Update spaCy pipeline

.gitattributes

@@ -32,3 +32,7 @@ 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
+de_test_pipeline-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
+ner/model filter=lfs diff=lfs merge=lfs -text
+tok2vec/model filter=lfs diff=lfs merge=lfs -text
+spancat/model filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,98 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- de
+license: mit
+model-index:
+- name: de_test_pipeline
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 1.0
+    - name: NER Recall
+      type: recall
+      value: 1.0
+    - name: NER F Score
+      type: f_score
+      value: 1.0
+  - task:
+      name: TAG
+      type: token-classification
+    metrics:
+    - name: TAG (XPOS) Accuracy
+      type: accuracy
+      value: 0.9917602996
+  - task:
+      name: UNLABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Unlabeled Attachment Score (UAS)
+      type: f_score
+      value: 0.9901873327
+  - task:
+      name: LABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Labeled Attachment Score (LAS)
+      type: f_score
+      value: 0.9901873327
+  - task:
+      name: SENTS
+      type: token-classification
+    metrics:
+    - name: Sentences F-Score
+      type: f_score
+      value: 1.0
+---
+A test pipeline for ModelManager testing purposes
+
+| Feature | Description |
+| --- | --- |
+| **Name** | `de_test_pipeline` |
+| **Version** | `0.1.0` |
+| **spaCy** | `>=3.5.0,<3.6.0` |
+| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `ner`, `spancat` |
+| **Components** | `tok2vec`, `tagger`, `parser`, `ner`, `spancat` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **Sources** | n/a |
+| **License** | `MIT` |
+| **Author** | [Inga Ulusoy]() |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (105 labels for 4 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`tagger`** | `$(`, `$,`, `$.`, `ADJA`, `ADJD`, `ADV`, `APPO`, `APPR`, `APPRART`, `APZR`, `ART`, `CARD`, `FM`, `ITJ`, `KOKOM`, `KON`, `KOUI`, `KOUS`, `NE`, `NN`, `NNE`, `PDAT`, `PDS`, `PIAT`, `PIS`, `PPER`, `PPOSAT`, `PPOSS`, `PRELAT`, `PRELS`, `PRF`, `PROAV`, `PTKA`, `PTKANT`, `PTKNEG`, `PTKVZ`, `PTKZU`, `PWAT`, `PWAV`, `PWS`, `TRUNC`, `VAFIN`, `VAIMP`, `VAINF`, `VAPP`, `VMFIN`, `VMINF`, `VMPP`, `VVFIN`, `VVIMP`, `VVINF`, `VVIZU`, `VVPP`, `XY`, `_SP` |
+| **`parser`** | `ROOT`, `ac`, `adc`, `ag`, `ams`, `app`, `avc`, `cc`, `cd`, `cj`, `cm`, `cp`, `cvc`, `da`, `dep`, `dm`, `ep`, `ju`, `mnr`, `mo`, `ng`, `nk`, `nmc`, `oa`, `oc`, `og`, `op`, `par`, `pd`, `pg`, `ph`, `pm`, `pnc`, `punct`, `rc`, `re`, `rs`, `sb`, `sbp`, `svp`, `uc`, `vo` |
+| **`ner`** | `LOC`, `MISC`, `ORG`, `PER` |
+| **`spancat`** | `Moralisierung explizit`, `Keine Moralisierung`, `Moralisierung`, `Moralisierung interpretativ` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `TAG_ACC` | 99.18 |
+| `DEP_UAS` | 99.02 |
+| `DEP_LAS` | 99.02 |
+| `SENTS_P` | 100.00 |
+| `SENTS_R` | 100.00 |
+| `SENTS_F` | 100.00 |
+| `ENTS_F` | 100.00 |
+| `ENTS_P` | 100.00 |
+| `ENTS_R` | 100.00 |
+| `SPANS_SC_F` | 0.00 |
+| `SPANS_SC_P` | 0.00 |
+| `SPANS_SC_R` | 0.00 |
+| `SPANCAT_LOSS` | 210521.12 |

config.cfg

@@ -0,0 +1,244 @@
+[paths]
+train = "/tmp/tmpszr2o3t5/train.spacy"
+dev = "/tmp/tmpszr2o3t5/dev.spacy"
+vectors = null
+init_tok2vec = null
+
+[system]
+gpu_allocator = null
+seed = 0
+
+[nlp]
+lang = "de"
+pipeline = ["tok2vec","tagger","parser","ner","spancat"]
+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
+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.Tok2Vec.v2"
+
+[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]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+depth = 4
+window_size = 1
+maxout_pieces = 3
+
+[components.parser]
+factory = "parser"
+learn_tokens = false
+min_action_freq = 30
+moves = null
+scorer = {"@scorers":"spacy.parser_scorer.v1"}
+update_with_oracle_cut_size = 100
+
+[components.parser.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "parser"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = true
+nO = null
+
+[components.parser.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[components.spancat]
+factory = "spancat"
+max_positive = null
+scorer = {"@scorers":"spacy.spancat_scorer.v1"}
+spans_key = "task1"
+threshold = 0.5
+
+[components.spancat.model]
+@architectures = "spacy.SpanCategorizer.v1"
+
+[components.spancat.model.reducer]
+@layers = "spacy.mean_max_reducer.v1"
+hidden_size = 128
+
+[components.spancat.model.scorer]
+@layers = "spacy.LinearLogistic.v1"
+nO = null
+nI = null
+
+[components.spancat.model.tok2vec]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.spancat.model.tok2vec.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = 96
+rows = [5000,2000,1000,1000]
+attrs = ["ORTH","PREFIX","SUFFIX","SHAPE"]
+include_static_vectors = false
+
+[components.spancat.model.tok2vec.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+window_size = 1
+maxout_pieces = 3
+depth = 4
+
+[components.spancat.suggester]
+@misc = "spacy.ngram_suggester.v1"
+sizes = [1,2,3]
+
+[components.tagger]
+factory = "tagger"
+neg_prefix = "!"
+overwrite = false
+scorer = {"@scorers":"spacy.tagger_scorer.v1"}
+
+[components.tagger.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+
+[components.tagger.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = 96
+upstream = "tok2vec"
+
+[components.tok2vec]
+factory = "tok2vec"
+
+[components.tok2vec.model]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.tok2vec.model.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = 96
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
+rows = [5000,1000,2500,2500,50,50]
+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 = 0
+gold_preproc = false
+limit = 0
+augmenter = null
+
+[training]
+frozen_components = ["tok2vec","tagger","parser","ner"]
+annotating_components = ["tok2vec","tagger","parser","ner"]
+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 = 20
+max_steps = 20000
+eval_frequency = 200
+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]
+tag_acc = 0.25
+dep_uas = 0.12
+dep_las = 0.12
+dep_las_per_type = null
+sents_p = null
+sents_r = null
+sents_f = 0.0
+ents_f = 0.25
+ents_p = 0.0
+ents_r = 0.0
+ents_per_type = null
+spans_sc_f = 0.25
+spans_sc_p = 0.0
+spans_sc_r = 0.0
+
+[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]

de_test_pipeline-any-py3-none-any.whl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:39d326210b6662dcec25b7c100cb42ab539ebfbc98ba9d48c744f3741b91447d
+size 19019121

meta.json

@@ -0,0 +1,345 @@
+{
+  "lang":"de",
+  "name":"test_pipeline",
+  "version":"0.1.0",
+  "description":"A test pipeline for ModelManager testing purposes",
+  "author":"Inga Ulusoy",
+  "email":"inga.ulusoy@uni-heidelberg.de",
+  "url":"",
+  "license":"MIT",
+  "spacy_version":">=3.5.0,<3.6.0",
+  "spacy_git_version":"Unknown",
+  "vectors":{
+    "width":0,
+    "vectors":0,
+    "keys":0,
+    "name":null
+  },
+  "labels":{
+    "tok2vec":[
+
+    ],
+    "tagger":[
+      "$(",
+      "$,",
+      "$.",
+      "ADJA",
+      "ADJD",
+      "ADV",
+      "APPO",
+      "APPR",
+      "APPRART",
+      "APZR",
+      "ART",
+      "CARD",
+      "FM",
+      "ITJ",
+      "KOKOM",
+      "KON",
+      "KOUI",
+      "KOUS",
+      "NE",
+      "NN",
+      "NNE",
+      "PDAT",
+      "PDS",
+      "PIAT",
+      "PIS",
+      "PPER",
+      "PPOSAT",
+      "PPOSS",
+      "PRELAT",
+      "PRELS",
+      "PRF",
+      "PROAV",
+      "PTKA",
+      "PTKANT",
+      "PTKNEG",
+      "PTKVZ",
+      "PTKZU",
+      "PWAT",
+      "PWAV",
+      "PWS",
+      "TRUNC",
+      "VAFIN",
+      "VAIMP",
+      "VAINF",
+      "VAPP",
+      "VMFIN",
+      "VMINF",
+      "VMPP",
+      "VVFIN",
+      "VVIMP",
+      "VVINF",
+      "VVIZU",
+      "VVPP",
+      "XY",
+      "_SP"
+    ],
+    "parser":[
+      "ROOT",
+      "ac",
+      "adc",
+      "ag",
+      "ams",
+      "app",
+      "avc",
+      "cc",
+      "cd",
+      "cj",
+      "cm",
+      "cp",
+      "cvc",
+      "da",
+      "dep",
+      "dm",
+      "ep",
+      "ju",
+      "mnr",
+      "mo",
+      "ng",
+      "nk",
+      "nmc",
+      "oa",
+      "oc",
+      "og",
+      "op",
+      "par",
+      "pd",
+      "pg",
+      "ph",
+      "pm",
+      "pnc",
+      "punct",
+      "rc",
+      "re",
+      "rs",
+      "sb",
+      "sbp",
+      "svp",
+      "uc",
+      "vo"
+    ],
+    "ner":[
+      "LOC",
+      "MISC",
+      "ORG",
+      "PER"
+    ],
+    "spancat":[
+      "Moralisierung explizit",
+      "Keine Moralisierung",
+      "Moralisierung",
+      "Moralisierung interpretativ"
+    ]
+  },
+  "pipeline":[
+    "tok2vec",
+    "tagger",
+    "parser",
+    "ner",
+    "spancat"
+  ],
+  "components":[
+    "tok2vec",
+    "tagger",
+    "parser",
+    "ner",
+    "spancat"
+  ],
+  "disabled":[
+
+  ],
+  "performance":{
+    "tag_acc":0.9917602996,
+    "dep_uas":0.9901873327,
+    "dep_las":0.9901873327,
+    "dep_las_per_type":{
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+    "spans_sc_r":0.0,
+    "spancat_loss":2105.2111816406
+  },
+  "requirements":[
+
+  ]
+}

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:ed5bd5d863ea3588431fce593428930529bc3b2e880d896a778913e4b230405d
+size 6140040

ner/moves

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+��moves��{"0":{},"1":{"LOC":161719,"PER":116712,"ORG":76676,"MISC":74723},"2":{"LOC":161719,"PER":116712,"ORG":76676,"MISC":74723},"3":{"LOC":161719,"PER":116712,"ORG":76676,"MISC":74723},"4":{"LOC":161719,"PER":116712,"ORG":76676,"MISC":74723,"":1},"5":{"":1}}�cfg��neg_key�

parser/cfg

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+{
+  "moves":null,
+  "update_with_oracle_cut_size":100,
+  "multitasks":[
+
+  ],
+  "min_action_freq":30,
+  "learn_tokens":false,
+  "beam_width":1,
+  "beam_density":0.0,
+  "beam_update_prob":0.0,
+  "incorrect_spans_key":null
+}

parser/moves

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spancat/cfg

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+{
+  "labels":[
+    "Moralisierung explizit",
+    "Keine Moralisierung",
+    "Moralisierung",
+    "Moralisierung interpretativ"
+  ],
+  "spans_key":"task1",
+  "threshold":0.5,
+  "max_positive":null
+}

spancat/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:243465cb97d5349b57007b1f5497df546532a3af194d630c07509695ff6f3b61
+size 5838234

tagger/cfg

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+{
+  "labels":[
+    "$(",
+    "$,",
+    "$.",
+    "ADJA",
+    "ADJD",
+    "ADV",
+    "APPO",
+    "APPR",
+    "APPRART",
+    "APZR",
+    "ART",
+    "CARD",
+    "FM",
+    "ITJ",
+    "KOKOM",
+    "KON",
+    "KOUI",
+    "KOUS",
+    "NE",
+    "NN",
+    "NNE",
+    "PDAT",
+    "PDS",
+    "PIAT",
+    "PIS",
+    "PPER",
+    "PPOSAT",
+    "PPOSS",
+    "PRELAT",
+    "PRELS",
+    "PRF",
+    "PROAV",
+    "PTKA",
+    "PTKANT",
+    "PTKNEG",
+    "PTKVZ",
+    "PTKZU",
+    "PWAT",
+    "PWAV",
+    "PWS",
+    "TRUNC",
+    "VAFIN",
+    "VAIMP",
+    "VAINF",
+    "VAPP",
+    "VMFIN",
+    "VMINF",
+    "VMPP",
+    "VVFIN",
+    "VVIMP",
+    "VVINF",
+    "VVIZU",
+    "VVPP",
+    "XY",
+    "_SP"
+  ],
+  "neg_prefix":"!",
+  "overwrite":false
+}

tok2vec/cfg

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+{
+
+}

tok2vec/model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f57c0f4fb800793c9d49c8a2e62a4221239a9802808a58756a6a5739e5b7eae4
+size 6269370

tokenizer

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