/
base_parser_tagger.cfg
173 lines (143 loc) · 3.33 KB
/
base_parser_tagger.cfg
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[vars]
include_static_vectors = null
[paths]
genia_train = "project_data/genia_train.spacy"
genia_dev = "project_data/genia_dev.spacy"
onto_train = "project_data/train"
vectors = null
init_tok2vec = null
vocab_path = null
[system]
gpu_allocator = null
seed = 0
[nlp]
lang = "en"
pipeline = ["tok2vec","tagger","attribute_ruler","lemmatizer","parser"]
tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
disabled = []
before_creation = null
after_creation = null
after_pipeline_creation = null
[components]
[components.attribute_ruler]
source = "en_core_web_sm"
[components.lemmatizer]
source = "en_core_web_sm"
[components.parser]
factory = "parser"
learn_tokens = false
min_action_freq = 30
moves = null
update_with_oracle_cut_size = 100
[components.parser.model]
@architectures = "spacy.TransitionBasedParser.v2"
state_type = "parser"
extra_state_tokens = false
hidden_width = 128
maxout_pieces = 3
use_upper = true
nO = null
[components.parser.model.tok2vec]
@architectures = "spacy.Tok2VecListener.v1"
width = ${components.tok2vec.model.encode.width}
upstream = "*"
[components.tagger]
factory = "tagger"
[components.tagger.model]
@architectures = "spacy.Tagger.v1"
nO = null
[components.tagger.model.tok2vec]
@architectures = "spacy.Tok2VecListener.v1"
width = ${components.tok2vec.model.encode.width}
upstream = "*"
[components.tok2vec]
factory = "tok2vec"
[components.tok2vec.model]
@architectures = "spacy.Tok2Vec.v2"
[components.tok2vec.model.embed]
@architectures = "spacy.MultiHashEmbed.v2"
width = ${components.tok2vec.model.encode.width}
attrs = ["NORM", "PREFIX", "SUFFIX", "SHAPE", "SPACY"]
rows = [5000, 2500, 2500, 2500, 100]
include_static_vectors = ${vars.include_static_vectors}
[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.genia_dev}
max_length = 0
gold_preproc = false
limit = 0
augmenter = null
[corpora.train]
@readers = "parser_tagger_data"
path = ${paths.genia_train}
mixin_data_path = ${paths.onto_train}
mixin_data_percent = 0.2
max_length = 2000
gold_preproc = false
limit = 0
augmenter = null
seed = ${system.seed}
[training]
dev_corpus = "corpora.dev"
train_corpus = "corpora.train"
seed = ${system.seed}
gpu_allocator = ${system.gpu_allocator}
dropout = 0.1
accumulate_gradient = 1
patience = 0
max_epochs = 20
max_steps = 0
eval_frequency = 2300
frozen_components = ["attribute_ruler", "lemmatizer"]
before_to_disk = null
[training.batcher]
@batchers = "spacy.batch_by_sequence.v1"
get_length = null
[training.batcher.size]
@schedules = "compounding.v1"
start = 1
stop = 16
compound = 1.001
t = 0.0
[training.logger]
@loggers = "spacy.ConsoleLogger.v1"
progress_bar = true
[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]
dep_las_per_type = null
sents_p = null
sents_r = null
ents_per_type = null
tag_acc = 0.33
dep_uas = 0.33
dep_las = 0.33
sents_f = 0.0
ents_f = 0.0
ents_p = 0.0
ents_r = 0.0
[pretraining]
[initialize]
vectors = ${paths.vectors}
init_tok2vec = ${paths.init_tok2vec}
vocab_data = ${paths.vocab_path}
lookups = null
[initialize.components]
[initialize.tokenizer]
[initialize.before_init]
@callbacks = "replace_tokenizer"