mirror of
https://github.com/explosion/spaCy.git
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108 lines
2.6 KiB
Django/Jinja
108 lines
2.6 KiB
Django/Jinja
{# Template for "CPU" configs. The transformer will use a different template. #}
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# This is an auto-generated partial config for training a model.
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# To use it for training, auto-fill it with all default values.
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# python -m spacy init config config.cfg --base base_config.cfg
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[paths]
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train = ""
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dev = ""
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[nlp]
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lang = "{{ lang }}"
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pipeline = {{ pipeline|safe }}
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vectors = {{ ('"en_vectors_web_lg"' if optimize == "accuracy" else false)|safe }}
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tokenizer = {"@tokenizers": "spacy.Tokenizer.v1"}
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[components]
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[components.tok2vec]
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factory = "tok2vec"
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[components.tok2vec.model]
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@architectures = "spacy.Tok2Vec.v1"
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[components.tok2vec.model.embed]
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@architectures = "spacy.MultiHashEmbed.v1"
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width = ${components.tok2vec.model.encode:width}
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rows = {{ 2000 if optimize == "efficiency" else 7000 }}
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also_embed_subwords = {{ true if has_letters else false }}
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also_use_static_vectors = {{ true if optimize == "accuracy" else false }}
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[components.tok2vec.model.encode]
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@architectures = "spacy.MaxoutWindowEncoder.v1"
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width = {{ 96 if optimize == "efficiency" else 256 }}
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depth = {{ 4 if optimize == "efficiency" else 8 }}
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window_size = 1
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maxout_pieces = 3
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{% if "tagger" in components %}
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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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[components.tagger.model.tok2vec]
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@architectures = "spacy.Tok2VecListener.v1"
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width = ${components.tok2vec.model.encode:width}
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{%- endif %}
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{% if "parser" in components -%}
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[components.parser]
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factory = "parser"
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[components.parser.model]
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@architectures = "spacy.TransitionBasedParser.v1"
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nr_feature_tokens = 8
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hidden_width = 128
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maxout_pieces = 3
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use_upper = true
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nO = null
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[components.parser.model.tok2vec]
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@architectures = "spacy.Tok2VecListener.v1"
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width = ${components.tok2vec.model.encode:width}
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{%- endif %}
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{% if "ner" in components -%}
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[components.ner]
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factory = "ner"
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[components.ner.model]
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@architectures = "spacy.TransitionBasedParser.v1"
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nr_feature_tokens = 6
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hidden_width = 64
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maxout_pieces = 2
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use_upper = true
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nO = null
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[components.ner.model.tok2vec]
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@architectures = "spacy.Tok2VecListener.v1"
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width = ${components.tok2vec.model.encode:width}
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{% endif -%}
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[training]
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[training.train_corpus]
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@readers = "spacy.Corpus.v1"
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path = ${paths:train}
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[training.dev_corpus]
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@readers = "spacy.Corpus.v1"
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path = ${paths:dev}
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[training.score_weights]
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{%- if "tagger" in components %}
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tag_acc = {{ (1.0 / components|length)|round() }}
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{%- endif -%}
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{%- if "parser" in components %}
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dep_uas = 0.0
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dep_las = {{ (1.0 / components|length)|round() }}
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sents_f = 0.0
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{%- endif %}
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{%- if "ner" in components %}
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ents_f = {{ (1.0 / components|length)|round() }}
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ents_p = 0.0
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ents_r = 0.0
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{%- endif -%}
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