep_las": 0.8612743404,
   "dep_las_per_type": {
     "cop": {
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-      "f": 0.8918918919
     },
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-      "r": 0.9035714286,
-      "f": 0.908438061
     },
     "det": {
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-      "r": 0.9659714599,
-      "f": 0.9680968097
     },
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-      "r": 0.9390243902,
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     },
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     },
     "nmod": {
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     "flat:name": {
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     "acl": {
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     },
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     },
     "obl": {
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-      "f": 0.6790505676
     },
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-      "f": 0.8965517241
     },
     "obj": {
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     "obl:agent": {
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     },
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-      "r": 0.8,
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     },
     "iobj": {
-      "p": 0.5,
-      "r": 0.2272727273,
-      "f": 0.3125
     },
     "appos": {
-      "p": 0.6235294118,
-      "r": 0.6463414634,
-      "f": 0.6347305389
     },
     "fixed": {
-      "p": 0.8039215686,
-      "r": 0.7321428571,
-      "f": 0.7663551402
     },
     "nummod": {
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-      "r": 0.9487179487,
-      "f": 0.9548387097
-    },
-    "dep": {
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     "aux": {
-      "p": 0.9230769231,
-      "r": 0.9677419355,
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       "r": 0.375,
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@@ -222,19 +217,19 @@
       "f": 1.0
     },
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@@ -242,62 +237,67 @@
       "f": 0.0
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   },
-  "speed": 9207.0798974617
 }

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   "token_r": 0.9995045581,
   "token_f": 0.9991580407,
+  "pos_acc": 0.9694357755,
+  "morph_acc": 0.958640844,
+  "morph_micro_p": 0.9820781104,
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   "morph_per_feat": {
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   "lemma_acc": 0.9730077757,
+  "tag_acc": 0.8951305295,
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