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transe-freebase-graph.yaml
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transe-freebase-graph.yaml
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dataset:
files:
test:
filename: test.del
type: triples
test_small:
filename: test_small.del
type: triples
test_tiny:
filename: test_tiny.del
type: triples
train:
filename: train.del
type: triples
valid:
filename: valid.del
type: triples
valid_small:
filename: valid_small.del
type: triples
valid_tiny:
filename: valid_tiny.del
type: triples
name: freebase
distributed_model:
base_model:
type: transe
entity_ranking:
chunk_size: 25000
class_name: EntityRankingJob
filter_splits:
- train
- valid
filter_with_test: true
eval:
batch_size: 128
split: valid
trace_level: epoch
type: entity_ranking
import:
- transe
- distributed_model
job:
device: cuda
device_pool:
- cuda:2
- cuda:3
- cuda:0
- cuda:1
distributed:
num_eval_workers: 1
num_partitions: 8
num_workers: 8
parameter_server: shared
partition_type: random
repartition_epoch: true
type: train
lookup_embedder:
class_name: LookupEmbedder
dim: 128
dropout: 0.0
initialize: xavier_normal_
initialize_args:
normal_:
mean: 0.0
std: 0.2778845470712436
uniform_:
a: -0.9172088051222935
xavier_normal_:
gain: 1.0
xavier_uniform_:
gain: 1.0
normalize:
p: -1.0
pretrain:
ensure_all: false
model_filename: ''
regularize: lp
regularize_args:
p: 3
weighted: true
regularize_weight: 0.0
sparse: true
model: distributed_model
negative_sampling:
class_name: TrainingJobNegativeSampling
implementation: batch
num_samples:
o: 921
p: 0
s: 425
sampling_type: uniform
shared: true
shared_type: default
with_replacement: false
train:
abort_on_nan: true
auto_correct: true
batch_size: 1024
loss: kl
loss_arg: 1.0
max_epochs: 10
num_workers: 4
optimizer:
default:
args:
lr: 0.04559698653015022
type: dist_rowadagrad
split: train
trace_level: epoch
type: distributed_negative_sampling
transe:
class_name: TransE
entity_embedder:
dropout: -0.29689234325882474
regularize_weight: 1.7109965436805706e-14
type: lookup_embedder
l_norm: 1.0
relation_embedder:
dropout: -0.15504653706540428
regularize_weight: 3.1643574613799776e-13
type: lookup_embedder
valid:
early_stopping:
patience: 0
threshold:
epochs: 0
metric_value: 0.0
every: 1
metric: mean_reciprocal_rank_filtered
split: valid_tiny
trace_level: epoch