Update spaCy pipeline
Browse files- .gitattributes +5 -0
- README.md +45 -0
- attribute_ruler/patterns +0 -0
- config.cfg +207 -0
- lemmatizer/lookups/lookups.bin +3 -0
- meta.json +351 -0
- ner/cfg +12 -0
- ner/model +3 -0
- ner/moves +1 -0
- parser/cfg +12 -0
- parser/model +3 -0
- parser/moves +1 -0
- sv_pipeline-any-py3-none-any.whl +3 -0
- tagger/cfg +21 -0
- tagger/model +3 -0
- tokenizer +4 -0
- transformer/cfg +3 -0
- transformer/model/config.json +25 -0
- transformer/model/pytorch_model.bin +3 -0
- transformer/model/special_tokens_map.json +1 -0
- transformer/model/tokenizer_config.json +1 -0
- transformer/model/vocab.txt +0 -0
- transformer_ner/cfg +3 -0
- transformer_ner/model/config.json +25 -0
- transformer_ner/model/pytorch_model.bin +3 -0
- transformer_ner/model/special_tokens_map.json +1 -0
- transformer_ner/model/tokenizer_config.json +1 -0
- transformer_ner/model/vocab.txt +0 -0
- vocab/key2row +1 -0
- vocab/lookups.bin +3 -0
- vocab/strings.json +3 -0
- vocab/vectors +3 -0
.gitattributes
CHANGED
@@ -25,3 +25,8 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.whl filter=lfs diff=lfs merge=lfs -text
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*.npz filter=lfs diff=lfs merge=lfs -text
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*strings.json filter=lfs diff=lfs merge=lfs -text
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vectors filter=lfs diff=lfs merge=lfs -text
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model filter=lfs diff=lfs merge=lfs -text
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README.md
ADDED
@@ -0,0 +1,45 @@
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---
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tags:
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- spacy
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- token-classification
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language:
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- sv
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license: mit
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model-index:
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- name: sv_pipeline
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results:
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS Accuracy
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type: accuracy
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value: 0.9818079056
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- task:
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name: SENTER
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type: token-classification
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metrics:
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- name: SENTER Precision
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type: precision
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value: 0.9212548015
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- name: SENTER Recall
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type: recall
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value: 0.9368489583
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- name: SENTER F Score
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type: f_score
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value: 0.9289864429
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Dependencies Accuracy
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type: accuracy
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value: 0.9198832946
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Dependencies Accuracy
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type: accuracy
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value: 0.9198832946
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---
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attribute_ruler/patterns
ADDED
Binary file (756 Bytes). View file
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config.cfg
ADDED
@@ -0,0 +1,207 @@
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[paths]
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train = "./data/sv_merged-upos-train.spacy"
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dev = "./data/sv_merged-upos-dev.spacy"
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vectors = null
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init_tok2vec = null
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[system]
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gpu_allocator = "pytorch"
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seed = 0
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[nlp]
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lang = "sv"
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pipeline = ["transformer","tagger","parser","transformer_ner","ner","attribute_ruler","lemmatizer"]
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batch_size = 128
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disabled = []
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before_creation = null
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after_creation = null
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after_pipeline_creation = null
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tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
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[components]
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[components.attribute_ruler]
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factory = "attribute_ruler"
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validate = false
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[components.lemmatizer]
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factory = "lemmatizer"
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mode = "lookup"
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model = null
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overwrite = false
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[components.ner]
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factory = "ner"
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moves = null
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update_with_oracle_cut_size = 100
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[components.ner.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "ner"
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extra_state_tokens = false
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hidden_width = 64
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maxout_pieces = 2
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use_upper = false
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nO = null
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[components.ner.model.tok2vec]
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@architectures = "spacy-transformers.TransformerListener.v1"
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grad_factor = 1.0
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pooling = {"@layers":"reduce_mean.v1"}
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upstream = "*"
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[components.parser]
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factory = "parser"
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learn_tokens = false
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min_action_freq = 30
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moves = null
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update_with_oracle_cut_size = 100
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[components.parser.model]
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@architectures = "spacy.TransitionBasedParser.v2"
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state_type = "parser"
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extra_state_tokens = false
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hidden_width = 128
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maxout_pieces = 3
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use_upper = false
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nO = null
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68 |
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[components.parser.model.tok2vec]
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@architectures = "spacy-transformers.TransformerListener.v1"
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grad_factor = 1.0
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pooling = {"@layers":"reduce_mean.v1"}
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upstream = "*"
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+
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[components.tagger]
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factory = "tagger"
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[components.tagger.model]
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@architectures = "spacy.Tagger.v1"
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nO = null
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+
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[components.tagger.model.tok2vec]
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@architectures = "spacy-transformers.TransformerListener.v1"
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grad_factor = 1.0
|
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pooling = {"@layers":"reduce_mean.v1"}
|
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upstream = "*"
|
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|
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[components.transformer]
|
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factory = "transformer"
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max_batch_items = 4096
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set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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+
|
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[components.transformer.model]
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@architectures = "spacy-transformers.TransformerModel.v1"
|
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name = "KB/bert-base-swedish-cased"
|
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|
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[components.transformer.model.get_spans]
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@span_getters = "spacy-transformers.strided_spans.v1"
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window = 128
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stride = 96
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[components.transformer.model.tokenizer_config]
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use_fast = true
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104 |
+
|
105 |
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[components.transformer_ner]
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factory = "transformer"
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107 |
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max_batch_items = 4096
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set_extra_annotations = {"@annotation_setters":"spacy-transformers.null_annotation_setter.v1"}
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[components.transformer_ner.model]
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@architectures = "spacy-transformers.TransformerModel.v1"
|
112 |
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name = "KB/bert-base-swedish-cased"
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+
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[components.transformer_ner.model.get_spans]
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@span_getters = "spacy-transformers.strided_spans.v1"
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window = 128
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stride = 96
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[components.transformer_ner.model.tokenizer_config]
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use_fast = true
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[corpora]
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[corpora.dev]
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@readers = "spacy.Corpus.v1"
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path = ${paths.dev}
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max_length = 0
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gold_preproc = false
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limit = 0
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augmenter = null
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[corpora.train]
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@readers = "spacy.Corpus.v1"
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path = ${paths.train}
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max_length = 500
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gold_preproc = false
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limit = 0
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augmenter = null
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[training]
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accumulate_gradient = 3
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dev_corpus = "corpora.dev"
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train_corpus = "corpora.train"
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seed = ${system.seed}
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gpu_allocator = ${system.gpu_allocator}
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dropout = 0.1
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patience = 1600
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max_epochs = 0
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max_steps = 20000
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eval_frequency = 200
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frozen_components = []
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before_to_disk = null
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[training.batcher]
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@batchers = "spacy.batch_by_padded.v1"
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discard_oversize = true
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size = 2000
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buffer = 256
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get_length = null
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[training.logger]
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@loggers = "spacy.ConsoleLogger.v1"
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progress_bar = false
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[training.optimizer]
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@optimizers = "Adam.v1"
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beta1 = 0.9
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beta2 = 0.999
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L2_is_weight_decay = true
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L2 = 0.01
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grad_clip = 1.0
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use_averages = false
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eps = 0.00000001
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[training.optimizer.learn_rate]
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@schedules = "warmup_linear.v1"
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warmup_steps = 250
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total_steps = 20000
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initial_rate = 0.00005
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|
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[training.score_weights]
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dep_las_per_type = null
|
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sents_p = null
|
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sents_r = null
|
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ents_per_type = null
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tag_acc = 0.25
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dep_uas = 0.12
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dep_las = 0.12
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sents_f = 0.0
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ents_f = 0.25
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ents_p = 0.0
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ents_r = 0.0
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lemma_acc = 0.25
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|
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[pretraining]
|
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|
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[initialize]
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vectors = null
|
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init_tok2vec = ${paths.init_tok2vec}
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vocab_data = null
|
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lookups = null
|
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before_init = null
|
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after_init = null
|
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|
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[initialize.components]
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|
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[initialize.tokenizer]
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lemmatizer/lookups/lookups.bin
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:eb9a983cec655364535fb0277ad477aaedcaf5758008428d1b6b816f0f9eba2b
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size 13239518
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meta.json
ADDED
@@ -0,0 +1,351 @@
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|
1 |
+
{
|
2 |
+
"lang":"sv",
|
3 |
+
"name":"pipeline",
|
4 |
+
"version":"0.0.0",
|
5 |
+
"description":"This is a transformer-based pipeline for Swedish, which includes tagger, parser, ner and lemmatizer modules. The model was trained on UD Treebanks and the SUC 3.0 dataset at the National Library of Sweden by KBLab. Warning: the lemmatizer is not based on a statistical model and its performance is a bit erratic, so use at your own risk!",
|
6 |
+
"author":"KBLab",
|
7 |
+
"email":"elena.fano@kb.se",
|
8 |
+
"url":"https://kb-labb.github.io/",
|
9 |
+
"license":"mit",
|
10 |
+
"spacy_version":">=3.0.6,<3.1.0",
|
11 |
+
"spacy_git_version":"91a3cab1c",
|
12 |
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|
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|
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|
16 |
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|
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},
|
18 |
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"labels":{
|
19 |
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"transformer":[
|
20 |
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|
21 |
+
],
|
22 |
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"tagger":[
|
23 |
+
"ADJ",
|
24 |
+
"ADP",
|
25 |
+
"ADV",
|
26 |
+
"AUX",
|
27 |
+
"CCONJ",
|
28 |
+
"DET",
|
29 |
+
"INTJ",
|
30 |
+
"NOUN",
|
31 |
+
"NUM",
|
32 |
+
"PART",
|
33 |
+
"PRON",
|
34 |
+
"PROPN",
|
35 |
+
"PUNCT",
|
36 |
+
"SCONJ",
|
37 |
+
"SYM",
|
38 |
+
"VERB",
|
39 |
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"X"
|
40 |
+
],
|
41 |
+
"parser":[
|
42 |
+
"ROOT",
|
43 |
+
"acl",
|
44 |
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"acl:cleft",
|
45 |
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"acl:relcl",
|
46 |
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"advcl",
|
47 |
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"advmod",
|
48 |
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"amod",
|
49 |
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"appos",
|
50 |
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"aux",
|
51 |
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"aux:pass",
|
52 |
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"case",
|
53 |
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"cc",
|
54 |
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"ccomp",
|
55 |
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"compound",
|
56 |
+
"compound:prt",
|
57 |
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"conj",
|
58 |
+
"cop",
|
59 |
+
"csubj",
|
60 |
+
"dep",
|
61 |
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"det",
|
62 |
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"discourse",
|
63 |
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"dislocated",
|
64 |
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"expl",
|
65 |
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"fixed",
|
66 |
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"flat",
|
67 |
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"flat:name",
|
68 |
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"iobj",
|
69 |
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"mark",
|
70 |
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"nmod",
|
71 |
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"nmod:poss",
|
72 |
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"nsubj",
|
73 |
+
"nsubj:pass",
|
74 |
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"nummod",
|
75 |
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"obj",
|
76 |
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"obl",
|
77 |
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"obl:agent",
|
78 |
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"parataxis",
|
79 |
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"punct",
|
80 |
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"xcomp"
|
81 |
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],
|
82 |
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"transformer_ner":[
|
83 |
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|
84 |
+
],
|
85 |
+
"ner":[
|
86 |
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"EVN",
|
87 |
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"LOC",
|
88 |
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"LOC/LOC",
|
89 |
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"LOC/ORG",
|
90 |
+
"LOC/PRS",
|
91 |
+
"MSR",
|
92 |
+
"OBJ",
|
93 |
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"ORG",
|
94 |
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"ORG/PRS",
|
95 |
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"PRS",
|
96 |
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"PRS/WRK",
|
97 |
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"TME",
|
98 |
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"WRK"
|
99 |
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],
|
100 |
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"attribute_ruler":[
|
101 |
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|
102 |
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],
|
103 |
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"lemmatizer":[
|
104 |
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|
105 |
+
]
|
106 |
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},
|
107 |
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"pipeline":[
|
108 |
+
"transformer",
|
109 |
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"tagger",
|
110 |
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"parser",
|
111 |
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"transformer_ner",
|
112 |
+
"ner",
|
113 |
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"attribute_ruler",
|
114 |
+
"lemmatizer"
|
115 |
+
],
|
116 |
+
"components":[
|
117 |
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"transformer",
|
118 |
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"tagger",
|
119 |
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"parser",
|
120 |
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"transformer_ner",
|
121 |
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"ner",
|
122 |
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"attribute_ruler",
|
123 |
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"lemmatizer"
|
124 |
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],
|
125 |
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"disabled":[
|
126 |
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|
127 |
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],
|
128 |
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|
129 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
338 |
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|
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}
|
340 |
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},
|
341 |
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"sents_p":0.9212548015,
|
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|
343 |
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"tag_acc":0.9818079056,
|
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|
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"dep_las":0.883373418,
|
346 |
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"sents_f":0.9289864429,
|
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"transformer_loss":3996.3977112946,
|
348 |
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"tagger_loss":304.7223157457,
|
349 |
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"parser_loss":17219.7631057223
|
350 |
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}
|
351 |
+
}
|
ner/cfg
ADDED
@@ -0,0 +1,12 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"moves":null,
|
3 |
+
"update_with_oracle_cut_size":100,
|
4 |
+
"multitasks":[
|
5 |
+
|
6 |
+
],
|
7 |
+
"min_action_freq":1,
|
8 |
+
"learn_tokens":false,
|
9 |
+
"beam_width":1,
|
10 |
+
"beam_density":0.0,
|
11 |
+
"beam_update_prob":0.0
|
12 |
+
}
|
ner/model
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:9d5b769d72ca7fe8f9d799294f43702e926bed3eac96f4cd25e01acc20250097
|
3 |
+
size 282413
|
ner/moves
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
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parser/cfg
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1 |
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{
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2 |
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"moves":null,
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"update_with_oracle_cut_size":100,
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4 |
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"multitasks":[
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5 |
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|
6 |
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],
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7 |
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"min_action_freq":30,
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8 |
+
"learn_tokens":false,
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"beam_width":1,
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10 |
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"beam_density":0.0,
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"beam_update_prob":0.0
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12 |
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}
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parser/model
ADDED
@@ -0,0 +1,3 @@
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a4211416898c56aaee02eef37a1fed2cabc59129b74d3b6b30843a721ff276c
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size 1138371
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parser/moves
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sv_pipeline-any-py3-none-any.whl
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1 |
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version https://git-lfs.github.com/spec/v1
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oid sha256:bf9fc4f23a04603b4b05cccd2e873c68f23690c872abea6c273e29a4bd4ba84d
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size 935376153
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tagger/cfg
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1 |
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{
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2 |
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"labels":[
|
3 |
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"ADJ",
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4 |
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"ADP",
|
5 |
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"ADV",
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6 |
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"AUX",
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7 |
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"CCONJ",
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8 |
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"DET",
|
9 |
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"INTJ",
|
10 |
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"NOUN",
|
11 |
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"NUM",
|
12 |
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"PART",
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13 |
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"PRON",
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14 |
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"PROPN",
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15 |
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"PUNCT",
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"SCONJ",
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"SYM",
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18 |
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"VERB",
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19 |
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"X"
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20 |
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]
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}
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tagger/model
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version https://git-lfs.github.com/spec/v1
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tokenizer
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