spaCy/examples/experiments/tok2vec-ner/multihashembed_tok2vec.cfg
Sofie Van Landeghem 7f5715a081
Various fixes to NEL functionality, Example class etc (#5460)
* setting KB in the EL constructor, similar to how the model is passed on

* removing wikipedia example files - moved to projects

* throw an error when nlp.update is called with 2 positional arguments

* rewriting the config logic in create pipe to accomodate for other objects (e.g. KB) in the config

* update config files with new parameters

* avoid training pipeline components that don't have a model (like sentencizer)

* various small fixes + UX improvements

* small fixes

* set thinc to 8.0.0a9 everywhere

* remove outdated comment
2020-05-20 11:41:12 +02:00

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INI

[training]
use_gpu = -1
limit = 0
dropout = 0.2
patience = 10000
eval_frequency = 200
scores = ["ents_p", "ents_r", "ents_f"]
score_weights = {"ents_f": 1}
orth_variant_level = 0.0
gold_preproc = true
max_length = 0
seed = 0
accumulate_gradient = 2
[training.batch_size]
@schedules = "compounding.v1"
start = 3000
stop = 3000
compound = 1.001
[optimizer]
@optimizers = "Adam.v1"
learn_rate = 0.001
beta1 = 0.9
beta2 = 0.999
[nlp]
lang = "en"
vectors = null
[nlp.pipeline.ner]
factory = "simple_ner"
[nlp.pipeline.ner.model]
@architectures = "spacy.BiluoTagger.v1"
[nlp.pipeline.ner.model.tok2vec]
@architectures = "spacy.HashEmbedCNN.v1"
width = 128
depth = 4
embed_size = 7000
maxout_pieces = 3
window_size = 1
subword_features = true
pretrained_vectors = null