"""
We use following lines because we are running on Google Colab
If you are running notebook on a local computer, you don't need these
"""
from google.colab import drive
drive.mount('/content/gdrive')
import os
os.chdir('/content/gdrive/My Drive/finch/tensorflow2/knowledge_graph_completion/wn18/main')
Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount("/content/gdrive", force_remount=True).
!pip install tensorflow-gpu==2.0.0-rc0
Requirement already satisfied: tensorflow-gpu==2.0.0-rc0 in /usr/local/lib/python3.6/dist-packages (2.0.0rc0) Requirement already satisfied: tb-nightly<1.15.0a20190807,>=1.15.0a20190806 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.15.0a20190806) Requirement already satisfied: termcolor>=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.1.0) Requirement already satisfied: protobuf>=3.6.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (3.7.1) Requirement already satisfied: six>=1.10.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.12.0) Requirement already satisfied: tf-estimator-nightly<1.14.0.dev2019080602,>=1.14.0.dev2019080601 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.14.0.dev2019080601) Requirement already satisfied: wrapt>=1.11.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.11.2) Requirement already satisfied: keras-preprocessing>=1.0.5 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.1.0) Requirement already satisfied: numpy<2.0,>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.16.5) Requirement already satisfied: absl-py>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (0.8.0) Requirement already satisfied: grpcio>=1.8.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.15.0) Requirement already satisfied: gast>=0.2.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (0.2.2) Requirement already satisfied: astor>=0.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (0.8.0) Requirement already satisfied: google-pasta>=0.1.6 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (0.1.7) Requirement already satisfied: keras-applications>=1.0.8 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (1.0.8) Requirement already satisfied: opt-einsum>=2.3.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (3.0.1) Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.6/dist-packages (from tensorflow-gpu==2.0.0-rc0) (0.33.6) Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.15.0a20190807,>=1.15.0a20190806->tensorflow-gpu==2.0.0-rc0) (3.1.1) Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.15.0a20190807,>=1.15.0a20190806->tensorflow-gpu==2.0.0-rc0) (41.2.0) Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<1.15.0a20190807,>=1.15.0a20190806->tensorflow-gpu==2.0.0-rc0) (0.15.5) Requirement already satisfied: h5py in /usr/local/lib/python3.6/dist-packages (from keras-applications>=1.0.8->tensorflow-gpu==2.0.0-rc0) (2.8.0)
import tensorflow as tf
import pprint
import logging
import time
print("TensorFlow Version", tf.__version__)
print('GPU Enabled:', tf.test.is_gpu_available())
TensorFlow Version 2.0.0-rc0 GPU Enabled: True
def get_vocab(f_path):
word2idx = {}
with open(f_path) as f:
for i, line in enumerate(f):
line = line.rstrip()
word2idx[line] = i
return word2idx
"""
we use 1vN fast evaluation as purposed in ConvE paper:
"https://arxiv.org/abs/1707.01476"
sp2o is a dictionary that maps a pair of <subject, predicate>
to multiple possible corresponding <objects> in graph
"""
def make_sp2o(f_paths, e2idx, r2idx):
sp2o = {}
for f_path in f_paths:
with open(f_path) as f:
for line in f:
line = line.rstrip()
s, p, o = line.split()
s, p, o = e2idx[s], r2idx[p], e2idx[o]
if (s,p) not in sp2o:
sp2o[(s,p)] = [o]
else:
if o not in sp2o[(s,p)]:
sp2o[(s,p)].append(o)
return sp2o
def map_fn(x, y):
i, v, s = y[0]
one_hot = tf.SparseTensor(i, v, s)
return x, (one_hot, y[1], y[2])
# stream data from text files
def data_generator(f_path, params, sp2o):
with open(f_path) as f:
print('Reading', f_path)
for line in f:
line = line.rstrip()
s, p, o = line.split()
s, p, o = params['e2idx'][s], params['r2idx'][p], params['e2idx'][o]
sparse_i = [[x] for x in sp2o[(s, p)]]
sparse_v = [1.] * len(sparse_i)
sparse_s = [len(params['e2idx'])]
yield ((s, p), ((sparse_i, sparse_v, sparse_s), o, len(sparse_i)))
def dataset(is_training, params, sp2o):
_shapes = (([], []), (([None, 1], [None], [1]), [], []))
_types = ((tf.int32, tf.int32),
((tf.int64, tf.float32, tf.int64), tf.int32, tf.int32))
if is_training:
ds = tf.data.Dataset.from_generator(
lambda: data_generator(params['train_path'], params, sp2o),
output_shapes = _shapes,
output_types = _types,)
ds = ds.shuffle(params['num_samples'])
ds = ds.map(map_fn)
ds = ds.batch(params['batch_size'])
else:
ds = tf.data.Dataset.from_generator(
lambda: data_generator(params['test_path'], params, sp2o),
output_shapes = _shapes,
output_types = _types,)
ds = ds.map(map_fn)
ds = ds.batch(params['batch_size'])
return ds
def update_metrics(scores, query, metrics):
to_float = lambda x: tf.cast(x, tf.float32)
_, i = tf.math.top_k(scores, sorted=True, k=scores.shape[1])
query = tf.expand_dims(query, 1)
is_query = to_float(tf.equal(i, query))
r = tf.argmax(is_query, -1) + 1
mrr = 1. / to_float(r)
hits_10 = to_float(tf.less_equal(r, 10))
hits_3 = to_float(tf.less_equal(r, 3))
hits_1 = to_float(tf.less_equal(r, 1))
metrics['mrr'].update_state(mrr)
metrics['hits_10'].update_state(hits_10)
metrics['hits_3'].update_state(hits_3)
metrics['hits_1'].update_state(hits_1)
class TuckER(tf.keras.Model):
def __init__(self, params):
super().__init__()
self.embed_ent = tf.keras.layers.Embedding(input_dim=len(params['e2idx']),
output_dim=params['ent_embed_dim'],
name='Entity',
embeddings_initializer=tf.initializers.GlorotNormal())
self.embed_rel = tf.keras.layers.Embedding(input_dim=len(params['r2idx']),
output_dim=params['rel_embed_dim'],
name='Relation',
embeddings_initializer=tf.initializers.GlorotNormal())
self.kernel = self.add_weight(name='Kernel', shape=(
params['rel_embed_dim'],
params['ent_embed_dim'],
params['ent_embed_dim'],), initializer=tf.initializers.RandomUniform(-1., 1.))
self.out_bias = self.add_weight(name='out_bias', shape=[len(params['e2idx'])])
def call(self, inputs, training):
s, p = inputs
batch_sz = tf.shape(s)[0]
s = self.embed_ent(s)
p = self.embed_rel(p)
kernel = tf.matmul(p, tf.reshape(self.kernel, (params['rel_embed_dim'], -1)))
kernel = tf.reshape(kernel, (batch_sz, params['ent_embed_dim'], params['ent_embed_dim']))
x = tf.matmul(tf.expand_dims(s, 1), kernel)
x = tf.squeeze(x, 1)
x = tf.matmul(x, self.embed_ent.embeddings, transpose_b=True)
x = tf.nn.bias_add(x, self.out_bias)
return x
def label_smoothing(inputs, epsilon):
V = inputs.get_shape().as_list()[-1]
return ((1-epsilon) * inputs) + (epsilon / V)
params = {
'train_path': '../data/wn18/train.txt',
'valid_path': '../data/wn18/valid.txt',
'test_path': '../data/wn18/test.txt',
'entity_path': '../vocab/entity.txt',
'relation_path': '../vocab/relation.txt',
'batch_size': 128,
'ent_embed_dim': 200,
'rel_embed_dim': 30,
'dropout_rate': 0.2,
'epsilon': 0.1,
'num_samples': 141442,
'lr': 3e-3,
'num_patience': 5,
}
params['e2idx'] = get_vocab(params['entity_path'])
params['r2idx'] = get_vocab(params['relation_path'])
sp2o_tr = make_sp2o([params['train_path']], params['e2idx'], params['r2idx'])
sp2o_all = make_sp2o([params['train_path'],
params['test_path'],
params['valid_path']], params['e2idx'], params['r2idx'])
def is_descending(history: list):
history = history[-(params['num_patience']+1):]
for i in range(1, len(history)):
if history[i-1] <= history[i]:
return False
return True
model = TuckER(params)
model.build(input_shape=[[None], [None]])
pprint.pprint([(v.name, v.shape) for v in model.trainable_variables])
decay_lr = tf.optimizers.schedules.ExponentialDecay(params['lr'], 1000, 0.95)
optim = tf.optimizers.Adam(params['lr'])
global_step = 0
best_mrr = 0.
history_mrr = []
t0 = time.time()
logger = logging.getLogger('tensorflow')
logger.setLevel(logging.INFO)
while True:
# TRAINING
for ((s, p), (multi_o, o, num_pos)) in dataset(is_training=True, params=params, sp2o=sp2o_tr):
with tf.GradientTape() as tape:
logits = model((s, p), training=True)
multi_o = tf.sparse.to_dense(multi_o, validate_indices=False)
num_neg = len(params['e2idx']) - num_pos
pos_weight = tf.expand_dims(tf.cast(num_neg/num_pos, tf.float32), 1)
labels = label_smoothing(multi_o, params['epsilon'])
loss = tf.nn.weighted_cross_entropy_with_logits(labels=labels, logits=logits, pos_weight=pos_weight)
loss = tf.reduce_mean(loss)
optim.lr.assign(decay_lr(global_step))
grads = tape.gradient(loss, model.trainable_variables)
optim.apply_gradients(zip(grads, model.trainable_variables))
if global_step % 50 == 0:
logger.info("Step {} | Loss: {:.4f} | Spent: {:.1f} secs | LR: {:.6f}".format(
global_step, loss.numpy().item(), time.time()-t0, optim.lr.numpy().item()))
t0 = time.time()
global_step += 1
# EVALUATION
metrics = {
'mrr': tf.metrics.Mean(),
'hits_10': tf.metrics.Mean(),
'hits_3': tf.metrics.Mean(),
'hits_1': tf.metrics.Mean(),
}
for ((s, p), (multi_o, o, num_pos)) in dataset(is_training=False, params=params, sp2o=sp2o_all):
logits = model((s, p), training=False)
multi_o = tf.sparse.to_dense(multi_o, validate_indices=False)
# create masks for Filtered MRR
o_one_hot = tf.one_hot(o, len(params['e2idx']))
unwanted = multi_o - o_one_hot
masks = tf.cast(tf.equal(unwanted, 0.), tf.float32)
scores = tf.sigmoid(logits) * masks
update_metrics(scores=scores, query=o, metrics=metrics)
logger.info("MRR: {:.3f}| [email protected]: {:.3f} | [email protected]: {:.3f} | [email protected]: {:.3f}".format(
metrics['mrr'].result().numpy(),
metrics['hits_10'].result().numpy(),
metrics['hits_3'].result().numpy(),
metrics['hits_1'].result().numpy()))
mrr = metrics['mrr'].result().numpy()
history_mrr.append(mrr)
if mrr > best_mrr:
best_mrr = mrr
# you can save model here
logger.info("Best MRR: {:.3f}".format(best_mrr))
if len(history_mrr) > params['num_patience'] and is_descending(history_mrr):
logger.info("MRR not improved over {} epochs, Early Stop".format(params['num_patience']))
break
[('Entity/embeddings:0', TensorShape([40943, 200])),
('Relation/embeddings:0', TensorShape([18, 30])),
('Kernel:0', TensorShape([30, 200, 200])),
('out_bias:0', TensorShape([40943]))]
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 0 | Loss: 1.3578 | Spent: 40.8 secs | LR: 0.003000
INFO:tensorflow:Step 50 | Loss: 1.2660 | Spent: 6.1 secs | LR: 0.002992
INFO:tensorflow:Step 100 | Loss: 1.0760 | Spent: 6.1 secs | LR: 0.002985
INFO:tensorflow:Step 150 | Loss: 0.9441 | Spent: 6.1 secs | LR: 0.002977
INFO:tensorflow:Step 200 | Loss: 0.9402 | Spent: 6.1 secs | LR: 0.002969
INFO:tensorflow:Step 250 | Loss: 0.9223 | Spent: 6.1 secs | LR: 0.002962
INFO:tensorflow:Step 300 | Loss: 0.8466 | Spent: 6.1 secs | LR: 0.002954
INFO:tensorflow:Step 350 | Loss: 0.8190 | Spent: 6.1 secs | LR: 0.002947
INFO:tensorflow:Step 400 | Loss: 0.7661 | Spent: 6.0 secs | LR: 0.002939
INFO:tensorflow:Step 450 | Loss: 0.7363 | Spent: 6.1 secs | LR: 0.002932
INFO:tensorflow:Step 500 | Loss: 0.6601 | Spent: 6.1 secs | LR: 0.002924
INFO:tensorflow:Step 550 | Loss: 0.5990 | Spent: 6.1 secs | LR: 0.002917
INFO:tensorflow:Step 600 | Loss: 0.5157 | Spent: 6.2 secs | LR: 0.002909
INFO:tensorflow:Step 650 | Loss: 0.5552 | Spent: 6.1 secs | LR: 0.002902
INFO:tensorflow:Step 700 | Loss: 0.5835 | Spent: 6.2 secs | LR: 0.002894
INFO:tensorflow:Step 750 | Loss: 0.5851 | Spent: 6.1 secs | LR: 0.002887
INFO:tensorflow:Step 800 | Loss: 0.4814 | Spent: 6.1 secs | LR: 0.002879
INFO:tensorflow:Step 850 | Loss: 0.5678 | Spent: 6.1 secs | LR: 0.002872
INFO:tensorflow:Step 900 | Loss: 0.4455 | Spent: 6.0 secs | LR: 0.002865
INFO:tensorflow:Step 950 | Loss: 0.5244 | Spent: 6.1 secs | LR: 0.002857
INFO:tensorflow:Step 1000 | Loss: 0.4812 | Spent: 6.1 secs | LR: 0.002850
INFO:tensorflow:Step 1050 | Loss: 0.3892 | Spent: 6.2 secs | LR: 0.002843
INFO:tensorflow:Step 1100 | Loss: 0.3839 | Spent: 6.1 secs | LR: 0.002835
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.341| [email protected]: 0.481 | [email protected]: 0.372 | [email protected]: 0.268
INFO:tensorflow:Best MRR: 0.341
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 1150 | Loss: 0.2982 | Spent: 50.3 secs | LR: 0.002828
INFO:tensorflow:Step 1200 | Loss: 0.3151 | Spent: 6.0 secs | LR: 0.002821
INFO:tensorflow:Step 1250 | Loss: 0.3051 | Spent: 5.9 secs | LR: 0.002814
INFO:tensorflow:Step 1300 | Loss: 0.3200 | Spent: 6.0 secs | LR: 0.002806
INFO:tensorflow:Step 1350 | Loss: 0.2872 | Spent: 5.9 secs | LR: 0.002799
INFO:tensorflow:Step 1400 | Loss: 0.2790 | Spent: 5.8 secs | LR: 0.002792
INFO:tensorflow:Step 1450 | Loss: 0.2661 | Spent: 6.1 secs | LR: 0.002785
INFO:tensorflow:Step 1500 | Loss: 0.3317 | Spent: 6.0 secs | LR: 0.002778
INFO:tensorflow:Step 1550 | Loss: 0.3176 | Spent: 6.0 secs | LR: 0.002771
INFO:tensorflow:Step 1600 | Loss: 0.2637 | Spent: 6.1 secs | LR: 0.002764
INFO:tensorflow:Step 1650 | Loss: 0.2813 | Spent: 6.1 secs | LR: 0.002757
INFO:tensorflow:Step 1700 | Loss: 0.2768 | Spent: 6.1 secs | LR: 0.002749
INFO:tensorflow:Step 1750 | Loss: 0.2976 | Spent: 6.1 secs | LR: 0.002742
INFO:tensorflow:Step 1800 | Loss: 0.2916 | Spent: 6.1 secs | LR: 0.002735
INFO:tensorflow:Step 1850 | Loss: 0.2830 | Spent: 6.0 secs | LR: 0.002728
INFO:tensorflow:Step 1900 | Loss: 0.2463 | Spent: 6.0 secs | LR: 0.002721
INFO:tensorflow:Step 1950 | Loss: 0.2848 | Spent: 6.1 secs | LR: 0.002714
INFO:tensorflow:Step 2000 | Loss: 0.2674 | Spent: 6.1 secs | LR: 0.002707
INFO:tensorflow:Step 2050 | Loss: 0.2589 | Spent: 6.1 secs | LR: 0.002701
INFO:tensorflow:Step 2100 | Loss: 0.2775 | Spent: 6.1 secs | LR: 0.002694
INFO:tensorflow:Step 2150 | Loss: 0.2441 | Spent: 6.1 secs | LR: 0.002687
INFO:tensorflow:Step 2200 | Loss: 0.2660 | Spent: 6.0 secs | LR: 0.002680
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.570| [email protected]: 0.720 | [email protected]: 0.620 | [email protected]: 0.487
INFO:tensorflow:Best MRR: 0.570
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 2250 | Loss: 0.2376 | Spent: 50.1 secs | LR: 0.002673
INFO:tensorflow:Step 2300 | Loss: 0.2332 | Spent: 6.1 secs | LR: 0.002666
INFO:tensorflow:Step 2350 | Loss: 0.2705 | Spent: 6.0 secs | LR: 0.002659
INFO:tensorflow:Step 2400 | Loss: 0.2569 | Spent: 6.1 secs | LR: 0.002653
INFO:tensorflow:Step 2450 | Loss: 0.2524 | Spent: 6.1 secs | LR: 0.002646
INFO:tensorflow:Step 2500 | Loss: 0.2529 | Spent: 6.1 secs | LR: 0.002639
INFO:tensorflow:Step 2550 | Loss: 0.2281 | Spent: 6.1 secs | LR: 0.002632
INFO:tensorflow:Step 2600 | Loss: 0.2584 | Spent: 6.1 secs | LR: 0.002625
INFO:tensorflow:Step 2650 | Loss: 0.2311 | Spent: 6.0 secs | LR: 0.002619
INFO:tensorflow:Step 2700 | Loss: 0.2261 | Spent: 6.1 secs | LR: 0.002612
INFO:tensorflow:Step 2750 | Loss: 0.2428 | Spent: 6.1 secs | LR: 0.002605
INFO:tensorflow:Step 2800 | Loss: 0.2585 | Spent: 6.1 secs | LR: 0.002599
INFO:tensorflow:Step 2850 | Loss: 0.2441 | Spent: 6.1 secs | LR: 0.002592
INFO:tensorflow:Step 2900 | Loss: 0.2456 | Spent: 6.1 secs | LR: 0.002585
INFO:tensorflow:Step 2950 | Loss: 0.2374 | Spent: 6.1 secs | LR: 0.002579
INFO:tensorflow:Step 3000 | Loss: 0.2485 | Spent: 6.0 secs | LR: 0.002572
INFO:tensorflow:Step 3050 | Loss: 0.2543 | Spent: 6.1 secs | LR: 0.002566
INFO:tensorflow:Step 3100 | Loss: 0.2476 | Spent: 6.0 secs | LR: 0.002559
INFO:tensorflow:Step 3150 | Loss: 0.2532 | Spent: 6.1 secs | LR: 0.002552
INFO:tensorflow:Step 3200 | Loss: 0.2466 | Spent: 6.1 secs | LR: 0.002546
INFO:tensorflow:Step 3250 | Loss: 0.2535 | Spent: 6.1 secs | LR: 0.002539
INFO:tensorflow:Step 3300 | Loss: 0.2467 | Spent: 6.1 secs | LR: 0.002533
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.699| [email protected]: 0.809 | [email protected]: 0.741 | [email protected]: 0.635
INFO:tensorflow:Best MRR: 0.699
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 3350 | Loss: 0.2419 | Spent: 50.4 secs | LR: 0.002526
INFO:tensorflow:Step 3400 | Loss: 0.2313 | Spent: 6.1 secs | LR: 0.002520
INFO:tensorflow:Step 3450 | Loss: 0.2326 | Spent: 6.0 secs | LR: 0.002513
INFO:tensorflow:Step 3500 | Loss: 0.2629 | Spent: 6.0 secs | LR: 0.002507
INFO:tensorflow:Step 3550 | Loss: 0.2246 | Spent: 6.0 secs | LR: 0.002501
INFO:tensorflow:Step 3600 | Loss: 0.2503 | Spent: 6.0 secs | LR: 0.002494
INFO:tensorflow:Step 3650 | Loss: 0.2333 | Spent: 6.1 secs | LR: 0.002488
INFO:tensorflow:Step 3700 | Loss: 0.2368 | Spent: 6.1 secs | LR: 0.002481
INFO:tensorflow:Step 3750 | Loss: 0.2554 | Spent: 6.1 secs | LR: 0.002475
INFO:tensorflow:Step 3800 | Loss: 0.2311 | Spent: 6.1 secs | LR: 0.002469
INFO:tensorflow:Step 3850 | Loss: 0.2495 | Spent: 6.1 secs | LR: 0.002462
INFO:tensorflow:Step 3900 | Loss: 0.2562 | Spent: 6.1 secs | LR: 0.002456
INFO:tensorflow:Step 3950 | Loss: 0.2408 | Spent: 6.0 secs | LR: 0.002450
INFO:tensorflow:Step 4000 | Loss: 0.2423 | Spent: 6.1 secs | LR: 0.002444
INFO:tensorflow:Step 4050 | Loss: 0.2439 | Spent: 6.1 secs | LR: 0.002437
INFO:tensorflow:Step 4100 | Loss: 0.2393 | Spent: 6.1 secs | LR: 0.002431
INFO:tensorflow:Step 4150 | Loss: 0.2377 | Spent: 6.2 secs | LR: 0.002425
INFO:tensorflow:Step 4200 | Loss: 0.2402 | Spent: 6.0 secs | LR: 0.002419
INFO:tensorflow:Step 4250 | Loss: 0.2566 | Spent: 6.1 secs | LR: 0.002412
INFO:tensorflow:Step 4300 | Loss: 0.2504 | Spent: 6.0 secs | LR: 0.002406
INFO:tensorflow:Step 4350 | Loss: 0.2645 | Spent: 6.1 secs | LR: 0.002400
INFO:tensorflow:Step 4400 | Loss: 0.2536 | Spent: 6.0 secs | LR: 0.002394
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.744| [email protected]: 0.838 | [email protected]: 0.775 | [email protected]: 0.692
INFO:tensorflow:Best MRR: 0.744
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 4450 | Loss: 0.2312 | Spent: 51.5 secs | LR: 0.002388
INFO:tensorflow:Step 4500 | Loss: 0.2406 | Spent: 6.1 secs | LR: 0.002382
INFO:tensorflow:Step 4550 | Loss: 0.2428 | Spent: 6.1 secs | LR: 0.002376
INFO:tensorflow:Step 4600 | Loss: 0.2492 | Spent: 6.1 secs | LR: 0.002369
INFO:tensorflow:Step 4650 | Loss: 0.2540 | Spent: 6.1 secs | LR: 0.002363
INFO:tensorflow:Step 4700 | Loss: 0.2622 | Spent: 6.0 secs | LR: 0.002357
INFO:tensorflow:Step 4750 | Loss: 0.2290 | Spent: 6.0 secs | LR: 0.002351
INFO:tensorflow:Step 4800 | Loss: 0.2542 | Spent: 6.0 secs | LR: 0.002345
INFO:tensorflow:Step 4850 | Loss: 0.2533 | Spent: 6.1 secs | LR: 0.002339
INFO:tensorflow:Step 4900 | Loss: 0.2282 | Spent: 6.1 secs | LR: 0.002333
INFO:tensorflow:Step 4950 | Loss: 0.2493 | Spent: 6.1 secs | LR: 0.002327
INFO:tensorflow:Step 5000 | Loss: 0.2452 | Spent: 6.0 secs | LR: 0.002321
INFO:tensorflow:Step 5050 | Loss: 0.2394 | Spent: 6.1 secs | LR: 0.002315
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INFO:tensorflow:Step 5500 | Loss: 0.2581 | Spent: 6.1 secs | LR: 0.002263
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.765| [email protected]: 0.858 | [email protected]: 0.794 | [email protected]: 0.714
INFO:tensorflow:Best MRR: 0.765
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 5550 | Loss: 0.2434 | Spent: 50.6 secs | LR: 0.002257
INFO:tensorflow:Step 5600 | Loss: 0.2524 | Spent: 6.0 secs | LR: 0.002251
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INFO:tensorflow:Step 6600 | Loss: 0.2343 | Spent: 6.2 secs | LR: 0.002138
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.785| [email protected]: 0.869 | [email protected]: 0.815 | [email protected]: 0.738
INFO:tensorflow:Best MRR: 0.785
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 6650 | Loss: 0.2216 | Spent: 50.4 secs | LR: 0.002133
INFO:tensorflow:Step 6700 | Loss: 0.2446 | Spent: 6.0 secs | LR: 0.002127
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INFO:tensorflow:Step 7700 | Loss: 0.2461 | Spent: 6.0 secs | LR: 0.002021
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.803| [email protected]: 0.884 | [email protected]: 0.837 | [email protected]: 0.757
INFO:tensorflow:Best MRR: 0.803
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 7750 | Loss: 0.2299 | Spent: 49.9 secs | LR: 0.002016
INFO:tensorflow:Step 7800 | Loss: 0.2478 | Spent: 5.9 secs | LR: 0.002011
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INFO:tensorflow:Step 8800 | Loss: 0.2317 | Spent: 6.2 secs | LR: 0.001910
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.815| [email protected]: 0.893 | [email protected]: 0.848 | [email protected]: 0.769
INFO:tensorflow:Best MRR: 0.815
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 8850 | Loss: 0.2531 | Spent: 50.0 secs | LR: 0.001905
INFO:tensorflow:Step 8900 | Loss: 0.2454 | Spent: 6.1 secs | LR: 0.001900
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INFO:tensorflow:Step 9950 | Loss: 0.2360 | Spent: 6.1 secs | LR: 0.001801
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.836| [email protected]: 0.904 | [email protected]: 0.864 | [email protected]: 0.796
INFO:tensorflow:Best MRR: 0.836
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 10000 | Loss: 0.2399 | Spent: 49.7 secs | LR: 0.001796
INFO:tensorflow:Step 10050 | Loss: 0.2470 | Spent: 5.8 secs | LR: 0.001792
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Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.846| [email protected]: 0.910 | [email protected]: 0.875 | [email protected]: 0.807
INFO:tensorflow:Best MRR: 0.846
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 11100 | Loss: 0.2430 | Spent: 49.9 secs | LR: 0.001698
INFO:tensorflow:Step 11150 | Loss: 0.2404 | Spent: 6.1 secs | LR: 0.001693
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INFO:tensorflow:Step 12150 | Loss: 0.2221 | Spent: 6.1 secs | LR: 0.001609
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.851| [email protected]: 0.915 | [email protected]: 0.879 | [email protected]: 0.813
INFO:tensorflow:Best MRR: 0.851
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 12200 | Loss: 0.2359 | Spent: 52.0 secs | LR: 0.001605
INFO:tensorflow:Step 12250 | Loss: 0.2326 | Spent: 5.9 secs | LR: 0.001600
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INFO:tensorflow:Step 12600 | Loss: 0.2343 | Spent: 6.2 secs | LR: 0.001572
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INFO:tensorflow:Step 13250 | Loss: 0.2437 | Spent: 6.1 secs | LR: 0.001520
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.855| [email protected]: 0.921 | [email protected]: 0.882 | [email protected]: 0.816
INFO:tensorflow:Best MRR: 0.855
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 13300 | Loss: 0.2324 | Spent: 50.3 secs | LR: 0.001517
INFO:tensorflow:Step 13350 | Loss: 0.2276 | Spent: 6.1 secs | LR: 0.001513
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INFO:tensorflow:Step 14350 | Loss: 0.2467 | Spent: 6.2 secs | LR: 0.001437
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.859| [email protected]: 0.922 | [email protected]: 0.887 | [email protected]: 0.821
INFO:tensorflow:Best MRR: 0.859
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 14400 | Loss: 0.2265 | Spent: 49.7 secs | LR: 0.001433
INFO:tensorflow:Step 14450 | Loss: 0.2158 | Spent: 5.9 secs | LR: 0.001430
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INFO:tensorflow:Step 14900 | Loss: 0.2444 | Spent: 6.1 secs | LR: 0.001397
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INFO:tensorflow:Step 15000 | Loss: 0.2411 | Spent: 6.1 secs | LR: 0.001390
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INFO:tensorflow:Step 15200 | Loss: 0.2283 | Spent: 6.0 secs | LR: 0.001376
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INFO:tensorflow:Step 15300 | Loss: 0.2144 | Spent: 6.1 secs | LR: 0.001369
INFO:tensorflow:Step 15350 | Loss: 0.2334 | Spent: 6.1 secs | LR: 0.001365
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INFO:tensorflow:Step 15450 | Loss: 0.2270 | Spent: 6.1 secs | LR: 0.001358
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.865| [email protected]: 0.924 | [email protected]: 0.890 | [email protected]: 0.829
INFO:tensorflow:Best MRR: 0.865
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 15500 | Loss: 0.2146 | Spent: 51.1 secs | LR: 0.001355
INFO:tensorflow:Step 15550 | Loss: 0.2523 | Spent: 6.2 secs | LR: 0.001351
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INFO:tensorflow:Step 15900 | Loss: 0.2290 | Spent: 6.1 secs | LR: 0.001327
INFO:tensorflow:Step 15950 | Loss: 0.2412 | Spent: 6.0 secs | LR: 0.001324
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INFO:tensorflow:Step 16150 | Loss: 0.2400 | Spent: 6.1 secs | LR: 0.001310
INFO:tensorflow:Step 16200 | Loss: 0.2288 | Spent: 6.1 secs | LR: 0.001307
INFO:tensorflow:Step 16250 | Loss: 0.2355 | Spent: 6.1 secs | LR: 0.001304
INFO:tensorflow:Step 16300 | Loss: 0.2342 | Spent: 6.0 secs | LR: 0.001300
INFO:tensorflow:Step 16350 | Loss: 0.2201 | Spent: 6.0 secs | LR: 0.001297
INFO:tensorflow:Step 16400 | Loss: 0.2575 | Spent: 6.0 secs | LR: 0.001294
INFO:tensorflow:Step 16450 | Loss: 0.2414 | Spent: 6.0 secs | LR: 0.001290
INFO:tensorflow:Step 16500 | Loss: 0.2255 | Spent: 6.2 secs | LR: 0.001287
INFO:tensorflow:Step 16550 | Loss: 0.2365 | Spent: 6.1 secs | LR: 0.001284
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.867| [email protected]: 0.929 | [email protected]: 0.897 | [email protected]: 0.830
INFO:tensorflow:Best MRR: 0.867
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 16600 | Loss: 0.2249 | Spent: 49.6 secs | LR: 0.001280
INFO:tensorflow:Step 16650 | Loss: 0.2196 | Spent: 6.0 secs | LR: 0.001277
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INFO:tensorflow:Step 16750 | Loss: 0.2130 | Spent: 6.0 secs | LR: 0.001271
INFO:tensorflow:Step 16800 | Loss: 0.2333 | Spent: 6.2 secs | LR: 0.001267
INFO:tensorflow:Step 16850 | Loss: 0.2456 | Spent: 6.1 secs | LR: 0.001264
INFO:tensorflow:Step 16900 | Loss: 0.2426 | Spent: 6.0 secs | LR: 0.001261
INFO:tensorflow:Step 16950 | Loss: 0.2309 | Spent: 6.1 secs | LR: 0.001258
INFO:tensorflow:Step 17000 | Loss: 0.2453 | Spent: 6.0 secs | LR: 0.001254
INFO:tensorflow:Step 17050 | Loss: 0.2450 | Spent: 6.1 secs | LR: 0.001251
INFO:tensorflow:Step 17100 | Loss: 0.2315 | Spent: 6.1 secs | LR: 0.001248
INFO:tensorflow:Step 17150 | Loss: 0.2287 | Spent: 6.1 secs | LR: 0.001245
INFO:tensorflow:Step 17200 | Loss: 0.2347 | Spent: 6.1 secs | LR: 0.001242
INFO:tensorflow:Step 17250 | Loss: 0.2326 | Spent: 6.1 secs | LR: 0.001238
INFO:tensorflow:Step 17300 | Loss: 0.2361 | Spent: 6.1 secs | LR: 0.001235
INFO:tensorflow:Step 17350 | Loss: 0.2315 | Spent: 6.1 secs | LR: 0.001232
INFO:tensorflow:Step 17400 | Loss: 0.2542 | Spent: 6.1 secs | LR: 0.001229
INFO:tensorflow:Step 17450 | Loss: 0.2234 | Spent: 6.0 secs | LR: 0.001226
INFO:tensorflow:Step 17500 | Loss: 0.2223 | Spent: 6.2 secs | LR: 0.001223
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INFO:tensorflow:Step 17600 | Loss: 0.2271 | Spent: 6.1 secs | LR: 0.001216
INFO:tensorflow:Step 17650 | Loss: 0.2448 | Spent: 6.1 secs | LR: 0.001213
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.866| [email protected]: 0.930 | [email protected]: 0.894 | [email protected]: 0.829
INFO:tensorflow:Best MRR: 0.867
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 17700 | Loss: 0.2334 | Spent: 50.7 secs | LR: 0.001210
INFO:tensorflow:Step 17750 | Loss: 0.2204 | Spent: 6.1 secs | LR: 0.001207
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INFO:tensorflow:Step 17850 | Loss: 0.2287 | Spent: 6.2 secs | LR: 0.001201
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INFO:tensorflow:Step 18000 | Loss: 0.2400 | Spent: 6.0 secs | LR: 0.001192
INFO:tensorflow:Step 18050 | Loss: 0.2447 | Spent: 6.0 secs | LR: 0.001189
INFO:tensorflow:Step 18100 | Loss: 0.2366 | Spent: 6.1 secs | LR: 0.001186
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INFO:tensorflow:Step 18200 | Loss: 0.2431 | Spent: 6.1 secs | LR: 0.001179
INFO:tensorflow:Step 18250 | Loss: 0.2188 | Spent: 6.0 secs | LR: 0.001176
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INFO:tensorflow:Step 18400 | Loss: 0.2218 | Spent: 6.1 secs | LR: 0.001167
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INFO:tensorflow:Step 18500 | Loss: 0.2379 | Spent: 6.1 secs | LR: 0.001161
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INFO:tensorflow:Step 18600 | Loss: 0.2439 | Spent: 6.1 secs | LR: 0.001156
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INFO:tensorflow:Step 18750 | Loss: 0.2257 | Spent: 6.1 secs | LR: 0.001147
INFO:tensorflow:Step 18800 | Loss: 0.2254 | Spent: 6.1 secs | LR: 0.001144
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.868| [email protected]: 0.932 | [email protected]: 0.897 | [email protected]: 0.831
INFO:tensorflow:Best MRR: 0.868
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 18850 | Loss: 0.2291 | Spent: 50.2 secs | LR: 0.001141
INFO:tensorflow:Step 18900 | Loss: 0.2399 | Spent: 6.1 secs | LR: 0.001138
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INFO:tensorflow:Step 19000 | Loss: 0.2347 | Spent: 6.0 secs | LR: 0.001132
INFO:tensorflow:Step 19050 | Loss: 0.2558 | Spent: 6.1 secs | LR: 0.001129
INFO:tensorflow:Step 19100 | Loss: 0.2329 | Spent: 6.1 secs | LR: 0.001126
INFO:tensorflow:Step 19150 | Loss: 0.2238 | Spent: 6.1 secs | LR: 0.001123
INFO:tensorflow:Step 19200 | Loss: 0.2336 | Spent: 6.1 secs | LR: 0.001121
INFO:tensorflow:Step 19250 | Loss: 0.2215 | Spent: 6.1 secs | LR: 0.001118
INFO:tensorflow:Step 19300 | Loss: 0.2403 | Spent: 6.1 secs | LR: 0.001115
INFO:tensorflow:Step 19350 | Loss: 0.2245 | Spent: 6.0 secs | LR: 0.001112
INFO:tensorflow:Step 19400 | Loss: 0.2309 | Spent: 6.1 secs | LR: 0.001109
INFO:tensorflow:Step 19450 | Loss: 0.2438 | Spent: 6.1 secs | LR: 0.001106
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INFO:tensorflow:Step 19750 | Loss: 0.2255 | Spent: 6.1 secs | LR: 0.001089
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INFO:tensorflow:Step 19900 | Loss: 0.2167 | Spent: 6.1 secs | LR: 0.001081
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.869| [email protected]: 0.929 | [email protected]: 0.896 | [email protected]: 0.833
INFO:tensorflow:Best MRR: 0.869
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 19950 | Loss: 0.2277 | Spent: 51.8 secs | LR: 0.001078
INFO:tensorflow:Step 20000 | Loss: 0.2303 | Spent: 6.1 secs | LR: 0.001075
INFO:tensorflow:Step 20050 | Loss: 0.2334 | Spent: 6.1 secs | LR: 0.001073
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INFO:tensorflow:Step 20200 | Loss: 0.2342 | Spent: 6.0 secs | LR: 0.001064
INFO:tensorflow:Step 20250 | Loss: 0.2506 | Spent: 6.1 secs | LR: 0.001062
INFO:tensorflow:Step 20300 | Loss: 0.2409 | Spent: 6.2 secs | LR: 0.001059
INFO:tensorflow:Step 20350 | Loss: 0.2331 | Spent: 6.1 secs | LR: 0.001056
INFO:tensorflow:Step 20400 | Loss: 0.2232 | Spent: 6.2 secs | LR: 0.001054
INFO:tensorflow:Step 20450 | Loss: 0.2309 | Spent: 6.1 secs | LR: 0.001051
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INFO:tensorflow:Step 20600 | Loss: 0.2136 | Spent: 6.1 secs | LR: 0.001043
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INFO:tensorflow:Step 20700 | Loss: 0.2445 | Spent: 6.1 secs | LR: 0.001038
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INFO:tensorflow:Step 20900 | Loss: 0.2255 | Spent: 6.1 secs | LR: 0.001027
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INFO:tensorflow:Step 21000 | Loss: 0.2329 | Spent: 6.1 secs | LR: 0.001022
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.872| [email protected]: 0.934 | [email protected]: 0.900 | [email protected]: 0.836
INFO:tensorflow:Best MRR: 0.872
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 21050 | Loss: 0.2237 | Spent: 49.2 secs | LR: 0.001019
INFO:tensorflow:Step 21100 | Loss: 0.2433 | Spent: 6.1 secs | LR: 0.001016
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INFO:tensorflow:Step 21450 | Loss: 0.2367 | Spent: 6.0 secs | LR: 0.000998
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INFO:tensorflow:Step 22000 | Loss: 0.2334 | Spent: 6.0 secs | LR: 0.000971
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INFO:tensorflow:Step 22100 | Loss: 0.2070 | Spent: 6.0 secs | LR: 0.000966
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.871| [email protected]: 0.934 | [email protected]: 0.900 | [email protected]: 0.833
INFO:tensorflow:Best MRR: 0.872
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 22150 | Loss: 0.2260 | Spent: 50.6 secs | LR: 0.000963
INFO:tensorflow:Step 22200 | Loss: 0.2437 | Spent: 6.1 secs | LR: 0.000961
INFO:tensorflow:Step 22250 | Loss: 0.2430 | Spent: 6.1 secs | LR: 0.000958
INFO:tensorflow:Step 22300 | Loss: 0.2185 | Spent: 6.0 secs | LR: 0.000956
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INFO:tensorflow:Step 22450 | Loss: 0.2375 | Spent: 6.0 secs | LR: 0.000948
INFO:tensorflow:Step 22500 | Loss: 0.2283 | Spent: 6.0 secs | LR: 0.000946
INFO:tensorflow:Step 22550 | Loss: 0.2333 | Spent: 6.1 secs | LR: 0.000944
INFO:tensorflow:Step 22600 | Loss: 0.2373 | Spent: 6.1 secs | LR: 0.000941
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INFO:tensorflow:Step 22750 | Loss: 0.2227 | Spent: 6.1 secs | LR: 0.000934
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INFO:tensorflow:Step 22900 | Loss: 0.2259 | Spent: 6.1 secs | LR: 0.000927
INFO:tensorflow:Step 22950 | Loss: 0.2346 | Spent: 6.1 secs | LR: 0.000924
INFO:tensorflow:Step 23000 | Loss: 0.2297 | Spent: 6.2 secs | LR: 0.000922
INFO:tensorflow:Step 23050 | Loss: 0.2218 | Spent: 6.0 secs | LR: 0.000920
INFO:tensorflow:Step 23100 | Loss: 0.2297 | Spent: 6.1 secs | LR: 0.000917
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INFO:tensorflow:Step 23200 | Loss: 0.2277 | Spent: 5.9 secs | LR: 0.000913
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.868| [email protected]: 0.931 | [email protected]: 0.900 | [email protected]: 0.829
INFO:tensorflow:Best MRR: 0.872
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 23250 | Loss: 0.2223 | Spent: 49.7 secs | LR: 0.000910
INFO:tensorflow:Step 23300 | Loss: 0.2341 | Spent: 6.1 secs | LR: 0.000908
INFO:tensorflow:Step 23350 | Loss: 0.2343 | Spent: 6.0 secs | LR: 0.000906
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INFO:tensorflow:Step 23550 | Loss: 0.2246 | Spent: 6.1 secs | LR: 0.000896
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INFO:tensorflow:Step 23650 | Loss: 0.2252 | Spent: 6.0 secs | LR: 0.000892
INFO:tensorflow:Step 23700 | Loss: 0.2338 | Spent: 6.1 secs | LR: 0.000890
INFO:tensorflow:Step 23750 | Loss: 0.2191 | Spent: 6.2 secs | LR: 0.000887
INFO:tensorflow:Step 23800 | Loss: 0.2305 | Spent: 6.2 secs | LR: 0.000885
INFO:tensorflow:Step 23850 | Loss: 0.2205 | Spent: 6.2 secs | LR: 0.000883
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INFO:tensorflow:Step 23950 | Loss: 0.2430 | Spent: 6.2 secs | LR: 0.000878
INFO:tensorflow:Step 24000 | Loss: 0.2171 | Spent: 6.1 secs | LR: 0.000876
INFO:tensorflow:Step 24050 | Loss: 0.2239 | Spent: 6.1 secs | LR: 0.000874
INFO:tensorflow:Step 24100 | Loss: 0.2213 | Spent: 6.1 secs | LR: 0.000871
INFO:tensorflow:Step 24150 | Loss: 0.2293 | Spent: 6.1 secs | LR: 0.000869
INFO:tensorflow:Step 24200 | Loss: 0.2303 | Spent: 6.1 secs | LR: 0.000867
INFO:tensorflow:Step 24250 | Loss: 0.2442 | Spent: 6.1 secs | LR: 0.000865
INFO:tensorflow:Step 24300 | Loss: 0.2377 | Spent: 6.1 secs | LR: 0.000863
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.936 | [email protected]: 0.903 | [email protected]: 0.836
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 24350 | Loss: 0.2442 | Spent: 50.8 secs | LR: 0.000860
INFO:tensorflow:Step 24400 | Loss: 0.2388 | Spent: 6.1 secs | LR: 0.000858
INFO:tensorflow:Step 24450 | Loss: 0.2217 | Spent: 6.1 secs | LR: 0.000856
INFO:tensorflow:Step 24500 | Loss: 0.2264 | Spent: 6.1 secs | LR: 0.000854
INFO:tensorflow:Step 24550 | Loss: 0.2067 | Spent: 6.1 secs | LR: 0.000852
INFO:tensorflow:Step 24600 | Loss: 0.2083 | Spent: 6.1 secs | LR: 0.000849
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INFO:tensorflow:Step 24700 | Loss: 0.2258 | Spent: 6.1 secs | LR: 0.000845
INFO:tensorflow:Step 24750 | Loss: 0.2110 | Spent: 6.1 secs | LR: 0.000843
INFO:tensorflow:Step 24800 | Loss: 0.2325 | Spent: 6.2 secs | LR: 0.000841
INFO:tensorflow:Step 24850 | Loss: 0.2254 | Spent: 6.2 secs | LR: 0.000839
INFO:tensorflow:Step 24900 | Loss: 0.2283 | Spent: 6.1 secs | LR: 0.000836
INFO:tensorflow:Step 24950 | Loss: 0.2280 | Spent: 6.0 secs | LR: 0.000834
INFO:tensorflow:Step 25000 | Loss: 0.2321 | Spent: 6.0 secs | LR: 0.000832
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INFO:tensorflow:Step 25100 | Loss: 0.2303 | Spent: 6.0 secs | LR: 0.000828
INFO:tensorflow:Step 25150 | Loss: 0.2374 | Spent: 6.1 secs | LR: 0.000826
INFO:tensorflow:Step 25200 | Loss: 0.2343 | Spent: 6.1 secs | LR: 0.000824
INFO:tensorflow:Step 25250 | Loss: 0.2273 | Spent: 6.1 secs | LR: 0.000822
INFO:tensorflow:Step 25300 | Loss: 0.2180 | Spent: 6.1 secs | LR: 0.000819
INFO:tensorflow:Step 25350 | Loss: 0.2186 | Spent: 6.0 secs | LR: 0.000817
INFO:tensorflow:Step 25400 | Loss: 0.2170 | Spent: 5.9 secs | LR: 0.000815
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.872| [email protected]: 0.933 | [email protected]: 0.901 | [email protected]: 0.835
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 25450 | Loss: 0.2338 | Spent: 50.6 secs | LR: 0.000813
INFO:tensorflow:Step 25500 | Loss: 0.2290 | Spent: 6.1 secs | LR: 0.000811
INFO:tensorflow:Step 25550 | Loss: 0.2245 | Spent: 6.2 secs | LR: 0.000809
INFO:tensorflow:Step 25600 | Loss: 0.2279 | Spent: 6.1 secs | LR: 0.000807
INFO:tensorflow:Step 25650 | Loss: 0.2371 | Spent: 6.0 secs | LR: 0.000805
INFO:tensorflow:Step 25700 | Loss: 0.2404 | Spent: 6.1 secs | LR: 0.000803
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INFO:tensorflow:Step 25850 | Loss: 0.2486 | Spent: 6.1 secs | LR: 0.000797
INFO:tensorflow:Step 25900 | Loss: 0.2400 | Spent: 6.1 secs | LR: 0.000795
INFO:tensorflow:Step 25950 | Loss: 0.2383 | Spent: 6.1 secs | LR: 0.000793
INFO:tensorflow:Step 26000 | Loss: 0.2394 | Spent: 6.1 secs | LR: 0.000791
INFO:tensorflow:Step 26050 | Loss: 0.2210 | Spent: 6.0 secs | LR: 0.000789
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INFO:tensorflow:Step 26200 | Loss: 0.2136 | Spent: 5.9 secs | LR: 0.000782
INFO:tensorflow:Step 26250 | Loss: 0.2391 | Spent: 5.9 secs | LR: 0.000780
INFO:tensorflow:Step 26300 | Loss: 0.2195 | Spent: 5.9 secs | LR: 0.000778
INFO:tensorflow:Step 26350 | Loss: 0.2325 | Spent: 5.9 secs | LR: 0.000776
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INFO:tensorflow:Step 26500 | Loss: 0.2434 | Spent: 6.1 secs | LR: 0.000771
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.937 | [email protected]: 0.905 | [email protected]: 0.834
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 26550 | Loss: 0.2247 | Spent: 50.1 secs | LR: 0.000769
INFO:tensorflow:Step 26600 | Loss: 0.2472 | Spent: 6.0 secs | LR: 0.000767
INFO:tensorflow:Step 26650 | Loss: 0.2208 | Spent: 6.0 secs | LR: 0.000765
INFO:tensorflow:Step 26700 | Loss: 0.2413 | Spent: 6.0 secs | LR: 0.000763
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INFO:tensorflow:Step 27000 | Loss: 0.2449 | Spent: 6.1 secs | LR: 0.000751
INFO:tensorflow:Step 27050 | Loss: 0.2371 | Spent: 6.1 secs | LR: 0.000749
INFO:tensorflow:Step 27100 | Loss: 0.2361 | Spent: 6.1 secs | LR: 0.000747
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INFO:tensorflow:Step 27200 | Loss: 0.2180 | Spent: 6.1 secs | LR: 0.000743
INFO:tensorflow:Step 27250 | Loss: 0.2361 | Spent: 6.0 secs | LR: 0.000741
INFO:tensorflow:Step 27300 | Loss: 0.2380 | Spent: 6.1 secs | LR: 0.000740
INFO:tensorflow:Step 27350 | Loss: 0.2382 | Spent: 6.0 secs | LR: 0.000738
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INFO:tensorflow:Step 27600 | Loss: 0.2367 | Spent: 6.1 secs | LR: 0.000728
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.873| [email protected]: 0.936 | [email protected]: 0.902 | [email protected]: 0.834
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 27650 | Loss: 0.2035 | Spent: 51.1 secs | LR: 0.000726
INFO:tensorflow:Step 27700 | Loss: 0.2281 | Spent: 6.0 secs | LR: 0.000725
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INFO:tensorflow:Step 28750 | Loss: 0.2122 | Spent: 6.1 secs | LR: 0.000687
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.871| [email protected]: 0.936 | [email protected]: 0.902 | [email protected]: 0.831
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 28800 | Loss: 0.2156 | Spent: 50.0 secs | LR: 0.000685
INFO:tensorflow:Step 28850 | Loss: 0.2220 | Spent: 6.1 secs | LR: 0.000683
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INFO:tensorflow:Step 29850 | Loss: 0.2293 | Spent: 6.1 secs | LR: 0.000649
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.873| [email protected]: 0.936 | [email protected]: 0.907 | [email protected]: 0.833
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 29900 | Loss: 0.2276 | Spent: 49.6 secs | LR: 0.000647
INFO:tensorflow:Step 29950 | Loss: 0.2247 | Spent: 6.0 secs | LR: 0.000646
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INFO:tensorflow:Step 30950 | Loss: 0.2244 | Spent: 6.1 secs | LR: 0.000613
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.938 | [email protected]: 0.904 | [email protected]: 0.835
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 31000 | Loss: 0.2448 | Spent: 50.2 secs | LR: 0.000612
INFO:tensorflow:Step 31050 | Loss: 0.2249 | Spent: 6.0 secs | LR: 0.000610
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Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.937 | [email protected]: 0.904 | [email protected]: 0.834
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 32100 | Loss: 0.2229 | Spent: 50.2 secs | LR: 0.000578
INFO:tensorflow:Step 32150 | Loss: 0.2315 | Spent: 6.1 secs | LR: 0.000577
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Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.940 | [email protected]: 0.904 | [email protected]: 0.835
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 33200 | Loss: 0.2456 | Spent: 50.6 secs | LR: 0.000546
INFO:tensorflow:Step 33250 | Loss: 0.2312 | Spent: 6.2 secs | LR: 0.000545
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INFO:tensorflow:Step 34250 | Loss: 0.2143 | Spent: 6.1 secs | LR: 0.000518
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.873| [email protected]: 0.939 | [email protected]: 0.904 | [email protected]: 0.833
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 34300 | Loss: 0.2549 | Spent: 50.4 secs | LR: 0.000516
INFO:tensorflow:Step 34350 | Loss: 0.2253 | Spent: 6.1 secs | LR: 0.000515
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INFO:tensorflow:Step 35150 | Loss: 0.2285 | Spent: 6.0 secs | LR: 0.000494
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INFO:tensorflow:Step 35350 | Loss: 0.2374 | Spent: 6.1 secs | LR: 0.000489
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.940 | [email protected]: 0.907 | [email protected]: 0.835
INFO:tensorflow:Best MRR: 0.874
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 35400 | Loss: 0.2353 | Spent: 51.0 secs | LR: 0.000488
INFO:tensorflow:Step 35450 | Loss: 0.2213 | Spent: 6.1 secs | LR: 0.000487
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INFO:tensorflow:Step 36450 | Loss: 0.2206 | Spent: 6.1 secs | LR: 0.000463
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.876| [email protected]: 0.939 | [email protected]: 0.907 | [email protected]: 0.837
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 36500 | Loss: 0.2302 | Spent: 49.9 secs | LR: 0.000461
INFO:tensorflow:Step 36550 | Loss: 0.2251 | Spent: 6.1 secs | LR: 0.000460
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INFO:tensorflow:Step 37600 | Loss: 0.2164 | Spent: 6.1 secs | LR: 0.000436
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.874| [email protected]: 0.940 | [email protected]: 0.903 | [email protected]: 0.836
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 37650 | Loss: 0.2166 | Spent: 51.0 secs | LR: 0.000435
INFO:tensorflow:Step 37700 | Loss: 0.2215 | Spent: 6.1 secs | LR: 0.000434
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INFO:tensorflow:Step 38350 | Loss: 0.2403 | Spent: 6.1 secs | LR: 0.000420
INFO:tensorflow:Step 38400 | Loss: 0.2438 | Spent: 6.1 secs | LR: 0.000419
INFO:tensorflow:Step 38450 | Loss: 0.2336 | Spent: 6.1 secs | LR: 0.000417
INFO:tensorflow:Step 38500 | Loss: 0.2198 | Spent: 6.1 secs | LR: 0.000416
INFO:tensorflow:Step 38550 | Loss: 0.2190 | Spent: 6.1 secs | LR: 0.000415
INFO:tensorflow:Step 38600 | Loss: 0.2118 | Spent: 6.1 secs | LR: 0.000414
INFO:tensorflow:Step 38650 | Loss: 0.2155 | Spent: 6.0 secs | LR: 0.000413
INFO:tensorflow:Step 38700 | Loss: 0.2041 | Spent: 6.1 secs | LR: 0.000412
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.873| [email protected]: 0.939 | [email protected]: 0.905 | [email protected]: 0.832
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 38750 | Loss: 0.2413 | Spent: 51.2 secs | LR: 0.000411
INFO:tensorflow:Step 38800 | Loss: 0.2048 | Spent: 6.1 secs | LR: 0.000410
INFO:tensorflow:Step 38850 | Loss: 0.2343 | Spent: 6.1 secs | LR: 0.000409
INFO:tensorflow:Step 38900 | Loss: 0.2342 | Spent: 6.0 secs | LR: 0.000408
INFO:tensorflow:Step 38950 | Loss: 0.2265 | Spent: 6.1 secs | LR: 0.000407
INFO:tensorflow:Step 39000 | Loss: 0.2398 | Spent: 6.1 secs | LR: 0.000406
INFO:tensorflow:Step 39050 | Loss: 0.2272 | Spent: 6.0 secs | LR: 0.000405
INFO:tensorflow:Step 39100 | Loss: 0.2043 | Spent: 6.1 secs | LR: 0.000404
INFO:tensorflow:Step 39150 | Loss: 0.2147 | Spent: 6.1 secs | LR: 0.000403
INFO:tensorflow:Step 39200 | Loss: 0.2191 | Spent: 6.1 secs | LR: 0.000402
INFO:tensorflow:Step 39250 | Loss: 0.2327 | Spent: 6.1 secs | LR: 0.000401
INFO:tensorflow:Step 39300 | Loss: 0.2311 | Spent: 6.1 secs | LR: 0.000400
INFO:tensorflow:Step 39350 | Loss: 0.2236 | Spent: 6.1 secs | LR: 0.000399
INFO:tensorflow:Step 39400 | Loss: 0.2343 | Spent: 6.0 secs | LR: 0.000398
INFO:tensorflow:Step 39450 | Loss: 0.2330 | Spent: 6.0 secs | LR: 0.000397
INFO:tensorflow:Step 39500 | Loss: 0.2322 | Spent: 5.9 secs | LR: 0.000396
INFO:tensorflow:Step 39550 | Loss: 0.2386 | Spent: 6.0 secs | LR: 0.000395
INFO:tensorflow:Step 39600 | Loss: 0.2301 | Spent: 6.0 secs | LR: 0.000394
INFO:tensorflow:Step 39650 | Loss: 0.2320 | Spent: 6.0 secs | LR: 0.000393
INFO:tensorflow:Step 39700 | Loss: 0.2287 | Spent: 6.1 secs | LR: 0.000392
INFO:tensorflow:Step 39750 | Loss: 0.2295 | Spent: 6.0 secs | LR: 0.000391
INFO:tensorflow:Step 39800 | Loss: 0.2107 | Spent: 6.2 secs | LR: 0.000390
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.872| [email protected]: 0.939 | [email protected]: 0.904 | [email protected]: 0.831
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 39850 | Loss: 0.2269 | Spent: 50.3 secs | LR: 0.000389
INFO:tensorflow:Step 39900 | Loss: 0.2329 | Spent: 6.1 secs | LR: 0.000388
INFO:tensorflow:Step 39950 | Loss: 0.2206 | Spent: 6.1 secs | LR: 0.000387
INFO:tensorflow:Step 40000 | Loss: 0.2342 | Spent: 6.2 secs | LR: 0.000386
INFO:tensorflow:Step 40050 | Loss: 0.2148 | Spent: 6.1 secs | LR: 0.000385
INFO:tensorflow:Step 40100 | Loss: 0.2384 | Spent: 6.1 secs | LR: 0.000384
INFO:tensorflow:Step 40150 | Loss: 0.2181 | Spent: 6.0 secs | LR: 0.000383
INFO:tensorflow:Step 40200 | Loss: 0.2246 | Spent: 6.1 secs | LR: 0.000382
INFO:tensorflow:Step 40250 | Loss: 0.2418 | Spent: 6.1 secs | LR: 0.000381
INFO:tensorflow:Step 40300 | Loss: 0.2390 | Spent: 6.1 secs | LR: 0.000380
INFO:tensorflow:Step 40350 | Loss: 0.2235 | Spent: 6.1 secs | LR: 0.000379
INFO:tensorflow:Step 40400 | Loss: 0.2371 | Spent: 6.1 secs | LR: 0.000378
INFO:tensorflow:Step 40450 | Loss: 0.2541 | Spent: 6.0 secs | LR: 0.000377
INFO:tensorflow:Step 40500 | Loss: 0.2299 | Spent: 6.1 secs | LR: 0.000376
INFO:tensorflow:Step 40550 | Loss: 0.2157 | Spent: 6.1 secs | LR: 0.000375
INFO:tensorflow:Step 40600 | Loss: 0.2398 | Spent: 6.1 secs | LR: 0.000374
INFO:tensorflow:Step 40650 | Loss: 0.2297 | Spent: 6.1 secs | LR: 0.000373
INFO:tensorflow:Step 40700 | Loss: 0.2300 | Spent: 6.0 secs | LR: 0.000372
INFO:tensorflow:Step 40750 | Loss: 0.2326 | Spent: 6.1 secs | LR: 0.000371
INFO:tensorflow:Step 40800 | Loss: 0.2374 | Spent: 6.1 secs | LR: 0.000370
INFO:tensorflow:Step 40850 | Loss: 0.2442 | Spent: 6.0 secs | LR: 0.000369
INFO:tensorflow:Step 40900 | Loss: 0.2286 | Spent: 6.1 secs | LR: 0.000368
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.871| [email protected]: 0.940 | [email protected]: 0.905 | [email protected]: 0.827
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 40950 | Loss: 0.2421 | Spent: 51.2 secs | LR: 0.000367
INFO:tensorflow:Step 41000 | Loss: 0.2310 | Spent: 6.0 secs | LR: 0.000366
INFO:tensorflow:Step 41050 | Loss: 0.2351 | Spent: 6.1 secs | LR: 0.000365
INFO:tensorflow:Step 41100 | Loss: 0.2449 | Spent: 6.1 secs | LR: 0.000364
INFO:tensorflow:Step 41150 | Loss: 0.2271 | Spent: 6.1 secs | LR: 0.000363
INFO:tensorflow:Step 41200 | Loss: 0.2327 | Spent: 6.1 secs | LR: 0.000363
INFO:tensorflow:Step 41250 | Loss: 0.2348 | Spent: 6.1 secs | LR: 0.000362
INFO:tensorflow:Step 41300 | Loss: 0.2276 | Spent: 6.1 secs | LR: 0.000361
INFO:tensorflow:Step 41350 | Loss: 0.2378 | Spent: 6.1 secs | LR: 0.000360
INFO:tensorflow:Step 41400 | Loss: 0.2260 | Spent: 6.1 secs | LR: 0.000359
INFO:tensorflow:Step 41450 | Loss: 0.2277 | Spent: 6.1 secs | LR: 0.000358
INFO:tensorflow:Step 41500 | Loss: 0.2356 | Spent: 6.1 secs | LR: 0.000357
INFO:tensorflow:Step 41550 | Loss: 0.2327 | Spent: 6.0 secs | LR: 0.000356
INFO:tensorflow:Step 41600 | Loss: 0.2181 | Spent: 6.2 secs | LR: 0.000355
INFO:tensorflow:Step 41650 | Loss: 0.2170 | Spent: 6.1 secs | LR: 0.000354
INFO:tensorflow:Step 41700 | Loss: 0.2025 | Spent: 6.0 secs | LR: 0.000353
INFO:tensorflow:Step 41750 | Loss: 0.2094 | Spent: 6.0 secs | LR: 0.000352
INFO:tensorflow:Step 41800 | Loss: 0.2355 | Spent: 5.9 secs | LR: 0.000352
INFO:tensorflow:Step 41850 | Loss: 0.2210 | Spent: 5.9 secs | LR: 0.000351
INFO:tensorflow:Step 41900 | Loss: 0.2130 | Spent: 6.1 secs | LR: 0.000350
INFO:tensorflow:Step 41950 | Loss: 0.2079 | Spent: 6.0 secs | LR: 0.000349
INFO:tensorflow:Step 42000 | Loss: 0.2250 | Spent: 6.0 secs | LR: 0.000348
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.870| [email protected]: 0.941 | [email protected]: 0.902 | [email protected]: 0.827
INFO:tensorflow:Best MRR: 0.876
INFO:tensorflow:MRR not improved over 5 epochs, Early Stop