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Update configs

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This commit is contained in:
Matthw Honnibal 2020-07-06 17:51:37 +02:00
parent f25761e513
commit 1eb1654941
1 changed files with 15 additions and 17 deletions
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examples/experiments/onto-ner.cfg
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@ -9,12 +9,12 @@ max_length = 5000
limit = 0 limit = 0
# Data augmentation # Data augmentation
orth_variant_level = 0.0 orth_variant_level = 0.0
dropout = 0.2 dropout = 0.1
# Controls early-stopping. 0 or -1 mean unlimited. # Controls early-stopping. 0 or -1 mean unlimited.
patience = 1600 patience = 100000
max_epochs = 0 max_epochs = 0
max_steps = 20000 max_steps = 100000
eval_frequency = 500 eval_frequency = 2000
# Other settings # Other settings
seed = 0 seed = 0
accumulate_gradient = 1 accumulate_gradient = 1
@ -30,25 +30,25 @@ omit_extra_lookups = false
[training.batch_size] [training.batch_size]
@schedules = "compounding.v1" @schedules = "compounding.v1"
start = 100 start = 100
stop = 1000 stop = 2000
compound = 1.001 compound = 1.001
[training.optimizer] [training.optimizer]
@optimizers = "Adam.v1" @optimizers = "Adam.v1"
beta1 = 0.9 beta1 = 0.9
beta2 = 0.999 beta2 = 0.999
L2_is_weight_decay = false L2_is_weight_decay = true
L2 = 1e-6 L2 = 0.0
grad_clip = 1.0 grad_clip = 1.0
use_averages = true use_averages = true
eps = 1e-8 eps = 1e-8
learn_rate = 0.001 learn_rate = 0.001
#[optimizer.learn_rate] #[training.optimizer.learn_rate]
#@schedules = "warmup_linear.v1" #@schedules = "warmup_linear.v1"
#warmup_steps = 250 #warmup_steps = 1000
#total_steps = 20000 #total_steps = 50000
#initial_rate = 0.001 #initial_rate = 0.003
[nlp] [nlp]
lang = "en" lang = "en"
@ -58,23 +58,21 @@ vectors = null
factory = "ner" factory = "ner"
learn_tokens = false learn_tokens = false
min_action_freq = 1 min_action_freq = 1
beam_width = 1
beam_update_prob = 1.0
[nlp.pipeline.ner.model] [nlp.pipeline.ner.model]
@architectures = "spacy.TransitionBasedParser.v1" @architectures = "spacy.TransitionBasedParser.v1"
nr_feature_tokens = 3 nr_feature_tokens = 3
hidden_width = 64 hidden_width = 64
maxout_pieces = 2 maxout_pieces = 2
use_upper = true use_upper = false
[nlp.pipeline.ner.model.tok2vec] [nlp.pipeline.ner.model.tok2vec]
@architectures = "spacy.HashEmbedCNN.v1" @architectures = "spacy.HashEmbedCNN.v1"
pretrained_vectors = ${nlp:vectors} pretrained_vectors = ${nlp:vectors}
width = 96 width = 300
depth = 4 depth = 4
window_size = 1 window_size = 1
embed_size = 2000 embed_size = 7000
maxout_pieces = 3 maxout_pieces = 1
subword_features = true subword_features = true
dropout = ${training:dropout} dropout = ${training:dropout}