Update spaCy pipeline

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Files changed (16) hide show

README.md +33 -32
config.cfg +13 -31
functions.py +1 -4
la_core_web_sm-any-py3-none-any.whl +2 -2
meta.json +206 -203
morphologizer/model +2 -2
ner/model +2 -2
ner/moves +1 -1
parser/model +1 -1
senter/model +0 -0
tagger/model +0 -0
tok2vec/model +1 -1
trainable_lemmatizer/cfg +1406 -5775
trainable_lemmatizer/model +2 -2
trainable_lemmatizer/trees +2 -2
vocab/strings.json +0 -0

README.md CHANGED Viewed

@@ -14,72 +14,72 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.8895878166
     - name: NER Recall
       type: recall
-      value: 0.8736790766
     - name: NER F Score
       type: f_score
-      value: 0.8815616798
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
-      value: 0.9353375104
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
-      value: 0.9675397134
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
-      value: 0.9136685316
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
-      value: 0.9475930552
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
-      value: 0.8296154996
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
-      value: 0.7736889673
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
-      value: 0.9916757941
 ---
 | Feature | Description |
 | --- | --- |
 | **Name** | `la_core_web_sm` |
-| **Version** | `3.7.6` |
-| **spaCy** | `>=3.7.4,<3.8.0` |
-| **Default Pipeline** | `normer`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `parser`, `lookup_lemmatizer`, `ner` |
 | **Components** | `senter`, `normer`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `parser`, `lookup_lemmatizer`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
-| **Sources** | UD_Latin-Perseus<br>UD_Latin-PROIEL<br>UD_Latin-ITTB<br>UD_Latin-LLCT<br>UD_Latin-UDante |
 | **License** | `MIT` |
 | **Author** | [Patrick J. Burns; with Nora Bernhardt [ner], Tim Geelhaar [tagger, morphologizer, parser, ner], Vincent Koch [ner]](https://diyclassics.github.io/) |
@@ -102,21 +102,22 @@ model-index:
 | Type | Score |
 | --- | --- |
-| `ENTS_F` | 88.16 |
-| `ENTS_P` | 88.96 |
-| `ENTS_R` | 87.37 |
-| `TOK2VEC_LOSS` | 11852473.35 |
-| `NER_LOSS` | 4380.08 |
-| `SENTS_F` | 99.17 |
-| `SENTS_P` | 99.08 |
-| `SENTS_R` | 99.25 |
-| `TAG_ACC` | 93.53 |
-| `POS_ACC` | 96.75 |
-| `MORPH_ACC` | 91.37 |
-| `LEMMA_ACC` | 94.76 |
-| `DEP_UAS` | 82.96 |
-| `DEP_LAS` | 77.37 |
-| `TAGGER_LOSS` | 813555.24 |
-| `MORPHOLOGIZER_LOSS` | 1875249.34 |
-| `TRAINABLE_LEMMATIZER_LOSS` | 735454.70 |
-| `PARSER_LOSS` | 6143128.62 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.9035268069
     - name: NER Recall
       type: recall
+      value: 0.9286410923
     - name: NER F Score
       type: f_score
+      value: 0.9159118236
   - task:
       name: TAG
       type: token-classification
     metrics:
     - name: TAG (XPOS) Accuracy
       type: accuracy
+      value: 0.9360567397
   - task:
       name: POS
       type: token-classification
     metrics:
     - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9679485974
   - task:
       name: MORPH
       type: token-classification
     metrics:
     - name: Morph (UFeats) Accuracy
       type: accuracy
+      value: 0.9131892766
   - task:
       name: LEMMA
       type: token-classification
     metrics:
     - name: Lemma Accuracy
       type: accuracy
+      value: 0.9478462525
   - task:
       name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Unlabeled Attachment Score (UAS)
       type: f_score
+      value: 0.8268572364
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
     - name: Labeled Attachment Score (LAS)
       type: f_score
+      value: 0.7728327237
   - task:
       name: SENTS
       type: token-classification
     metrics:
     - name: Sentences F-Score
       type: f_score
+      value: 0.9949627683
 ---
 | Feature | Description |
 | --- | --- |
 | **Name** | `la_core_web_sm` |
+| **Version** | `3.7.7` |
+| **spaCy** | `>=3.7.5,<3.8.0` |
+| **Default Pipeline** | `senter`, `normer`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `parser`, `lookup_lemmatizer`, `ner` |
 | **Components** | `senter`, `normer`, `tok2vec`, `tagger`, `morphologizer`, `trainable_lemmatizer`, `parser`, `lookup_lemmatizer`, `ner` |
 | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **Sources** | UD_Latin-Perseus (via Gamba/Zeman 2023)<br>UD_Latin-PROIEL (via Gamba/Zeman 2023)<br>UD_Latin-ITTB (via Gamba/Zeman 2023)<br>UD_Latin-LLCT (via Gamba/Zeman 2023<br>UD_Latin-UDante (via Gamba/Zeman 2023)<br>CIRCSE/LASLA: LASLA Corpus |
 | **License** | `MIT` |
 | **Author** | [Patrick J. Burns; with Nora Bernhardt [ner], Tim Geelhaar [tagger, morphologizer, parser, ner], Vincent Koch [ner]](https://diyclassics.github.io/) |
 | Type | Score |
 | --- | --- |
+| `TAG_ACC` | 93.50 |
+| `ENTS_F` | 88.04 |
+| `ENTS_P` | 86.93 |
+| `ENTS_R` | 89.17 |
+| `TOK2VEC_LOSS` | 11573015.06 |
+| `NER_LOSS` | 3068.28 |
+| `SENTS_F` | 99.56 |
+| `SENTS_P` | 99.43 |
+| `SENTS_R` | 99.69 |
+| `POS_ACC` | 96.80 |
+| `MORPH_ACC` | 91.34 |
+| `LEMMA_ACC` | 94.78 |
+| `DEP_UAS` | 82.97 |
+| `DEP_LAS` | 77.48 |
+| `SENTER_LOSS` | 2691.47 |
+| `TAGGER_LOSS` | 857353.80 |
+| `MORPHOLOGIZER_LOSS` | 1977789.84 |
+| `TRAINABLE_LEMMATIZER_LOSS` | 793680.49 |
+| `PARSER_LOSS` | 6175564.17 |

config.cfg CHANGED Viewed

@@ -12,7 +12,7 @@ seed = 0
 lang = "la"
 pipeline = ["senter","normer","tok2vec","tagger","morphologizer","trainable_lemmatizer","parser","lookup_lemmatizer","ner"]
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
-disabled = ["senter"]
 before_creation = null
 after_creation = null
 after_pipeline_creation = null
@@ -37,21 +37,9 @@ nO = null
 normalize = false
 [components.morphologizer.model.tok2vec]
-@architectures = "spacy.Tok2Vec.v2"
-[components.morphologizer.model.tok2vec.embed]
-@architectures = "spacy.MultiHashEmbed.v2"
-width = 96
-attrs = ["LOWER","PREFIX","SUFFIX","SHAPE"]
-rows = [5000,2500,2500,2500]
-include_static_vectors = false
-[components.morphologizer.model.tok2vec.encode]
-@architectures = "spacy.MaxoutWindowEncoder.v2"
 width = 96
-depth = 4
-window_size = 1
-maxout_pieces = 3
 [components.ner]
 factory = "ner"
@@ -75,8 +63,8 @@ nO = null
 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [5000,1000,2500,2500]
 include_static_vectors = false
 [components.ner.model.tok2vec.encode]
@@ -129,25 +117,19 @@ overwrite = false
 scorer = {"@scorers":"spacy.senter_scorer.v1"}
 [components.senter.model]
-@architectures = "spacy.Tagger.v1"
 nO = null
 [components.senter.model.tok2vec]
-@architectures = "spacy.Tok2Vec.v2"
-[components.senter.model.tok2vec.embed]
-@architectures = "spacy.MultiHashEmbed.v2"
-width = 16
-attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
-rows = [1000,500,500,500]
-include_static_vectors = false
-[components.senter.model.tok2vec.encode]
-@architectures = "spacy.MaxoutWindowEncoder.v2"
-width = 16
-depth = 2
 window_size = 1
 maxout_pieces = 2
 [components.tagger]
 factory = "tagger"

 lang = "la"
 pipeline = ["senter","normer","tok2vec","tagger","morphologizer","trainable_lemmatizer","parser","lookup_lemmatizer","ner"]
 tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+disabled = []
 before_creation = null
 after_creation = null
 after_pipeline_creation = null
 normalize = false
 [components.morphologizer.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
 width = 96
+upstream = "tok2vec"
 [components.ner]
 factory = "ner"
 [components.ner.model.tok2vec.embed]
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE","POS"]
+rows = [5000,1000,2500,2500,1000]
 include_static_vectors = false
 [components.ner.model.tok2vec.encode]
 scorer = {"@scorers":"spacy.senter_scorer.v1"}
 [components.senter.model]
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 [components.senter.model.tok2vec]
+@architectures = "spacy.HashEmbedCNN.v2"
+pretrained_vectors = null
+width = 12
+depth = 1
+embed_size = 2000
 window_size = 1
 maxout_pieces = 2
+subword_features = true
 [components.tagger]
 factory = "tagger"

functions.py CHANGED Viewed

@@ -200,11 +200,8 @@ import string
 blank_nlp = spacy.blank("la")
 lookups = Lookups()
-try:
-    lookups_data = load_lookups(lang=blank_nlp.vocab.lang, tables=["lemma_lookup"])
-except:
-    lookups_data = lookups.from_disk("scripts/lemmatizer_lookups")
 LOOKUPS = lookups_data.get_table("lemma_lookup")
 predicted_lemma_getter = lambda token: token.lemma_

 blank_nlp = spacy.blank("la")
 lookups = Lookups()
+lookups_data = load_lookups(lang=blank_nlp.vocab.lang, tables=["lemma_lookup"])
 LOOKUPS = lookups_data.get_table("lemma_lookup")
 predicted_lemma_getter = lambda token: token.lemma_

la_core_web_sm-any-py3-none-any.whl CHANGED Viewed

@@ -1,3 +1,3 @@
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meta.json CHANGED Viewed

@@ -1,14 +1,14 @@
 {
   "lang":"la",
   "name":"core_web_sm",
-  "version":"3.7.6",
   "description":"",
   "author":"Patrick J. Burns; with Nora Bernhardt [ner], Tim Geelhaar [tagger, morphologizer, parser, ner], Vincent Koch [ner]",
   "email":"pjb311@nyu.edu",
   "url":"https://diyclassics.github.io/",
   "license":"MIT",
-  "spacy_version":">=3.7.4,<3.8.0",
-  "spacy_git_version":"bff8725f4",
   "vectors":{
     "width":0,
     "vectors":0,
@@ -811,6 +811,7 @@
     ]
   },
   "pipeline":[
     "normer",
     "tok2vec",
     "tagger",
@@ -832,302 +833,297 @@
     "ner"
   ],
   "disabled":[
-    "senter"
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   "performance":{
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@@ -1149,20 +1145,25 @@
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@@ -1170,9 +1171,9 @@
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@@ -1210,10 +1211,11 @@
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-    "tagger_loss":8135.5524425507,
-    "morphologizer_loss":18752.4934272766,
-    "trainable_lemmatizer_loss":7354.5470409393,
-    "parser_loss":61431.2862028896
   },
   "sources":[
     "UD_Latin-Perseus (via Gamba/Zeman 2023)",
@@ -1221,7 +1223,8 @@
     "UD_Latin-ITTB (via Gamba/Zeman 2023)",
     "UD_Latin-LLCT (via Gamba/Zeman 2023",
     "UD_Latin-UDante (via Gamba/Zeman 2023)",
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 {
   "lang":"la",
   "name":"core_web_sm",
+  "version":"3.7.7",
   "description":"",
   "author":"Patrick J. Burns; with Nora Bernhardt [ner], Tim Geelhaar [tagger, morphologizer, parser, ner], Vincent Koch [ner]",
   "email":"pjb311@nyu.edu",
   "url":"https://diyclassics.github.io/",
   "license":"MIT",
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+  "spacy_git_version":"a6d0fc360",
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     "vectors":0,
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     "tagger",
     "ner"
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     "UD_Latin-ITTB (via Gamba/Zeman 2023)",
     "UD_Latin-LLCT (via Gamba/Zeman 2023",
     "UD_Latin-UDante (via Gamba/Zeman 2023)",
+    "CIRCSE/LASLA: LASLA Corpus",
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   "requirements":[
     "spacy_lookups_data @ git+https://github.com/diyclassics/spacy-lookups-data.git#egg=spacy-lookups-data"

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@@ -719,295 +717,287 @@
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@@ -1015,7 +1005,6 @@
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     1939,
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     1941,
     1943,
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@@ -1023,105 +1012,104 @@
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@@ -1134,301 +1122,287 @@
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@@ -1436,707 +1410,699 @@
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@@ -2144,454 +2110,496 @@
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@@ -2599,5023 +2607,646 @@
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