Update spaCy pipeline

.gitattributes

@@ -15,3 +15,8 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.whl filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*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

README.md

@@ -0,0 +1,59 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- de
+license: cc-by
+model-index:
+- name: de_MRP_NER
+  results:
+  - tasks:
+      name: NER
+      type: token-classification
+      metrics:
+      - name: Precision
+        type: precision
+        value: 0.905255631
+      - name: Recall
+        type: recall
+        value: 0.8568527919
+      - name: F Score
+        type: f_score
+        value: 0.8803894298
+---
+NER Model for 'Ministerratsprotokolle'
+
+| Feature | Description |
+| --- | --- |
+| **Name** | `de_MRP_NER` |
+| **Version** | `0.0.0` |
+| **spaCy** | `>=3.1.0,<3.2.0` |
+| **Default Pipeline** | `tok2vec`, `ner` |
+| **Components** | `tok2vec`, `ner` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **Sources** | n/a |
+| **License** | `cc-by` |
+| **Author** | [Peter Andorfer]() |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (4 labels for 1 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`ner`** | `GPE`, `LOC`, `ORG`, `PER` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `ENTS_F` | 88.04 |
+| `ENTS_P` | 90.53 |
+| `ENTS_R` | 85.69 |
+| `TOK2VEC_LOSS` | 40077.56 |
+| `NER_LOSS` | 77727.57 |

config.cfg

@@ -0,0 +1,142 @@
+[paths]
+train = "./train.spacy"
+dev = "./dev.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = null
+seed = 0
+
+[nlp]
+lang = "de"
+pipeline = ["tok2vec","ner"]
+batch_size = 1000
+disabled = []
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+
+[components]
+
+[components.ner]
+factory = "ner"
+incorrect_spans_key = null
+moves = null
+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.v1"
+width = ${components.tok2vec.model.encode.width}
+attrs = ["ORTH","SHAPE"]
+rows = [5000,2500]
+include_static_vectors = false
+
+[components.tok2vec.model.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+depth = 4
+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 = 2000
+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 = []
+before_to_disk = null
+annotating_components = []
+
+[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 = null
+init_tok2vec = ${paths.init_tok2vec}
+vocab_data = null
+lookups = null
+before_init = null
+after_init = null
+
+[initialize.components]
+
+[initialize.tokenizer]

de_MRP_NER-any-py3-none-any.whl

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+size 4408159

meta.json

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+{
+  "lang":"de",
+  "name":"MRP_NER",
+  "version":"0.0.0",
+  "description":"NER Model for 'Ministerratsprotokolle'",
+  "author":"Peter Andorfer",
+  "email":"p.andorfer@gmail.com",
+  "url":"",
+  "license":"cc-by",
+  "spacy_version":">=3.1.0,<3.2.0",
+  "spacy_git_version":"530b5d72f",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
+  },
+  "labels":{
+    "tok2vec":[
+
+    ],
+    "ner":[
+      "GPE",
+      "LOC",
+      "ORG",
+      "PER"
+    ]
+  },
+  "pipeline":[
+    "tok2vec",
+    "ner"
+  ],
+  "components":[
+    "tok2vec",
+    "ner"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "ents_f":0.8803894298,
+    "ents_p":0.905255631,
+    "ents_r":0.8568527919,
+    "ents_per_type":{
+      "PER":{
+        "p":0.9378342246,
+        "r":0.9022508039,
+        "f":0.9196984595
+      },
+      "ORG":{
+        "p":0.874301676,
+        "r":0.7864321608,
+        "f":0.828042328
+      },
+      "GPE":{
+        "p":0.8682745826,
+        "r":0.8830188679,
+        "f":0.8755846586
+      },
+      "LOC":{
+        "p":0.7608695652,
+        "r":0.472972973,
+        "f":0.5833333333
+      }
+    },
+    "tok2vec_loss":400.7755703424,
+    "ner_loss":777.275670269
+  }
+}

ner/cfg

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+{
+  "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/model

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ner/moves

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tok2vec/cfg

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+{
+
+}

tok2vec/model

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tokenizer

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