Update spaCy pipeline

.gitattributes

@@ -25,3 +25,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zstandard 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 +1,58 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- de
+model-index:
+- name: de_GERNERMEDpp_GermanBERT
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 0.9088501091
+    - name: NER Recall
+      type: recall
+      value: 0.9085669782
+    - name: NER F Score
+      type: f_score
+      value: 0.9087085216
+---
+GottBERT-based model of the GERNERMED++ German NER model for medical entities.
+
+| Feature | Description |
+| --- | --- |
+| **Name** | `de_GERNERMEDpp_GermanBERT` |
+| **Version** | `1.0.0` |
+| **spaCy** | `>=3.2.3,<3.3.0` |
+| **Default Pipeline** | `transformer`, `ner` |
+| **Components** | `transformer`, `ner` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **Sources** | n/a |
+| **License** | n/a |
+| **Author** | [Johann Frei](https://github.com/frankkramer-lab/GERNERMED-pp) |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (6 labels for 1 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`ner`** | `Dosage`, `Drug`, `Duration`, `Form`, `Frequency`, `Strength` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `ENTS_F` | 90.87 |
+| `ENTS_P` | 90.89 |
+| `ENTS_R` | 90.86 |
+| `TRANSFORMER_LOSS` | 193600.80 |
+| `NER_LOSS` | 255416.71 |

config.cfg

@@ -0,0 +1,149 @@
+[paths]
+train = "/data_output/spacy/corpus.train.spacy"
+dev = "/data_output/spacy/corpus.val.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = "pytorch"
+seed = 0
+
+[nlp]
+lang = "de"
+pipeline = ["transformer","ner"]
+batch_size = 128
+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
+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 = false
+nO = null
+
+[components.ner.model.tok2vec]
+@architectures = "spacy-transformers.TransformerListener.v1"
+grad_factor = 1.0
+pooling = {"@layers":"reduce_mean.v1"}
+upstream = "*"
+
+[components.transformer]
+factory = "transformer"
+max_batch_items = 4096
+set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
+
+[components.transformer.model]
+@architectures = "spacy-transformers.TransformerModel.v3"
+name = "bert-base-german-cased"
+mixed_precision = false
+
+[components.transformer.model.get_spans]
+@span_getters = "spacy-transformers.strided_spans.v1"
+window = 128
+stride = 96
+
+[components.transformer.model.grad_scaler_config]
+
+[components.transformer.model.tokenizer_config]
+use_fast = true
+
+[components.transformer.model.transformer_config]
+
+[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]
+accumulate_gradient = 3
+dev_corpus = "corpora.dev"
+train_corpus = "corpora.train"
+seed = ${system.seed}
+gpu_allocator = ${system.gpu_allocator}
+dropout = 0.1
+patience = 1600
+max_epochs = 0
+max_steps = 20000
+eval_frequency = 200
+frozen_components = []
+annotating_components = []
+before_to_disk = null
+
+[training.batcher]
+@batchers = "spacy.batch_by_padded.v1"
+discard_oversize = true
+size = 2000
+buffer = 256
+get_length = null
+
+[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
+
+[training.optimizer.learn_rate]
+@schedules = "warmup_linear.v1"
+warmup_steps = 250
+total_steps = 20000
+initial_rate = 0.00005
+
+[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
+before_init = null
+after_init = null
+
+[initialize.components]
+
+[initialize.lookups]
+@misc = "spacy.LookupsDataLoader.v1"
+lang = ${nlp.lang}
+tables = ["lexeme_norm"]
+
+[initialize.tokenizer]

de_GERNERMEDpp_GermanBERT-any-py3-none-any.whl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c1c968fb8c53d69b3462e55aee18b31b1cfc51e05f534465500b5c12e783799a
+size 406042094

meta.json

@@ -0,0 +1,84 @@
+{
+  "lang":"de",
+  "name":"GERNERMEDpp_GermanBERT",
+  "version":"1.0.0",
+  "description":"GottBERT-based model of the GERNERMED++ German NER model for medical entities.",
+  "author":"Johann Frei",
+  "email":"[email protected]",
+  "url":"https://github.com/frankkramer-lab/GERNERMED-pp",
+  "license":"",
+  "spacy_version":">=3.2.3,<3.3.0",
+  "spacy_git_version":"99425de36",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
+  },
+  "labels":{
+    "transformer":[
+
+    ],
+    "ner":[
+      "Dosage",
+      "Drug",
+      "Duration",
+      "Form",
+      "Frequency",
+      "Strength"
+    ]
+  },
+  "pipeline":[
+    "transformer",
+    "ner"
+  ],
+  "components":[
+    "transformer",
+    "ner"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "ents_f":0.9087085216,
+    "ents_p":0.9088501091,
+    "ents_r":0.9085669782,
+    "ents_per_type":{
+      "Drug":{
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+        "r":0.9450381679,
+        "f":0.9459407832
+      },
+      "Strength":{
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+        "r":0.9475164011,
+        "f":0.9145183175
+      },
+      "Form":{
+        "p":0.9243614931,
+        "r":0.9289239882,
+        "f":0.9266371246
+      },
+      "Dosage":{
+        "p":0.9090909091,
+        "r":0.8995502249,
+        "f":0.9042954032
+      },
+      "Frequency":{
+        "p":0.8346727899,
+        "r":0.7709437964,
+        "f":0.8015435502
+      },
+      "Duration":{
+        "p":0.7090909091,
+        "r":0.7090909091,
+        "f":0.7090909091
+      }
+    },
+    "transformer_loss":1936.0080456654,
+    "ner_loss":2554.1670563572
+  },
+  "requirements":[
+    "spacy-transformers>=1.1.5,<1.2.0"
+  ]
+}

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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+oid sha256:1800c0d86edde3b1a25ba029d4c7f0df7dfb6fcd5fb9805c03db113bdf7a3f09
+size 238506

ner/moves

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tokenizer

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