2020-08-13 15:38:30 +00:00
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{# This is a template for training configs used for the quickstart widget in
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the docs and the init config command. It encodes various best practices and
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can help generate the best possible configuration, given a user's requirements. #}
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2020-08-15 12:50:29 +00:00
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{%- set use_transformer = (transformer_data and hardware != "cpu") -%}
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{%- set transformer = transformer_data[optimize] if use_transformer else {} -%}
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2020-08-13 15:38:30 +00:00
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[paths]
|
2020-09-29 20:33:46 +00:00
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train = null
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dev = null
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2020-08-13 15:38:30 +00:00
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2020-08-15 12:50:29 +00:00
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[system]
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2020-09-20 10:30:53 +00:00
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{% if use_transformer -%}
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gpu_allocator = "pytorch"
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{% else -%}
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gpu_allocator = null
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{% endif %}
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2020-08-15 12:50:29 +00:00
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2020-08-13 15:38:30 +00:00
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[nlp]
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lang = "{{ lang }}"
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2020-08-15 12:50:29 +00:00
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{%- set full_pipeline = ["transformer" if use_transformer else "tok2vec"] + components %}
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pipeline = {{ full_pipeline|pprint()|replace("'", '"')|safe }}
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2020-08-13 15:38:30 +00:00
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tokenizer = {"@tokenizers": "spacy.Tokenizer.v1"}
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[components]
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{# TRANSFORMER PIPELINE #}
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2020-08-15 12:50:29 +00:00
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{%- if use_transformer -%}
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2020-08-13 15:38:30 +00:00
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[components.transformer]
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factory = "transformer"
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[components.transformer.model]
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@architectures = "spacy-transformers.TransformerModel.v1"
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2020-08-15 12:50:29 +00:00
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name = "{{ transformer["name"] }}"
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2020-08-13 15:38:30 +00:00
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tokenizer_config = {"use_fast": true}
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[components.transformer.model.get_spans]
|
2020-09-03 15:37:06 +00:00
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@span_getters = "spacy-transformers.strided_spans.v1"
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2020-08-13 15:38:30 +00:00
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window = 128
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stride = 96
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2020-10-02 13:06:16 +00:00
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{% if "morphologizer" in components %}
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[components.morphologizer]
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factory = "morphologizer"
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[components.morphologizer.model]
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@architectures = "spacy.Tagger.v1"
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nO = null
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[components.morphologizer.model.tok2vec]
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@architectures = "spacy-transformers.TransformerListener.v1"
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grad_factor = 1.0
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[components.morphologizer.model.tok2vec.pooling]
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@layers = "reduce_mean.v1"
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{%- endif %}
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2020-08-13 15:38:30 +00:00
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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]
|
2020-08-31 10:41:39 +00:00
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@architectures = "spacy-transformers.TransformerListener.v1"
|
2020-08-13 15:38:30 +00:00
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grad_factor = 1.0
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[components.tagger.model.tok2vec.pooling]
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@layers = "reduce_mean.v1"
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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"
|
2020-09-23 14:53:49 +00:00
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state_type = "parser"
|
2020-09-23 11:35:09 +00:00
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extra_state_tokens = false
|
2020-08-13 15:38:30 +00:00
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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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|
[components.parser.model.tok2vec]
|
2020-08-31 10:41:39 +00:00
|
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|
@architectures = "spacy-transformers.TransformerListener.v1"
|
2020-08-13 15:38:30 +00:00
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grad_factor = 1.0
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[components.parser.model.tok2vec.pooling]
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@layers = "reduce_mean.v1"
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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"
|
2020-09-23 11:35:09 +00:00
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state_type = "ner"
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|
extra_state_tokens = false
|
2020-08-13 15:38:30 +00:00
|
|
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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]
|
2020-08-31 10:41:39 +00:00
|
|
|
@architectures = "spacy-transformers.TransformerListener.v1"
|
2020-08-13 15:38:30 +00:00
|
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|
grad_factor = 1.0
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[components.ner.model.tok2vec.pooling]
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@layers = "reduce_mean.v1"
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{% endif -%}
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|
2020-09-22 08:40:05 +00:00
|
|
|
{% if "entity_linker" in components -%}
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|
[components.entity_linker]
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|
|
factory = "entity_linker"
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|
get_candidates = {"@misc":"spacy.CandidateGenerator.v1"}
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|
incl_context = true
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|
incl_prior = true
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[components.entity_linker.model]
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|
@architectures = "spacy.EntityLinker.v1"
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nO = null
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|
|
[components.entity_linker.model.tok2vec]
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|
|
@architectures = "spacy-transformers.TransformerListener.v1"
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|
grad_factor = 1.0
|
2020-09-23 07:24:28 +00:00
|
|
|
|
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|
|
[components.entity_linker.model.tok2vec.pooling]
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|
@layers = "reduce_mean.v1"
|
2020-09-22 08:40:05 +00:00
|
|
|
{% endif -%}
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|
2020-09-22 08:22:06 +00:00
|
|
|
{% if "textcat" in components %}
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|
[components.textcat]
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|
|
factory = "textcat"
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|
|
{% if optimize == "accuracy" %}
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|
[components.textcat.model]
|
2020-10-18 12:50:41 +00:00
|
|
|
@architectures = "spacy.TextCatEnsemble.v2"
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|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.textcat.model.tok2vec]
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|
|
|
@architectures = "spacy-transformers.TransformerListener.v1"
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|
|
|
grad_factor = 1.0
|
|
|
|
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|
|
[components.textcat.model.linear_model]
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|
|
@architectures = "spacy.TextCatBOW.v1"
|
2020-09-22 08:22:06 +00:00
|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
2020-10-18 12:50:41 +00:00
|
|
|
no_output_layer = false
|
2020-09-22 08:22:06 +00:00
|
|
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|
|
{% else -%}
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|
[components.textcat.model]
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|
|
|
@architectures = "spacy.TextCatBOW.v1"
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|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
2020-09-22 10:06:40 +00:00
|
|
|
no_output_layer = false
|
2020-09-22 08:22:06 +00:00
|
|
|
{%- endif %}
|
|
|
|
{%- endif %}
|
|
|
|
|
2020-08-13 15:38:30 +00:00
|
|
|
{# NON-TRANSFORMER PIPELINE #}
|
|
|
|
{% else -%}
|
|
|
|
|
|
|
|
{%- if hardware == "gpu" -%}
|
|
|
|
# There are no recommended transformer weights available for language '{{ lang }}'
|
|
|
|
# yet, so the pipeline described here is not transformer-based.
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|
|
{%- endif %}
|
|
|
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|
|
|
[components.tok2vec]
|
|
|
|
factory = "tok2vec"
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|
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|
|
[components.tok2vec.model]
|
|
|
|
@architectures = "spacy.Tok2Vec.v1"
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|
|
|
|
|
|
|
[components.tok2vec.model.embed]
|
|
|
|
@architectures = "spacy.MultiHashEmbed.v1"
|
2020-08-20 09:20:58 +00:00
|
|
|
width = ${components.tok2vec.model.encode.width}
|
2020-10-05 19:19:41 +00:00
|
|
|
{% if has_letters -%}
|
|
|
|
attrs = ["NORM", "PREFIX", "SUFFIX", "SHAPE"]
|
|
|
|
rows = [5000, 2500, 2500, 2500]
|
|
|
|
{% else -%}
|
|
|
|
attrs = ["ORTH", "SHAPE"]
|
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|
|
rows = [5000, 2500]
|
|
|
|
{% endif -%}
|
2020-10-05 19:21:30 +00:00
|
|
|
include_static_vectors = {{ "true" if optimize == "accuracy" else "false" }}
|
2020-08-13 15:38:30 +00:00
|
|
|
|
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|
|
[components.tok2vec.model.encode]
|
|
|
|
@architectures = "spacy.MaxoutWindowEncoder.v1"
|
|
|
|
width = {{ 96 if optimize == "efficiency" else 256 }}
|
|
|
|
depth = {{ 4 if optimize == "efficiency" else 8 }}
|
|
|
|
window_size = 1
|
|
|
|
maxout_pieces = 3
|
|
|
|
|
2020-10-02 13:06:16 +00:00
|
|
|
{% if "morphologizer" in components %}
|
|
|
|
[components.morphologizer]
|
|
|
|
factory = "morphologizer"
|
|
|
|
|
|
|
|
[components.morphologizer.model]
|
|
|
|
@architectures = "spacy.Tagger.v1"
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.morphologizer.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
|
|
|
width = ${components.tok2vec.model.encode.width}
|
|
|
|
{%- endif %}
|
|
|
|
|
2020-08-13 15:38:30 +00:00
|
|
|
{% if "tagger" in components %}
|
|
|
|
[components.tagger]
|
|
|
|
factory = "tagger"
|
|
|
|
|
|
|
|
[components.tagger.model]
|
|
|
|
@architectures = "spacy.Tagger.v1"
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.tagger.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
2020-08-20 09:20:58 +00:00
|
|
|
width = ${components.tok2vec.model.encode.width}
|
2020-08-13 15:38:30 +00:00
|
|
|
{%- endif %}
|
|
|
|
|
|
|
|
{% if "parser" in components -%}
|
|
|
|
[components.parser]
|
|
|
|
factory = "parser"
|
|
|
|
|
|
|
|
[components.parser.model]
|
|
|
|
@architectures = "spacy.TransitionBasedParser.v1"
|
2020-09-23 14:53:49 +00:00
|
|
|
state_type = "parser"
|
2020-09-23 11:35:09 +00:00
|
|
|
extra_state_tokens = false
|
2020-08-13 15:38:30 +00:00
|
|
|
hidden_width = 128
|
|
|
|
maxout_pieces = 3
|
|
|
|
use_upper = true
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.parser.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
2020-08-20 09:20:58 +00:00
|
|
|
width = ${components.tok2vec.model.encode.width}
|
2020-08-13 15:38:30 +00:00
|
|
|
{%- endif %}
|
|
|
|
|
|
|
|
{% if "ner" in components %}
|
|
|
|
[components.ner]
|
|
|
|
factory = "ner"
|
|
|
|
|
|
|
|
[components.ner.model]
|
|
|
|
@architectures = "spacy.TransitionBasedParser.v1"
|
2020-09-23 11:35:09 +00:00
|
|
|
state_type = "ner"
|
|
|
|
extra_state_tokens = false
|
2020-08-13 15:38:30 +00:00
|
|
|
hidden_width = 64
|
|
|
|
maxout_pieces = 2
|
|
|
|
use_upper = true
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.ner.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
2020-08-20 09:20:58 +00:00
|
|
|
width = ${components.tok2vec.model.encode.width}
|
2020-08-13 15:38:30 +00:00
|
|
|
{% endif %}
|
2020-09-22 08:22:06 +00:00
|
|
|
|
2020-09-22 08:40:05 +00:00
|
|
|
{% if "entity_linker" in components -%}
|
|
|
|
[components.entity_linker]
|
|
|
|
factory = "entity_linker"
|
|
|
|
get_candidates = {"@misc":"spacy.CandidateGenerator.v1"}
|
|
|
|
incl_context = true
|
|
|
|
incl_prior = true
|
|
|
|
|
|
|
|
[components.entity_linker.model]
|
|
|
|
@architectures = "spacy.EntityLinker.v1"
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.entity_linker.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
|
|
|
width = ${components.tok2vec.model.encode.width}
|
|
|
|
{% endif %}
|
|
|
|
|
2020-09-22 08:22:06 +00:00
|
|
|
{% if "textcat" in components %}
|
|
|
|
[components.textcat]
|
|
|
|
factory = "textcat"
|
|
|
|
|
|
|
|
{% if optimize == "accuracy" %}
|
|
|
|
[components.textcat.model]
|
2020-10-18 12:50:41 +00:00
|
|
|
@architectures = "spacy.TextCatEnsemble.v2"
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.textcat.model.tok2vec]
|
|
|
|
@architectures = "spacy.Tok2VecListener.v1"
|
|
|
|
width = ${components.tok2vec.model.encode.width}
|
|
|
|
|
|
|
|
[components.textcat.model.linear_model]
|
|
|
|
@architectures = "spacy.TextCatBOW.v1"
|
2020-09-22 08:22:06 +00:00
|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
2020-10-18 12:50:41 +00:00
|
|
|
no_output_layer = false
|
2020-09-22 08:22:06 +00:00
|
|
|
|
|
|
|
{% else -%}
|
|
|
|
[components.textcat.model]
|
|
|
|
@architectures = "spacy.TextCatBOW.v1"
|
|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
2020-09-22 10:06:40 +00:00
|
|
|
no_output_layer = false
|
2020-09-22 08:22:06 +00:00
|
|
|
{%- endif %}
|
|
|
|
{%- endif %}
|
2020-08-13 15:38:30 +00:00
|
|
|
{% endif %}
|
|
|
|
|
|
|
|
{% for pipe in components %}
|
2020-10-02 13:06:16 +00:00
|
|
|
{% if pipe not in ["tagger", "morphologizer", "parser", "ner", "textcat", "entity_linker"] %}
|
2020-08-13 15:38:30 +00:00
|
|
|
{# Other components defined by the user: we just assume they're factories #}
|
|
|
|
[components.{{ pipe }}]
|
|
|
|
factory = "{{ pipe }}"
|
|
|
|
{% endif %}
|
|
|
|
{% endfor %}
|
|
|
|
|
2020-09-17 09:38:59 +00:00
|
|
|
[corpora]
|
|
|
|
|
|
|
|
[corpora.train]
|
|
|
|
@readers = "spacy.Corpus.v1"
|
|
|
|
path = ${paths.train}
|
|
|
|
max_length = {{ 500 if hardware == "gpu" else 2000 }}
|
|
|
|
|
|
|
|
[corpora.dev]
|
|
|
|
@readers = "spacy.Corpus.v1"
|
|
|
|
path = ${paths.dev}
|
|
|
|
max_length = 0
|
|
|
|
|
2020-08-13 15:38:30 +00:00
|
|
|
[training]
|
2020-08-15 12:50:29 +00:00
|
|
|
{% if use_transformer -%}
|
|
|
|
accumulate_gradient = {{ transformer["size_factor"] }}
|
2020-09-23 11:21:42 +00:00
|
|
|
{% endif -%}
|
2020-09-17 09:38:59 +00:00
|
|
|
dev_corpus = "corpora.dev"
|
|
|
|
train_corpus = "corpora.train"
|
2020-08-13 15:38:30 +00:00
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[training.optimizer]
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@optimizers = "Adam.v1"
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2020-09-04 19:22:50 +00:00
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{% if use_transformer -%}
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2020-08-13 15:38:30 +00:00
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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 = 5e-5
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2020-09-04 19:22:50 +00:00
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{% endif %}
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2020-08-13 15:38:30 +00:00
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2020-08-15 12:50:29 +00:00
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{% if use_transformer %}
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2020-08-13 15:38:30 +00:00
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[training.batcher]
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2020-09-03 15:30:41 +00:00
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@batchers = "spacy.batch_by_padded.v1"
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2020-08-13 15:38:30 +00:00
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discard_oversize = true
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size = 2000
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buffer = 256
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{%- else %}
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[training.batcher]
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2020-09-03 15:30:41 +00:00
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@batchers = "spacy.batch_by_words.v1"
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2020-08-13 15:38:30 +00:00
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discard_oversize = false
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tolerance = 0.2
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[training.batcher.size]
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@schedules = "compounding.v1"
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start = 100
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stop = 1000
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compound = 1.001
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{% endif %}
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2020-09-28 10:05:23 +00:00
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[initialize]
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{% if use_transformer or optimize == "efficiency" or not word_vectors -%}
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vectors = null
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{% else -%}
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vectors = "{{ word_vectors }}"
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{% endif -%}
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