2020-08-13 15:38:30 +00:00
|
|
|
{# This is a template for training configs used for the quickstart widget in
|
|
|
|
the docs and the init config command. It encodes various best practices and
|
|
|
|
can help generate the best possible configuration, given a user's requirements. #}
|
2020-08-15 12:50:29 +00:00
|
|
|
{%- set use_transformer = (transformer_data and hardware != "cpu") -%}
|
|
|
|
{%- set transformer = transformer_data[optimize] if use_transformer else {} -%}
|
2020-08-13 15:38:30 +00:00
|
|
|
[paths]
|
|
|
|
train = ""
|
|
|
|
dev = ""
|
|
|
|
|
2020-08-15 12:50:29 +00:00
|
|
|
[system]
|
2020-09-20 10:30:53 +00:00
|
|
|
{% if use_transformer -%}
|
|
|
|
gpu_allocator = "pytorch"
|
|
|
|
{% else -%}
|
|
|
|
gpu_allocator = null
|
|
|
|
{% endif %}
|
2020-08-15 12:50:29 +00:00
|
|
|
|
2020-08-13 15:38:30 +00:00
|
|
|
[nlp]
|
|
|
|
lang = "{{ lang }}"
|
2020-08-15 12:50:29 +00:00
|
|
|
{%- set full_pipeline = ["transformer" if use_transformer else "tok2vec"] + components %}
|
|
|
|
pipeline = {{ full_pipeline|pprint()|replace("'", '"')|safe }}
|
2020-08-13 15:38:30 +00:00
|
|
|
tokenizer = {"@tokenizers": "spacy.Tokenizer.v1"}
|
|
|
|
|
|
|
|
[components]
|
|
|
|
|
|
|
|
{# TRANSFORMER PIPELINE #}
|
2020-08-15 12:50:29 +00:00
|
|
|
{%- if use_transformer -%}
|
2020-08-13 15:38:30 +00:00
|
|
|
[components.transformer]
|
|
|
|
factory = "transformer"
|
|
|
|
|
|
|
|
[components.transformer.model]
|
|
|
|
@architectures = "spacy-transformers.TransformerModel.v1"
|
2020-08-15 12:50:29 +00:00
|
|
|
name = "{{ transformer["name"] }}"
|
2020-08-13 15:38:30 +00:00
|
|
|
tokenizer_config = {"use_fast": true}
|
|
|
|
|
|
|
|
[components.transformer.model.get_spans]
|
2020-09-03 15:37:06 +00:00
|
|
|
@span_getters = "spacy-transformers.strided_spans.v1"
|
2020-08-13 15:38:30 +00:00
|
|
|
window = 128
|
|
|
|
stride = 96
|
|
|
|
|
|
|
|
{% if "tagger" in components %}
|
|
|
|
[components.tagger]
|
|
|
|
factory = "tagger"
|
|
|
|
|
|
|
|
[components.tagger.model]
|
|
|
|
@architectures = "spacy.Tagger.v1"
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.tagger.model.tok2vec]
|
2020-08-31 10:41:39 +00:00
|
|
|
@architectures = "spacy-transformers.TransformerListener.v1"
|
2020-08-13 15:38:30 +00:00
|
|
|
grad_factor = 1.0
|
|
|
|
|
|
|
|
[components.tagger.model.tok2vec.pooling]
|
|
|
|
@layers = "reduce_mean.v1"
|
|
|
|
{%- endif %}
|
|
|
|
|
|
|
|
{% if "parser" in components -%}
|
|
|
|
[components.parser]
|
|
|
|
factory = "parser"
|
|
|
|
|
|
|
|
[components.parser.model]
|
|
|
|
@architectures = "spacy.TransitionBasedParser.v1"
|
|
|
|
nr_feature_tokens = 8
|
|
|
|
hidden_width = 128
|
|
|
|
maxout_pieces = 3
|
|
|
|
use_upper = false
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[components.parser.model.tok2vec]
|
2020-08-31 10:41:39 +00:00
|
|
|
@architectures = "spacy-transformers.TransformerListener.v1"
|
2020-08-13 15:38:30 +00:00
|
|
|
grad_factor = 1.0
|
|
|
|
|
|
|
|
[components.parser.model.tok2vec.pooling]
|
|
|
|
@layers = "reduce_mean.v1"
|
|
|
|
{%- endif %}
|
|
|
|
|
|
|
|
{% if "ner" in components -%}
|
|
|
|
[components.ner]
|
|
|
|
factory = "ner"
|
|
|
|
|
|
|
|
[components.ner.model]
|
|
|
|
@architectures = "spacy.TransitionBasedParser.v1"
|
|
|
|
nr_feature_tokens = 3
|
|
|
|
hidden_width = 64
|
|
|
|
maxout_pieces = 2
|
|
|
|
use_upper = false
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
[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
|
|
|
grad_factor = 1.0
|
|
|
|
|
|
|
|
[components.ner.model.tok2vec.pooling]
|
|
|
|
@layers = "reduce_mean.v1"
|
|
|
|
{% endif -%}
|
|
|
|
|
2020-09-22 08:22:06 +00:00
|
|
|
{% if "textcat" in components %}
|
|
|
|
[components.textcat]
|
|
|
|
factory = "textcat"
|
|
|
|
|
|
|
|
{% if optimize == "accuracy" %}
|
|
|
|
[components.textcat.model]
|
|
|
|
@architectures = "spacy.TextCatEnsemble.v1"
|
|
|
|
exclusive_classes = false
|
|
|
|
width = 64
|
|
|
|
conv_depth = 2
|
|
|
|
embed_size = 2000
|
|
|
|
window_size = 1
|
|
|
|
ngram_size = 1
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
{% else -%}
|
|
|
|
[components.textcat.model]
|
|
|
|
@architectures = "spacy.TextCatBOW.v1"
|
|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
|
|
|
{%- 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.
|
|
|
|
{%- endif %}
|
|
|
|
|
|
|
|
[components.tok2vec]
|
|
|
|
factory = "tok2vec"
|
|
|
|
|
|
|
|
[components.tok2vec.model]
|
|
|
|
@architectures = "spacy.Tok2Vec.v1"
|
|
|
|
|
|
|
|
[components.tok2vec.model.embed]
|
|
|
|
@architectures = "spacy.MultiHashEmbed.v1"
|
2020-08-20 09:20:58 +00:00
|
|
|
width = ${components.tok2vec.model.encode.width}
|
2020-08-13 15:38:30 +00:00
|
|
|
rows = {{ 2000 if optimize == "efficiency" else 7000 }}
|
2020-08-20 22:10:21 +00:00
|
|
|
also_embed_subwords = {{ "true" if has_letters else "false" }}
|
|
|
|
also_use_static_vectors = {{ "true" if optimize == "accuracy" else "false" }}
|
2020-08-13 15:38:30 +00:00
|
|
|
|
|
|
|
[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
|
|
|
|
|
|
|
|
{% 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"
|
|
|
|
nr_feature_tokens = 8
|
|
|
|
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"
|
|
|
|
nr_feature_tokens = 6
|
|
|
|
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
|
|
|
|
|
|
|
{% if "textcat" in components %}
|
|
|
|
[components.textcat]
|
|
|
|
factory = "textcat"
|
|
|
|
|
|
|
|
{% if optimize == "accuracy" %}
|
|
|
|
[components.textcat.model]
|
|
|
|
@architectures = "spacy.TextCatEnsemble.v1"
|
|
|
|
exclusive_classes = false
|
|
|
|
width = 64
|
|
|
|
conv_depth = 2
|
|
|
|
embed_size = 2000
|
|
|
|
window_size = 1
|
|
|
|
ngram_size = 1
|
|
|
|
nO = null
|
|
|
|
|
|
|
|
{% else -%}
|
|
|
|
[components.textcat.model]
|
|
|
|
@architectures = "spacy.TextCatBOW.v1"
|
|
|
|
exclusive_classes = false
|
|
|
|
ngram_size = 1
|
|
|
|
{%- endif %}
|
|
|
|
{%- endif %}
|
2020-08-13 15:38:30 +00:00
|
|
|
{% endif %}
|
|
|
|
|
|
|
|
{% for pipe in components %}
|
2020-09-22 08:22:06 +00:00
|
|
|
{% if pipe not in ["tagger", "parser", "ner", "textcat"] %}
|
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 or optimize == "efficiency" or not word_vectors -%}
|
|
|
|
vectors = null
|
|
|
|
{% else -%}
|
|
|
|
vectors = "{{ word_vectors }}"
|
2020-08-13 15:38:30 +00:00
|
|
|
{% endif -%}
|
2020-08-15 12:50:29 +00:00
|
|
|
{% if use_transformer -%}
|
|
|
|
accumulate_gradient = {{ transformer["size_factor"] }}
|
|
|
|
{% 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
|
|
|
|
|
|
|
[training.optimizer]
|
|
|
|
@optimizers = "Adam.v1"
|
|
|
|
|
2020-09-04 19:22:50 +00:00
|
|
|
{% if use_transformer -%}
|
2020-08-13 15:38:30 +00:00
|
|
|
[training.optimizer.learn_rate]
|
|
|
|
@schedules = "warmup_linear.v1"
|
|
|
|
warmup_steps = 250
|
|
|
|
total_steps = 20000
|
|
|
|
initial_rate = 5e-5
|
2020-09-04 19:22:50 +00:00
|
|
|
{% endif %}
|
2020-08-13 15:38:30 +00:00
|
|
|
|
2020-08-15 12:50:29 +00:00
|
|
|
{% if use_transformer %}
|
2020-08-13 15:38:30 +00:00
|
|
|
[training.batcher]
|
2020-09-03 15:30:41 +00:00
|
|
|
@batchers = "spacy.batch_by_padded.v1"
|
2020-08-13 15:38:30 +00:00
|
|
|
discard_oversize = true
|
|
|
|
size = 2000
|
|
|
|
buffer = 256
|
|
|
|
{%- else %}
|
|
|
|
[training.batcher]
|
2020-09-03 15:30:41 +00:00
|
|
|
@batchers = "spacy.batch_by_words.v1"
|
2020-08-13 15:38:30 +00:00
|
|
|
discard_oversize = false
|
|
|
|
tolerance = 0.2
|
|
|
|
|
|
|
|
[training.batcher.size]
|
|
|
|
@schedules = "compounding.v1"
|
|
|
|
start = 100
|
|
|
|
stop = 1000
|
|
|
|
compound = 1.001
|
|
|
|
{% endif %}
|
|
|
|
|
|
|
|
[training.score_weights]
|
|
|
|
{%- if "tagger" in components %}
|
|
|
|
tag_acc = {{ (1.0 / components|length)|round(2) }}
|
|
|
|
{%- endif -%}
|
|
|
|
{%- if "parser" in components %}
|
|
|
|
dep_uas = 0.0
|
|
|
|
dep_las = {{ (1.0 / components|length)|round(2) }}
|
|
|
|
sents_f = 0.0
|
|
|
|
{%- endif %}
|
|
|
|
{%- if "ner" in components %}
|
|
|
|
ents_f = {{ (1.0 / components|length)|round(2) }}
|
|
|
|
ents_p = 0.0
|
|
|
|
ents_r = 0.0
|
|
|
|
{%- endif -%}
|