Update spaCy pipeline

.gitattributes

@@ -33,3 +33,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+fr_arches_ner-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
+tok2vec/model filter=lfs diff=lfs merge=lfs -text
+vocab/key2row filter=lfs diff=lfs merge=lfs -text
+vocab/strings.json filter=lfs diff=lfs merge=lfs -text
+vocab/vectors filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,56 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- fr
+model-index:
+- name: fr_arches_ner
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 0.6778376222
+    - name: NER Recall
+      type: recall
+      value: 0.7156697557
+    - name: NER F Score
+      type: f_score
+      value: 0.6962401393
+---
+| Feature | Description |
+| --- | --- |
+| **Name** | `fr_arches_ner` |
+| **Version** | `0.0.0` |
+| **spaCy** | `>=3.6.1,<3.7.0` |
+| **Default Pipeline** | `tok2vec`, `ner`, `entity_punctuation_removal` |
+| **Components** | `tok2vec`, `ner`, `entity_punctuation_removal` |
+| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
+| **Sources** | n/a |
+| **License** | n/a |
+| **Author** | [n/a]() |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (15 labels for 1 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`ner`** | `CHRONOLOGIE`, `DECOR`, `EDIFICE`, `ESPECE`, `GPE`, `ID`, `LIEUDIT_SITE`, `LOC`, `MATERIAU`, `MOBILIER`, `ORG`, `PERSONNE`, `PEUPLE_CULTURE`, `STRUCTURE`, `TECHNIQUE_STYLE` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `ENTS_F` | 69.62 |
+| `ENTS_P` | 67.78 |
+| `ENTS_R` | 71.57 |
+| `TOK2VEC_LOSS` | 63436.09 |
+| `NER_LOSS` | 246059.83 |

config.cfg

@@ -0,0 +1,147 @@
+[paths]
+train = "train.spacy"
+dev = "dev.spacy"
+vectors = "fr_core_news_lg"
+init_tok2vec = null
+
+[system]
+gpu_allocator = null
+seed = 0
+
+[nlp]
+lang = "fr"
+pipeline = ["tok2vec","ner","entity_punctuation_removal"]
+batch_size = 1000
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+
+[components]
+
+[components.entity_punctuation_removal]
+factory = "entity_punctuation_removal"
+
+[components.ner]
+factory = "ner"
+incorrect_spans_key = null
+moves = null
+scorer = {"@scorers":"spacy.ner_scorer.v1"}
+update_with_oracle_cut_size = 100
+
+[components.ner.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "ner"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = true
+nO = null
+
+[components.ner.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = ${components.tok2vec.model.encode.width}
+upstream = "*"
+
+[components.tok2vec]
+factory = "tok2vec"
+
+[components.tok2vec.model]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.tok2vec.model.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = ${components.tok2vec.model.encode.width}
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,1000,2500,2500]
+include_static_vectors = true
+
+[components.tok2vec.model.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 256
+depth = 8
+window_size = 1
+maxout_pieces = 3
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+path = ${paths.dev}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths.train}
+max_length = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[training]
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+accumulate_gradient = 1
+patience = 1600
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+before_to_disk = null
+before_update = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_words.v1"
+discard_oversize = false
+tolerance = 0.2
+get_length = null
+
+[training.batcher.size]
+@schedules = "compounding.v1"
+start = 100
+stop = 1000
+compound = 1.001
+t = 0.0
+
+[training.logger]
+@loggers = "spacy.ConsoleLogger.v1"
+progress_bar = false
+
+[training.optimizer]
+@optimizers = "Adam.v1"
+beta1 = 0.9
+beta2 = 0.999
+L2_is_weight_decay = true
+L2 = 0.01
+grad_clip = 1.0
+use_averages = false
+eps = 0.00000001
+learn_rate = 0.001
+
+[training.score_weights]
+ents_f = 1.0
+ents_p = 0.0
+ents_r = 0.0
+ents_per_type = null
+
+[pretraining]
+
+[initialize]
+vectors = ${paths.vectors}
+init_tok2vec = ${paths.init_tok2vec}
+vocab_data = null
+lookups = null
+before_init = null
+after_init = null
+
+[initialize.components]
+
+[initialize.tokenizer]

entity_punctuation_removal.py

@@ -0,0 +1,34 @@
+import spacy
+from spacy.language import Language
+import regex
+
+
+@Language.component("entity_punctuation_removal")
+
+
+def entity_punctuation_removal(doc):
+    # On liste nos entités
+    ents = list(doc.ents)
+
+    i = 0
+    while i < len(ents):
+        current_ent = ents[i]
+
+        # On attrape l'entité si :
+        # - Elle consiste en un unique signe de ponctuation
+        # - Et que son tag IOB est B (début d'entité)
+        # - Et qu'elle n'est pas suivie par une entité de tag IOB I (suite d'entité) OU qu'elle n'est suivie par aucun token
+        # Si l'entité est attrapée, elle est supprimée du doc
+        if i + 1 < len(ents) and regex.match(r'^\p{P}$', current_ent.text) and current_ent.root.ent_iob_ == "B" :
+          ents.pop(i)
+        elif i == len(ents) - 1 and regex.match(r'^\p{P}$', current_ent.text) and current_ent.root.ent_iob_ == "B" :
+          ents.pop(i)
+        else:
+            i += 1
+
+    # On met à jour le doc avec les entités modifiées
+    doc.ents = tuple(ents)
+
+    return doc
+
+Language.component("entity_punctuation_removal", func=entity_punctuation_removal)

fr_arches_ner-any-py3-none-any.whl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7e42c101b766cc100c041e3e898d6565703687e9f2a20a14809f77aef3a11ca8
+size 587844207

meta.json

@@ -0,0 +1,140 @@
+{
+  "lang":"fr",
+  "name":"arches_ner",
+  "version":"0.0.0",
+  "description":"",
+  "author":"",
+  "email":"",
+  "url":"",
+  "license":"",
+  "spacy_version":">=3.6.1,<3.7.0",
+  "spacy_git_version":"458bc5f45",
+  "vectors":{
+    "width":300,
+    "vectors":500000,
+    "keys":500000,
+    "name":"fr_vectors"
+  },
+  "labels":{
+    "tok2vec":[
+
+    ],
+    "ner":[
+      "CHRONOLOGIE",
+      "DECOR",
+      "EDIFICE",
+      "ESPECE",
+      "GPE",
+      "ID",
+      "LIEUDIT_SITE",
+      "LOC",
+      "MATERIAU",
+      "MOBILIER",
+      "ORG",
+      "PERSONNE",
+      "PEUPLE_CULTURE",
+      "STRUCTURE",
+      "TECHNIQUE_STYLE"
+    ]
+  },
+  "pipeline":[
+    "tok2vec",
+    "ner",
+    "entity_punctuation_removal"
+  ],
+  "components":[
+    "tok2vec",
+    "ner",
+    "entity_punctuation_removal"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "ents_f":0.6962401393,
+    "ents_p":0.6778376222,
+    "ents_r":0.7156697557,
+    "ents_per_type":{
+      "STRUCTURE":{
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+        "r":0.6840336134,
+        "f":0.6002949853
+      },
+      "GPE":{
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+        "r":0.8609756098,
+        "f":0.7384937238
+      },
+      "ORG":{
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+        "r":0.5142857143,
+        "f":0.5901639344
+      },
+      "CHRONOLOGIE":{
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+        "r":0.7548638132,
+        "f":0.7232059646
+      },
+      "LOC":{
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+        "r":0.447761194,
+        "f":0.5529953917
+      },
+      "LIEUDIT_SITE":{
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+        "f":0.5150684932
+      },
+      "PEUPLE_CULTURE":{
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+        "f":0.3414634146
+      },
+      "MATERIAU":{
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+        "f":0.7160493827
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+      "TECHNIQUE_STYLE":{
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+        "f":0.6274509804
+      },
+      "MOBILIER":{
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+        "r":0.6992230855,
+        "f":0.724137931
+      },
+      "ID":{
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+        "r":0.8368159204,
+        "f":0.7885607126
+      },
+      "EDIFICE":{
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+        "r":0.4090909091,
+        "f":0.4090909091
+      },
+      "ESPECE":{
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+      "PERSONNE":{
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+      "DECOR":{
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+        "r":0.4423076923,
+        "f":0.3931623932
+      }
+    },
+    "tok2vec_loss":634.3608600097,
+    "ner_loss":2460.5982992177
+  },
+  "requirements":[
+
+  ]
+}

ner/cfg

@@ -0,0 +1,13 @@
+{
+  "moves":null,
+  "update_with_oracle_cut_size":100,
+  "multitasks":[
+
+  ],
+  "min_action_freq":1,
+  "learn_tokens":false,
+  "beam_width":1,
+  "beam_density":0.0,
+  "beam_update_prob":0.0,
+  "incorrect_spans_key":null
+}

ner/moves

@@ -0,0 +1 @@
+��moves��{"0":{},"1":{"MOBILIER":24870,"STRUCTURE":23884,"CHRONOLOGIE":21745,"ID":20721,"MATERIAU":11489,"GPE":4094,"TECHNIQUE_STYLE":3857,"LIEUDIT_SITE":3672,"PERSONNE":2710,"DECOR":2038,"LOC":1686,"ORG":1596,"ESPECE":1310,"EDIFICE":1216,"PEUPLE_CULTURE":757},"2":{"MOBILIER":24870,"STRUCTURE":23884,"CHRONOLOGIE":21745,"ID":20721,"MATERIAU":11489,"GPE":4094,"TECHNIQUE_STYLE":3857,"LIEUDIT_SITE":3672,"PERSONNE":2710,"DECOR":2038,"LOC":1686,"ORG":1596,"ESPECE":1310,"EDIFICE":1216,"PEUPLE_CULTURE":757},"3":{"MOBILIER":24870,"STRUCTURE":23884,"CHRONOLOGIE":21745,"ID":20721,"MATERIAU":11489,"GPE":4094,"TECHNIQUE_STYLE":3857,"LIEUDIT_SITE":3672,"PERSONNE":2710,"DECOR":2038,"LOC":1686,"ORG":1596,"ESPECE":1310,"EDIFICE":1216,"PEUPLE_CULTURE":757},"4":{"MOBILIER":24870,"STRUCTURE":23884,"CHRONOLOGIE":21745,"ID":20721,"MATERIAU":11489,"GPE":4094,"TECHNIQUE_STYLE":3857,"LIEUDIT_SITE":3672,"PERSONNE":2710,"DECOR":2038,"LOC":1686,"ORG":1596,"ESPECE":1310,"EDIFICE":1216,"PEUPLE_CULTURE":757,"":1},"5":{"":1}}�cfg��neg_key�

repartition.txt

@@ -0,0 +1,31 @@
+Corpus train:
+
+CIF_antique_C001185_BD.conll
+BFC_neo_F200449601_BD.conll
+BFC_proto_F101604_01.conll
+BFC_paleo_CB09001802_01.conll
+BFC_moderne_F114238.conll
+ARA_neo_F102890_01.conll
+ARA_paleo_F125492_01.conll
+ARA_contempo_F110732.conll
+ARA_med_F108171.conll
+BFC_med_F106159.conll
+ARA_antique_F120714.conll
+CIF_proto_F004820.conll
+CIF_neo_C102845.conll
+CIF_contempo_F115347.conll
+CIF_moderne_C106097.conll
+CIF_med_F148315_BD.conll
+
+
+Corpus dev:
+
+CIF_paleo_F110854.conll
+BFC_contempo_F123602.conll
+ARA_proto_F128240.conll
+
+
+Corpus test:
+
+BFC_antique_CB09003002.conll
+ARA_moderne_F114296.conll

resultats_post_ponct.json

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+  "token_r":1.0,
+  "token_f":1.0,
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+      "f":0.6991150442
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+    "PEUPLE_CULTURE":{
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+      "r":0.0,
+      "f":0.0
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+    "MOBILIER":{
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+      "r":0.7081967213,
+      "f":0.7164179104
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+    "DECOR":{
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+      "f":0.2666666667
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+    "ESPECE":{
+      "p":0.625,
+      "r":0.5555555556,
+      "f":0.5882352941
+    }
+  },
+  "speed":17108.4619219715
+}

tok2vec/cfg

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+{
+
+}

tok2vec/model

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+oid sha256:d9da4a07dd47786095e49afeabd31cbfff7f79a0019aeaa6f6f48dbc38a068c8
+size 34434008

vocab/key2row

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vocab/lookups.bin

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vocab/strings.json

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+size 10647622

vocab/vectors

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vocab/vectors.cfg

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+{
+  "mode":"default"
+}