Update configs

This commit is contained in:
Matthw Honnibal 2020-07-06 17:51:37 +02:00
parent f25761e513
commit 1eb1654941

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@ -9,12 +9,12 @@ max_length = 5000
limit = 0
# Data augmentation
orth_variant_level = 0.0
dropout = 0.2
dropout = 0.1
# Controls early-stopping. 0 or -1 mean unlimited.
patience = 1600
patience = 100000
max_epochs = 0
max_steps = 20000
eval_frequency = 500
max_steps = 100000
eval_frequency = 2000
# Other settings
seed = 0
accumulate_gradient = 1
@ -30,25 +30,25 @@ omit_extra_lookups = false
[training.batch_size]
@schedules = "compounding.v1"
start = 100
stop = 1000
stop = 2000
compound = 1.001
[training.optimizer]
@optimizers = "Adam.v1"
beta1 = 0.9
beta2 = 0.999
L2_is_weight_decay = false
L2 = 1e-6
L2_is_weight_decay = true
L2 = 0.0
grad_clip = 1.0
use_averages = true
eps = 1e-8
learn_rate = 0.001
#[optimizer.learn_rate]
#[training.optimizer.learn_rate]
#@schedules = "warmup_linear.v1"
#warmup_steps = 250
#total_steps = 20000
#initial_rate = 0.001
#warmup_steps = 1000
#total_steps = 50000
#initial_rate = 0.003
[nlp]
lang = "en"
@ -58,23 +58,21 @@ vectors = null
factory = "ner"
learn_tokens = false
min_action_freq = 1
beam_width = 1
beam_update_prob = 1.0
[nlp.pipeline.ner.model]
@architectures = "spacy.TransitionBasedParser.v1"
nr_feature_tokens = 3
hidden_width = 64
maxout_pieces = 2
use_upper = true
use_upper = false
[nlp.pipeline.ner.model.tok2vec]
@architectures = "spacy.HashEmbedCNN.v1"
pretrained_vectors = ${nlp:vectors}
width = 96
width = 300
depth = 4
window_size = 1
embed_size = 2000
maxout_pieces = 3
embed_size = 7000
maxout_pieces = 1
subword_features = true
dropout = ${training:dropout}