Updated readme

README.md

@@ -3,19 +3,20 @@ tags:
 - spacy
 - dacy
 - danish
-- named entity recognition
+- token-classification
 - pos tagging
+- morphological analysis
 - lemmatization
 - dependency parsing
+- named entity recognition
 - coreference resolution
 - named entity linking
 - named entity disambiguation
-- token-classification
 language:
 - da
 license: apache-2.0
 model-index:
-- name: da_dacy_medium_trf
+- name: da_dacy_medium_trf-0.2.0
   results:
   - task:
       name: NER
@@ -70,6 +71,18 @@ model-index:
       split: test
       type: universal_dependencies
       config: da_ddt
+  - task:
+      name: LEMMA
+      type: token-classification
+    metrics:
+    - name: Lemma Accuracy
+      type: accuracy
+      value: 0.9419805438
+    dataset:
+      name: UD Danish DDT
+      split: test
+      type: universal_dependencies
+      config: da_ddt
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
@@ -137,16 +150,12 @@ model-index:
 library_name: spacy
 datasets:
 - universal_dependencies
-- alexandrainst/dacoref
 - dane
+- alexandrainst/dacoref
 metrics:
 - accuracy
 ---
 
-
-
-
-
 <a href="https://github.com/centre-for-humanities-computing/Dacy"><img src="https://centre-for-humanities-computing.github.io/DaCy/_static/icon.png" width="175" height="175" align="right" /></a>
 
 # DaCy medium
@@ -157,6 +166,7 @@ parsing for Danish on the Danish Dependency treebank as well as competitive perf
 To read more check out the [DaCy repository](https://github.com/centre-for-humanities-computing/DaCy) for material on how to use DaCy and reproduce the results. 
 DaCy also contains guides on usage of the package as well as behavioural test for biases and robustness of Danish NLP pipelines.
 
+
 | Feature | Description |
 | --- | --- |
 | **Name** | `da_dacy_medium_trf` |
@@ -166,7 +176,7 @@ DaCy also contains guides on usage of the package as well as behavioural test fo
 | **Components** | `transformer`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `parser`, `ner`, `coref`, `span_resolver`, `span_cleaner`, `entity_linker` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
 | **Sources** | [UD Danish DDT v2.11](https://github.com/UniversalDependencies/UD_Danish-DDT) (Johannsen, Anders; Martínez Alonso, Héctor; Plank, Barbara)<br />[DaNE](https://huggingface.co/datasets/dane) (Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders Søgaard)<br />[DaCoref](https://huggingface.co/datasets/alexandrainst/dacoref) (Buch-Kromann, Matthias)<br />[DaNED](https://danlp-alexandra.readthedocs.io/en/stable/docs/datasets.html#daned) (Barrett, M. J., Lam, H., Wu, M., Lacroix, O., Plank, B., & Søgaard, A.)<br />[vesteinn/DanskBERT](https://huggingface.co/vesteinn/DanskBERT) (Vésteinn Snæbjarnarson) |
-| **License** | `Apache-2.0 License` |
+| **License** | `Apache-2.0` |
 | **Author** | [Kenneth Enevoldsen](https://chcaa.io/#/) |
 
 ### Label Scheme
@@ -184,8 +194,7 @@ DaCy also contains guides on usage of the package as well as behavioural test fo
 
 </details>
 
-### Performance Metrics
-
+### Accuracy
 
 | Type | Score |
 | --- | --- |
@@ -207,6 +216,7 @@ DaCy also contains guides on usage of the package as well as behavioural test fo
 | `ENTS_P` | 87.08 |
 | `ENTS_R` | 84.59 |
 | `ENTS_F` | 85.82 |
+| `LEMMA_ACC` | 94.20 |
 | `COREF_LEA_F1` | 41.18 |
 | `COREF_LEA_PRECISION` | 48.89 |
 | `COREF_LEA_RECALL` | 35.58 |

meta.json

@@ -1,23 +1,25 @@
 {
-  "lang": "da",
-  "name": "dacy_medium_trf",
-  "version": "0.2.0",
-  "description": "\n<a href=\"https://github.com/centre-for-humanities-computing/Dacy\"><img src=\"https://centre-for-humanities-computing.github.io/DaCy/_static/icon.png\" width=\"175\" height=\"175\" align=\"right\" /></a>\n\n# DaCy medium\n\nDaCy is a Danish language processing framework with state-of-the-art pipelines as well as functionality for analysing Danish pipelines.\nDaCy's largest pipeline has achieved State-of-the-Art performance on parts-of-speech tagging and dependency \nparsing for Danish on the DaNE dataset. To read more check out the [DaCy repository](https://github.com/centre-for-humanities-computing/DaCy) for material on how to use DaCy and reproduce the results. \nDaCy also contains guides on usage of the package as well as behavioural test for biases and robustness of Danish NLP pipelines.\n",
-  "author": "Kenneth Enevoldsen",
-  "email": "[email protected]",
-  "url": "https://chcaa.io/#/",
-  "license": "Apache-2.0",
-  "spacy_version": ">=3.5.2,<3.6.0",
-  "spacy_git_version": "Unknown",
-  "vectors": {
-    "width": 0,
-    "vectors": 0,
-    "keys": 0,
-    "name": null
+  "lang":"da",
+  "name":"dacy_medium_trf",
+  "version":"0.2.0",
+  "description":"\n<a href=\"https://github.com/centre-for-humanities-computing/Dacy\"><img src=\"https://centre-for-humanities-computing.github.io/DaCy/_static/icon.png\" width=\"175\" height=\"175\" align=\"right\" /></a>\n\n# DaCy medium\n\nDaCy is a Danish language processing framework with state-of-the-art pipelines as well as functionality for analysing Danish pipelines.\nDaCy's largest pipeline has achieved State-of-the-Art performance on parts-of-speech tagging and dependency \nparsing for Danish on the Danish Dependency treebank as well as competitive performance on named entity recognition, named entity disambiguation and coreference resolution. \nTo read more check out the [DaCy repository](https://github.com/centre-for-humanities-computing/DaCy) for material on how to use DaCy and reproduce the results. \nDaCy also contains guides on usage of the package as well as behavioural test for biases and robustness of Danish NLP pipelines.\n",
+  "author":"Kenneth Enevoldsen",
+  "email":"[email protected]",
+  "url":"https://chcaa.io/#/",
+  "license":"Apache-2.0",
+  "spacy_version":">=3.5.2,<3.6.0",
+  "spacy_git_version":"Unknown",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
   },
-  "labels": {
-    "transformer": [],
-    "tagger": [
+  "labels":{
+    "transformer":[
+
+    ],
+    "tagger":[
       "ADJ",
       "ADP",
       "ADV",
@@ -36,7 +38,7 @@
       "VERB",
       "X"
     ],
-    "morphologizer": [
+    "morphologizer":[
       "AdpType=Prep|POS=ADP",
       "Definite=Ind|Gender=Com|Number=Sing|POS=NOUN",
       "Mood=Ind|POS=AUX|Tense=Pres|VerbForm=Fin|Voice=Act",
@@ -196,7 +198,7 @@
       "Case=Gen|POS=NOUN",
       "POS=AUX|Tense=Pres|VerbForm=Part"
     ],
-    "parser": [
+    "parser":[
       "ROOT",
       "acl:relcl",
       "advcl",
@@ -230,17 +232,23 @@
       "punct",
       "xcomp"
     ],
-    "ner": [
+    "ner":[
       "LOC",
       "MISC",
       "ORG",
       "PER"
     ],
-    "coref": [],
-    "span_resolver": [],
-    "entity_linker": []
+    "coref":[
+
+    ],
+    "span_resolver":[
+
+    ],
+    "entity_linker":[
+
+    ]
   },
-  "pipeline": [
+  "pipeline":[
     "transformer",
     "tagger",
     "morphologizer",
@@ -252,7 +260,7 @@
     "span_cleaner",
     "entity_linker"
   ],
-  "components": [
+  "components":[
     "transformer",
     "tagger",
     "morphologizer",
@@ -264,411 +272,414 @@
     "span_cleaner",
     "entity_linker"
   ],
-  "disabled": [],
-  "requirements": [
-    "spacy-transformers>=1.2.3,<1.3.0",
-    "spacy-experimental>=0.6.2,<0.7.0"
+  "disabled":[
+
+  ],
+  "requirements":[
+    "spacy-experimental>=0.6.2,<0.7.0",
+    "spacy-transformers>=1.2.3,<1.3.0"
   ],
-  "performance": {
-    "token_acc": 0.9992023928,
-    "token_p": 0.9970089731,
-    "token_r": 0.9977052779,
-    "token_f": 0.9973570039,
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-    "tag_acc": 0.9847290149,
-    "pos_acc": 0.985677928,
-    "morph_acc": 0.9814371257,
-    "morph_micro_p": 0.9910058542,
-    "morph_micro_r": 0.9876942662,
-    "morph_micro_f": 0.989347289,
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+  "performance":{
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+    "token_r":0.9977052779,
+    "token_f":0.9973570039,
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     }
   },
-  "sources": [
+  "sources":[
     {
-      "name": "UD Danish DDT v2.11",
-      "url": "https://github.com/UniversalDependencies/UD_Danish-DDT",
-      "license": "CC BY-SA 4.0",
-      "author": "Johannsen, Anders; Mart\u00ednez Alonso, H\u00e9ctor; Plank, Barbara"
+      "name":"UD Danish DDT v2.11",
+      "url":"https://github.com/UniversalDependencies/UD_Danish-DDT",
+      "license":"CC BY-SA 4.0",
+      "author":"Johannsen, Anders; Mart\u00ednez Alonso, H\u00e9ctor; Plank, Barbara"
     },
     {
-      "name": "DaNE",
-      "url": "https://huggingface.co/datasets/dane",
-      "license": "CC BY-SA 4.0",
-      "author": "Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders S\u00f8gaard"
+      "name":"DaNE",
+      "url":"https://huggingface.co/datasets/dane",
+      "license":"CC BY-SA 4.0",
+      "author":"Rasmus Hvingelby, Amalie B. Pauli, Maria Barrett, Christina Rosted, Lasse M. Lidegaard, Anders S\u00f8gaard"
     },
     {
-      "name": "DaCoref",
-      "url": "https://huggingface.co/datasets/alexandrainst/dacoref",
-      "license": "CC BY-SA 4.0",
-      "author": "Buch-Kromann, Matthias"
+      "name":"DaCoref",
+      "url":"https://huggingface.co/datasets/alexandrainst/dacoref",
+      "license":"CC BY-SA 4.0",
+      "author":"Buch-Kromann, Matthias"
     },
     {
-      "name": "DaNED",
-      "url": "https://danlp-alexandra.readthedocs.io/en/stable/docs/datasets.html#daned",
-      "license": "CC BY-SA 4.0",
-      "author": "Barrett, M. J., Lam, H., Wu, M., Lacroix, O., Plank, B., & S\u00f8gaard, A."
+      "name":"DaNED",
+      "url":"https://danlp-alexandra.readthedocs.io/en/stable/docs/datasets.html#daned",
+      "license":"CC BY-SA 4.0",
+      "author":"Barrett, M. J., Lam, H., Wu, M., Lacroix, O., Plank, B., & S\u00f8gaard, A."
     },
     {
-      "name": "vesteinn/DanskBERT",
-      "author": "V\u00e9steinn Sn\u00e6bjarnarson",
-      "url": "https://huggingface.co/vesteinn/DanskBERT",
-      "license": "MIT"
+      "name":"vesteinn/DanskBERT",
+      "author":"V\u00e9steinn Sn\u00e6bjarnarson",
+      "url":"https://huggingface.co/vesteinn/DanskBERT",
+      "license":"MIT"
     }
   ],
-  "notes": "\n\n### Training\nThis model was trained using [spaCy](https://spacy.io) and logged to [Weights & Biases](https://wandb.ai/kenevoldsen/dacy-v0.2.0). You can find all the training logs [here](https://wandb.ai/kenevoldsen/dacy-v0.2.0)."
+  "notes":"\n\n### Training\nThis model was trained using [spaCy](https://spacy.io) and logged to [Weights & Biases](https://wandb.ai/kenevoldsen/dacy-v0.2.0). You can find all the training logs [here](https://wandb.ai/kenevoldsen/dacy-v0.2.0)."
 }