Update spaCy pipeline

.gitattributes

@@ -19,3 +19,4 @@
 *strings.json filter=lfs diff=lfs merge=lfs -text
 vectors filter=lfs diff=lfs merge=lfs -text
 model filter=lfs diff=lfs merge=lfs -text
+*key2row filter=lfs diff=lfs merge=lfs -text

LICENSES_SOURCES

@@ -878,446 +878,6 @@ Creative Commons may be contacted at creativecommons.org.
 
 
 
-# Sprogteknologisk orddatabase over det danske sprog
-
-* Author: Center for Language Technology, University of Copenhagen
-* URL: https://cst.ku.dk/sto_ordbase/
-* License: CC BY-SA 4.0
-
-```
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-
 # Maltehb/danish-bert-botxo
 
 * Author: BotXO.ai
@@ -1325,6 +885,8 @@ Creative Commons may be contacted at creativecommons.org.
 * License: CC BY 4.0
 
 ```
+Creative Commons Attribution 4.0 International Public License
+
 By exercising the Licensed Rights (defined below), You accept and agree to be bound by the terms and conditions of this Creative Commons Attribution 4.0 International Public License ("Public License"). To the extent this Public License may be interpreted as a contract, You are granted the Licensed Rights in consideration of Your acceptance of these terms and conditions, and the Licensor grants You such rights in consideration of benefits the Licensor receives from making the Licensed Material available under these terms and conditions.
 
 Section 1 – Definitions.

README.md

@@ -14,61 +14,76 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.7784313725
+      value: 0.8106995885
     - name: NER Recall
       type: recall
-      value: 0.8270833333
+      value: 0.8208333333
     - name: NER F Score
       type: f_score
-      value: 0.802020202
+      value: 0.8157349896
+  - task:
+      name: TAG
+      type: token-classification
+    metrics:
+    - name: TAG (XPOS) Accuracy
+      type: accuracy
+      value: 0.9763184658
   - task:
       name: POS
       type: token-classification
     metrics:
-    - name: POS Accuracy
+    - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9734127561
+      value: 0.9763184658
   - task:
-      name: SENTER
+      name: MORPH
       type: token-classification
     metrics:
-    - name: SENTER Precision
-      type: precision
-      value: 0.8057921635
-    - name: SENTER Recall
-      type: recall
-      value: 0.8386524823
-    - name: SENTER F Score
-      type: f_score
-      value: 0.8218940052
+    - name: Morph (UFeats) Accuracy
+      type: accuracy
+      value: 0.97360647
   - task:
-      name: UNLABELED_DEPENDENCIES
+      name: LEMMA
       type: token-classification
     metrics:
-    - name: Unlabeled Dependencies Accuracy
+    - name: Lemma Accuracy
       type: accuracy
-      value: 0.8639535533
+      value: 0.9458595642
+  - task:
+      name: UNLABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Unlabeled Attachment Score (UAS)
+      type: f_score
+      value: 0.8620092701
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
-    - name: Labeled Dependencies Accuracy
-      type: accuracy
-      value: 0.8639535533
+    - name: Labeled Attachment Score (LAS)
+      type: f_score
+      value: 0.8339289703
+  - task:
+      name: SENTS
+      type: token-classification
+    metrics:
+    - name: Sentences F-Score
+      type: f_score
+      value: 0.8692579505
 ---
 ### Details: https://spacy.io/models/da#da_core_news_trf
 
-Danish transformer pipeline (Maltehb/danish-bert-botxo). Components: transformer, morphologizer, parser, ner, attribute_ruler, lemmatizer.
+Danish transformer pipeline (Maltehb/danish-bert-botxo). Components: transformer, morphologizer, parser, lemmatizer (trainable_lemmatizer), ner, attribute_ruler.
 
 | Feature | Description |
 | --- | --- |
 | **Name** | `da_core_news_trf` |
-| **Version** | `3.2.0` |
-| **spaCy** | `>=3.2.0,<3.3.0` |
-| **Default Pipeline** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
-| **Components** | `transformer`, `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
+| **Version** | `3.3.0` |
+| **spaCy** | `>=3.3.0.dev0,<3.4.0` |
+| **Default Pipeline** | `transformer`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
+| **Components** | `transformer`, `morphologizer`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
-| **Sources** | [UD Danish DDT v2.8](https://github.com/UniversalDependencies/UD_Danish-DDT) (Johannsen, Anders; Martínez Alonso, Héctor; Plank, Barbara)<br />[DaNE](https://github.com/alexandrainst/danlp/blob/master/docs/datasets.md#danish-dependency-treebank-dane) (Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders Søgaard)<br />[Sprogteknologisk orddatabase over det danske sprog](https://cst.ku.dk/sto_ordbase/) (Center for Language Technology, University of Copenhagen)<br />[Maltehb/danish-bert-botxo](https://huggingface.co/Maltehb/danish-bert-botxo) (BotXO.ai) |
+| **Sources** | [UD Danish DDT v2.8](https://github.com/UniversalDependencies/UD_Danish-DDT) (Johannsen, Anders; Martínez Alonso, Héctor; Plank, Barbara)<br />[DaNE](https://github.com/alexandrainst/danlp/blob/master/docs/datasets.md#danish-dependency-treebank-dane) (Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders Søgaard)<br />[Maltehb/danish-bert-botxo](https://huggingface.co/Maltehb/danish-bert-botxo) (BotXO.ai) |
 | **License** | `CC BY-SA 4.0` |
 | **Author** | [Explosion](https://explosion.ai) |
 
@@ -94,18 +109,18 @@ Danish transformer pipeline (Maltehb/danish-bert-botxo). Components: transformer
 | `TOKEN_P` | 99.78 |
 | `TOKEN_R` | 99.75 |
 | `TOKEN_F` | 99.76 |
-| `POS_ACC` | 97.34 |
-| `MORPH_ACC` | 97.00 |
-| `MORPH_MICRO_P` | 98.74 |
-| `MORPH_MICRO_R` | 97.64 |
-| `MORPH_MICRO_F` | 98.19 |
-| `SENTS_P` | 80.58 |
-| `SENTS_R` | 83.87 |
-| `SENTS_F` | 82.19 |
-| `DEP_UAS` | 86.40 |
-| `DEP_LAS` | 83.27 |
-| `TAG_ACC` | 97.34 |
-| `LEMMA_ACC` | 84.91 |
-| `ENTS_P` | 77.84 |
-| `ENTS_R` | 82.71 |
-| `ENTS_F` | 80.20 |
+| `POS_ACC` | 97.63 |
+| `MORPH_ACC` | 97.36 |
+| `MORPH_MICRO_P` | 98.75 |
+| `MORPH_MICRO_R` | 98.03 |
+| `MORPH_MICRO_F` | 98.39 |
+| `SENTS_P` | 86.62 |
+| `SENTS_R` | 87.23 |
+| `SENTS_F` | 86.93 |
+| `DEP_UAS` | 86.20 |
+| `DEP_LAS` | 83.39 |
+| `LEMMA_ACC` | 94.59 |
+| `TAG_ACC` | 97.63 |
+| `ENTS_P` | 81.07 |
+| `ENTS_R` | 82.08 |
+| `ENTS_F` | 81.57 |

accuracy.json

@@ -3,51 +3,51 @@
   "token_p": 0.9977732598,
   "token_r": 0.9974835463,
   "token_f": 0.997628382,
-  "pos_acc": 0.9734127561,
-  "morph_acc": 0.9700227614,
-  "morph_micro_p": 0.9874419317,
-  "morph_micro_r": 0.9763767604,
-  "morph_micro_f": 0.9818781726,
+  "pos_acc": 0.9763184658,
+  "morph_acc": 0.97360647,
+  "morph_micro_p": 0.9874911014,
+  "morph_micro_r": 0.98026349,
+  "morph_micro_f": 0.9838640221,
   "morph_per_feat": {
     "Mood": {
-      "p": 0.9923298178,
-      "r": 0.9866539561,
-      "f": 0.9894837476
+      "p": 0.9942638623,
+      "r": 0.9914204004,
+      "f": 0.9928400955
     },
     "Tense": {
-      "p": 0.9832953683,
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@@ -55,9 +55,9 @@
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@@ -65,19 +65,19 @@
       "f": 0.9839857651
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@@ -100,14 +100,14 @@
       "f": 0.9942857143
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@@ -115,131 +115,131 @@
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@@ -247,14 +247,14 @@
       "f": 0.0
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@@ -262,24 +262,24 @@
       "f": 0.0
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@@ -287,32 +287,32 @@
       "f": 0.0
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+  "speed": 451.6438624119
 }

config.cfg

@@ -10,7 +10,7 @@ seed = 1
 
 [nlp]
 lang = "da"
-pipeline = ["transformer","morphologizer","parser","attribute_ruler","lemmatizer","ner"]
+pipeline = ["transformer","morphologizer","parser","lemmatizer","attribute_ruler","ner"]
 disabled = []
 before_creation = null
 after_creation = null
@@ -26,11 +26,23 @@ scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
 validate = false
 
 [components.lemmatizer]
-factory = "lemmatizer"
-mode = "lookup"
-model = null
+factory = "trainable_lemmatizer"
+backoff = "orth"
+min_tree_freq = 3
 overwrite = false
 scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
+top_k = 1
+
+[components.lemmatizer.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.lemmatizer.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+upstream = "transformer"
+pooling = {"@layers":"reduce_mean.v1"}
 
 [components.morphologizer]
 factory = "morphologizer"
@@ -39,8 +51,9 @@ overwrite = true
 scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
 
 [components.morphologizer.model]
-@architectures = "spacy.Tagger.v1"
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 
 [components.morphologizer.model.tok2vec]
 @architectures = "spacy-transformers.TransformerListener.v1"
@@ -142,7 +155,7 @@ dropout = 0.1
 accumulate_gradient = 3
 patience = 5000
 max_epochs = 0
-max_steps = 20000
+max_steps = 16000
 eval_frequency = 1000
 frozen_components = []
 before_to_disk = null
@@ -176,17 +189,17 @@ total_steps = 20000
 initial_rate = 0.00005
 
 [training.score_weights]
-pos_acc = 0.08
-morph_acc = 0.08
+pos_acc = 0.14
+morph_acc = 0.14
 morph_per_feat = null
 dep_uas = 0.0
-dep_las = 0.16
+dep_las = 0.29
 dep_las_per_type = null
 sents_p = null
 sents_r = null
-sents_f = 0.02
-lemma_acc = 0.5
-ents_f = 0.16
+sents_f = 0.04
+lemma_acc = 0.1
+ents_f = 0.29
 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null
@@ -203,6 +216,13 @@ after_init = null
 
 [initialize.components]
 
+[initialize.components.lemmatizer]
+
+[initialize.components.lemmatizer.labels]
+@readers = "spacy.read_labels.v1"
+path = "corpus/labels/trainable_lemmatizer.json"
+require = false
+
 [initialize.components.morphologizer]
 
 [initialize.components.morphologizer.labels]

da_core_news_trf-any-py3-none-any.whl

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 version https://git-lfs.github.com/spec/v1
-oid sha256:1ac3b39be8adc4426c9d1083986d08767b564b40dec4fcfd3c6f2547083a8efa
-size 418019836
+oid sha256:28f147c7a0787272245429a6eedec0f834a98ebb48ab421b3ef75c4081bd52c5
+size 413499670

lemmatizer/cfg

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meta.json

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 {
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-  "description":"Danish transformer pipeline (Maltehb/danish-bert-botxo). Components: transformer, morphologizer, parser, ner, attribute_ruler, lemmatizer.",
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+  "description":"Danish transformer pipeline (Maltehb/danish-bert-botxo). Components: transformer, morphologizer, parser, lemmatizer (trainable_lemmatizer), ner, attribute_ruler.",
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