Update spaCy pipeline

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Files changed (14) hide show

README.md +26 -26
accuracy.json +158 -158
attribute_ruler/patterns +0 -0
config.cfg +5 -4
lemmatizer/model +1 -1
meta.json +161 -161
morphologizer/model +1 -1
ner/model +2 -2
parser/model +1 -1
pt_core_news_md-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

@@ -14,62 +14,62 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8956672035
     - name: NER Recall
       type: recall
-      value: 0.8974475036
     - name: NER F Score
       type: f_score
-      value: 0.8965564698
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.8961656594
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9702764292
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9565561995
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9704323709
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.9010773751
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.8627722088
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9412168385
 ---
 ### Details: https://spacy.io/models/pt#pt_core_news_md
@@ -78,8 +78,8 @@ Portuguese pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
 | Feature | Description |
 | --- | --- |
 | **Name** | `pt_core_news_md` |
-| **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, 20000 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` | 97.03 |
-| `MORPH_ACC` | 95.66 |
-| `MORPH_MICRO_P` | 97.97 |
-| `MORPH_MICRO_R` | 97.75 |
-| `MORPH_MICRO_F` | 97.86 |
-| `SENTS_P` | 92.55 |
-| `SENTS_R` | 95.75 |
-| `SENTS_F` | 94.12 |
-| `DEP_UAS` | 90.11 |
-| `DEP_LAS` | 86.28 |
-| `LEMMA_ACC` | 97.04 |
 | `TAG_ACC` | 89.62 |
-| `ENTS_P` | 89.57 |
-| `ENTS_R` | 89.74 |
-| `ENTS_F` | 89.66 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.8937657035
     - name: NER Recall
       type: recall
+      value: 0.8960699034
     - name: NER F Score
       type: f_score
+      value: 0.8949163203
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.8962306206
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9702313141
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9534422982
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9703333168
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.9013711257
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.8593155894
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9457981824
 ---
 ### Details: https://spacy.io/models/pt#pt_core_news_md
 | Feature | Description |
 | --- | --- |
 | **Name** | `pt_core_news_md` |
+| **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, 20000 unique vectors (300 dimensions) |
 | `TOKEN_P` | 99.88 |
 | `TOKEN_R` | 99.95 |
 | `TOKEN_F` | 99.92 |
+| `POS_ACC` | 97.02 |
+| `MORPH_ACC` | 95.34 |
+| `MORPH_MICRO_P` | 97.84 |
+| `MORPH_MICRO_R` | 97.51 |
+| `MORPH_MICRO_F` | 97.68 |
+| `SENTS_P` | 93.47 |
+| `SENTS_R` | 95.98 |
+| `SENTS_F` | 94.58 |
+| `DEP_UAS` | 90.14 |
+| `DEP_LAS` | 85.93 |
+| `LEMMA_ACC` | 97.03 |
 | `TAG_ACC` | 89.62 |
+| `ENTS_P` | 89.38 |
+| `ENTS_R` | 89.61 |
+| `ENTS_F` | 89.49 |

accuracy.json CHANGED Viewed

@@ -3,148 +3,148 @@
   "token_p": 0.9988117635,
   "token_r": 0.9995045581,
   "token_f": 0.9991580407,
-  "pos_acc": 0.9702764292,
-  "morph_acc": 0.9565561995,
-  "morph_micro_p": 0.9796550656,
-  "morph_micro_r": 0.9775350371,
-  "morph_micro_f": 0.9785939031,
   "morph_per_feat": {
     "Mood": {
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       "r": 0.9794437727,
-      "f": 0.9788519637
     },
     "Number": {
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-      "r": 0.9881638374,
-      "f": 0.9902458057
     },
     "Person": {
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-      "r": 0.9797225187,
-      "f": 0.977115487
     },
     "Tense": {
-      "p": 0.9402795426,
-      "r": 0.9736842105,
-      "f": 0.9566903685
     },
     "VerbForm": {
-      "p": 0.975571316,
-      "r": 0.9809825674,
-      "f": 0.9782694587
     },
     "Gender": {
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-      "r": 0.9575444636,
-      "f": 0.9615901671
     },
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     "Definite": {
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-      "f": 0.9952477936
     },
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-      "r": 0.9770491803,
-      "f": 0.9706840391
     },
     "Voice": {
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       "r": 0.9302325581,
-      "f": 0.9142857143
     },
     "Polarity": {
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-      "r": 1.0,
-      "f": 0.9931034483
     },
     "Case": {
-      "p": 0.9285714286,
-      "r": 0.9285714286,
-      "f": 0.9285714286
     }
   },
-  "sents_p": 0.9255220912,
-  "sents_r": 0.9574530624,
-  "sents_f": 0.9412168385,
-  "dep_uas": 0.9010773751,
-  "dep_las": 0.8627722088,
   "dep_las_per_type": {
     "cop": {
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       "r": 0.9361702128,
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     "det": {
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-      "r": 0.9703622393,
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     },
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-      "r": 0.979578813,
-      "f": 0.9786420147
     },
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-      "r": 0.6034482759,
-      "f": 0.6222222222
     },
     "advmod": {
-      "p": 0.8242074928,
-      "r": 0.8125,
-      "f": 0.8183118741
     },
     "obl": {
-      "p": 0.7002012072,
-      "r": 0.7160493827,
-      "f": 0.7080366226
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@@ -152,59 +152,64 @@
       "f": 0.84375
     },
     "acl:relcl": {
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-      "r": 0.7452830189,
-      "f": 0.738317757
     },
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-      "r": 0.792,
-      "f": 0.7764705882
     },
     "iobj": {
-      "p": 0.3,
-      "r": 0.1363636364,
-      "f": 0.1875
     },
     "appos": {
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-      "f": 0.6018237082
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     "fixed": {
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-      "f": 0.9646302251
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     },
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-      "r": 0.375,
-      "f": 0.4285714286
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-      "f": 0.6788990826
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     "orphan": {
       "p": 0.0,
@@ -218,18 +223,18 @@
     },
     "aux:pass": {
       "p": 1.0,
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     "list": {
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@@ -237,19 +242,14 @@
       "f": 0.0
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     "expl": {
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@@ -257,9 +257,9 @@
       "f": 0.0
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@@ -272,32 +272,32 @@
       "f": 0.8571428571
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-  "lemma_acc": 0.9704323709,
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   },
-  "speed": 11566.5552368993
 }

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+  "pos_acc": 0.9702313141,
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