In [1]:
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).
In [2]:
%tensorflow_version 2.x
!pip install tensorflow-addons
Requirement already satisfied: tensorflow-addons in /usr/local/lib/python3.6/dist-packages (0.8.3)
Requirement already satisfied: typeguard in /usr/local/lib/python3.6/dist-packages (from tensorflow-addons) (2.7.1)
In [3]:
from tensorflow_addons.optimizers.cyclical_learning_rate import Triangular2CyclicalLearningRate

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 2.2.0
WARNING:tensorflow:From <ipython-input-3-177c62f47bc4>:9: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
GPU Enabled: True
In [0]:
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
In [0]:
"""
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
In [0]:
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
In [0]:
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)
In [0]:
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.))
  
  
  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)
    return x
In [0]:
def label_smoothing(inputs, epsilon):
  V = inputs.get_shape().as_list()[-1]
  return ((1-epsilon) * inputs) + (epsilon / V)
In [0]:
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,
    'num_samples': 141442,
    'init_lr': 1e-4,
    'max_lr': 5e-3,
    'num_patience': 10,
    'epsilon': .1,
}
In [0]:
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'])
In [12]:
model = TuckER(params)
model.build(input_shape=[[None], [None]])
pprint.pprint([(v.name, v.shape) for v in model.trainable_variables])

decay_lr = Triangular2CyclicalLearningRate(
  initial_learning_rate = params['init_lr'],
  maximal_learning_rate = params['max_lr'],
  step_size = 8 * params['num_samples'] // params['batch_size'],)
optim = tf.optimizers.Adam(params['init_lr'])
global_step = 0

best_mrr = 0.
count = 0

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()
  
  if mrr > best_mrr:
    best_mrr = mrr
    # you can save model here
    count = 0
  else:
    count += 1
  logger.info("Best MRR: {:.3f}".format(best_mrr))
  
  if count == params['num_patience']:
    print(params['num_patience'], "times not improve the best result, therefore stop training")
    break
[('Entity/embeddings:0', TensorShape([40943, 200])),
 ('Relation/embeddings:0', TensorShape([18, 30])),
 ('Kernel:0', TensorShape([30, 200, 200]))]
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 0 | Loss: 1.3566 | Spent: 28.3 secs | LR: 0.000100
INFO:tensorflow:Step 50 | Loss: 1.3608 | Spent: 3.9 secs | LR: 0.000128
INFO:tensorflow:Step 100 | Loss: 1.3560 | Spent: 3.9 secs | LR: 0.000155
INFO:tensorflow:Step 150 | Loss: 1.3505 | Spent: 3.9 secs | LR: 0.000183
INFO:tensorflow:Step 200 | Loss: 1.3551 | Spent: 3.9 secs | LR: 0.000211
INFO:tensorflow:Step 250 | Loss: 1.3430 | Spent: 3.9 secs | LR: 0.000239
INFO:tensorflow:Step 300 | Loss: 1.3206 | Spent: 4.0 secs | LR: 0.000266
INFO:tensorflow:Step 350 | Loss: 1.3240 | Spent: 3.9 secs | LR: 0.000294
INFO:tensorflow:Step 400 | Loss: 1.2878 | Spent: 3.9 secs | LR: 0.000322
INFO:tensorflow:Step 450 | Loss: 1.2850 | Spent: 3.9 secs | LR: 0.000349
INFO:tensorflow:Step 500 | Loss: 1.2382 | Spent: 3.9 secs | LR: 0.000377
INFO:tensorflow:Step 550 | Loss: 1.1703 | Spent: 3.9 secs | LR: 0.000405
INFO:tensorflow:Step 600 | Loss: 1.1644 | Spent: 4.0 secs | LR: 0.000433
INFO:tensorflow:Step 650 | Loss: 1.0887 | Spent: 4.0 secs | LR: 0.000460
INFO:tensorflow:Step 700 | Loss: 0.9794 | Spent: 4.0 secs | LR: 0.000488
INFO:tensorflow:Step 750 | Loss: 0.9560 | Spent: 3.9 secs | LR: 0.000516
INFO:tensorflow:Step 800 | Loss: 0.9206 | Spent: 3.9 secs | LR: 0.000543
INFO:tensorflow:Step 850 | Loss: 0.8336 | Spent: 3.9 secs | LR: 0.000571
INFO:tensorflow:Step 900 | Loss: 0.6615 | Spent: 3.9 secs | LR: 0.000599
INFO:tensorflow:Step 950 | Loss: 0.7575 | Spent: 3.9 secs | LR: 0.000627
INFO:tensorflow:Step 1000 | Loss: 0.6943 | Spent: 3.9 secs | LR: 0.000654
INFO:tensorflow:Step 1050 | Loss: 0.6499 | Spent: 3.9 secs | LR: 0.000682
INFO:tensorflow:Step 1100 | Loss: 0.6538 | Spent: 3.9 secs | LR: 0.000710
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.181| [email protected]: 0.258 | [email protected]: 0.197 | [email protected]: 0.140
INFO:tensorflow:Best MRR: 0.181
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 1150 | Loss: 0.4462 | Spent: 34.5 secs | LR: 0.000737
INFO:tensorflow:Step 1200 | Loss: 0.4277 | Spent: 3.9 secs | LR: 0.000765
INFO:tensorflow:Step 1250 | Loss: 0.4784 | Spent: 3.9 secs | LR: 0.000793
INFO:tensorflow:Step 1300 | Loss: 0.4376 | Spent: 3.9 secs | LR: 0.000821
INFO:tensorflow:Step 1350 | Loss: 0.3833 | Spent: 3.9 secs | LR: 0.000848
INFO:tensorflow:Step 1400 | Loss: 0.4248 | Spent: 3.9 secs | LR: 0.000876
INFO:tensorflow:Step 1450 | Loss: 0.3956 | Spent: 3.9 secs | LR: 0.000904
INFO:tensorflow:Step 1500 | Loss: 0.3547 | Spent: 3.9 secs | LR: 0.000931
INFO:tensorflow:Step 1550 | Loss: 0.3082 | Spent: 3.9 secs | LR: 0.000959
INFO:tensorflow:Step 1600 | Loss: 0.3689 | Spent: 3.9 secs | LR: 0.000987
INFO:tensorflow:Step 1650 | Loss: 0.4146 | Spent: 3.9 secs | LR: 0.001015
INFO:tensorflow:Step 1700 | Loss: 0.3565 | Spent: 3.9 secs | LR: 0.001042
INFO:tensorflow:Step 1750 | Loss: 0.3600 | Spent: 3.9 secs | LR: 0.001070
INFO:tensorflow:Step 1800 | Loss: 0.3138 | Spent: 3.9 secs | LR: 0.001098
INFO:tensorflow:Step 1850 | Loss: 0.3412 | Spent: 3.9 secs | LR: 0.001125
INFO:tensorflow:Step 1900 | Loss: 0.3611 | Spent: 3.9 secs | LR: 0.001153
INFO:tensorflow:Step 1950 | Loss: 0.3818 | Spent: 4.0 secs | LR: 0.001181
INFO:tensorflow:Step 2000 | Loss: 0.3119 | Spent: 3.9 secs | LR: 0.001209
INFO:tensorflow:Step 2050 | Loss: 0.3023 | Spent: 3.9 secs | LR: 0.001236
INFO:tensorflow:Step 2100 | Loss: 0.3255 | Spent: 3.9 secs | LR: 0.001264
INFO:tensorflow:Step 2150 | Loss: 0.3346 | Spent: 3.9 secs | LR: 0.001292
INFO:tensorflow:Step 2200 | Loss: 0.2976 | Spent: 3.9 secs | LR: 0.001319
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.390| [email protected]: 0.529 | [email protected]: 0.422 | [email protected]: 0.317
INFO:tensorflow:Best MRR: 0.390
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 2250 | Loss: 0.2915 | Spent: 34.4 secs | LR: 0.001347
INFO:tensorflow:Step 2300 | Loss: 0.2695 | Spent: 3.9 secs | LR: 0.001375
INFO:tensorflow:Step 2350 | Loss: 0.2749 | Spent: 3.9 secs | LR: 0.001403
INFO:tensorflow:Step 2400 | Loss: 0.2530 | Spent: 3.9 secs | LR: 0.001430
INFO:tensorflow:Step 2450 | Loss: 0.2772 | Spent: 3.9 secs | LR: 0.001458
INFO:tensorflow:Step 2500 | Loss: 0.2744 | Spent: 3.9 secs | LR: 0.001486
INFO:tensorflow:Step 2550 | Loss: 0.2565 | Spent: 4.0 secs | LR: 0.001513
INFO:tensorflow:Step 2600 | Loss: 0.2725 | Spent: 3.9 secs | LR: 0.001541
INFO:tensorflow:Step 2650 | Loss: 0.2615 | Spent: 3.9 secs | LR: 0.001569
INFO:tensorflow:Step 2700 | Loss: 0.2421 | Spent: 3.9 secs | LR: 0.001597
INFO:tensorflow:Step 2750 | Loss: 0.2697 | Spent: 3.9 secs | LR: 0.001624
INFO:tensorflow:Step 2800 | Loss: 0.2651 | Spent: 3.9 secs | LR: 0.001652
INFO:tensorflow:Step 2850 | Loss: 0.2657 | Spent: 3.9 secs | LR: 0.001680
INFO:tensorflow:Step 2900 | Loss: 0.2560 | Spent: 3.9 secs | LR: 0.001707
INFO:tensorflow:Step 2950 | Loss: 0.2601 | Spent: 3.9 secs | LR: 0.001735
INFO:tensorflow:Step 3000 | Loss: 0.2611 | Spent: 3.9 secs | LR: 0.001763
INFO:tensorflow:Step 3050 | Loss: 0.2637 | Spent: 3.9 secs | LR: 0.001791
INFO:tensorflow:Step 3100 | Loss: 0.3035 | Spent: 3.9 secs | LR: 0.001818
INFO:tensorflow:Step 3150 | Loss: 0.2722 | Spent: 3.9 secs | LR: 0.001846
INFO:tensorflow:Step 3200 | Loss: 0.2535 | Spent: 3.9 secs | LR: 0.001874
INFO:tensorflow:Step 3250 | Loss: 0.2638 | Spent: 3.9 secs | LR: 0.001901
INFO:tensorflow:Step 3300 | Loss: 0.2749 | Spent: 3.9 secs | LR: 0.001929
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.477| [email protected]: 0.641 | [email protected]: 0.517 | [email protected]: 0.394
INFO:tensorflow:Best MRR: 0.477
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 3350 | Loss: 0.2573 | Spent: 34.5 secs | LR: 0.001957
INFO:tensorflow:Step 3400 | Loss: 0.2547 | Spent: 4.0 secs | LR: 0.001985
INFO:tensorflow:Step 3450 | Loss: 0.2568 | Spent: 4.0 secs | LR: 0.002012
INFO:tensorflow:Step 3500 | Loss: 0.2577 | Spent: 3.9 secs | LR: 0.002040
INFO:tensorflow:Step 3550 | Loss: 0.2571 | Spent: 3.9 secs | LR: 0.002068
INFO:tensorflow:Step 3600 | Loss: 0.2439 | Spent: 3.9 secs | LR: 0.002095
INFO:tensorflow:Step 3650 | Loss: 0.2498 | Spent: 3.9 secs | LR: 0.002123
INFO:tensorflow:Step 3700 | Loss: 0.2838 | Spent: 3.9 secs | LR: 0.002151
INFO:tensorflow:Step 3750 | Loss: 0.2677 | Spent: 3.9 secs | LR: 0.002179
INFO:tensorflow:Step 3800 | Loss: 0.2975 | Spent: 3.9 secs | LR: 0.002206
INFO:tensorflow:Step 3850 | Loss: 0.2382 | Spent: 3.9 secs | LR: 0.002234
INFO:tensorflow:Step 3900 | Loss: 0.2487 | Spent: 3.9 secs | LR: 0.002262
INFO:tensorflow:Step 3950 | Loss: 0.2702 | Spent: 3.9 secs | LR: 0.002289
INFO:tensorflow:Step 4000 | Loss: 0.2576 | Spent: 3.9 secs | LR: 0.002317
INFO:tensorflow:Step 4050 | Loss: 0.2809 | Spent: 3.9 secs | LR: 0.002345
INFO:tensorflow:Step 4100 | Loss: 0.2622 | Spent: 3.9 secs | LR: 0.002373
INFO:tensorflow:Step 4150 | Loss: 0.2814 | Spent: 3.9 secs | LR: 0.002400
INFO:tensorflow:Step 4200 | Loss: 0.2342 | Spent: 3.9 secs | LR: 0.002428
INFO:tensorflow:Step 4250 | Loss: 0.2692 | Spent: 3.9 secs | LR: 0.002456
INFO:tensorflow:Step 4300 | Loss: 0.2668 | Spent: 3.9 secs | LR: 0.002483
INFO:tensorflow:Step 4350 | Loss: 0.2629 | Spent: 3.9 secs | LR: 0.002511
INFO:tensorflow:Step 4400 | Loss: 0.2714 | Spent: 3.9 secs | LR: 0.002539
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.468| [email protected]: 0.626 | [email protected]: 0.503 | [email protected]: 0.386
INFO:tensorflow:Best MRR: 0.477
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 4450 | Loss: 0.2810 | Spent: 34.3 secs | LR: 0.002567
INFO:tensorflow:Step 4500 | Loss: 0.2395 | Spent: 3.9 secs | LR: 0.002594
INFO:tensorflow:Step 4550 | Loss: 0.2386 | Spent: 3.9 secs | LR: 0.002622
INFO:tensorflow:Step 4600 | Loss: 0.2942 | Spent: 3.9 secs | LR: 0.002650
INFO:tensorflow:Step 4650 | Loss: 0.2644 | Spent: 3.9 secs | LR: 0.002677
INFO:tensorflow:Step 4700 | Loss: 0.2550 | Spent: 3.9 secs | LR: 0.002705
INFO:tensorflow:Step 4750 | Loss: 0.2700 | Spent: 3.9 secs | LR: 0.002733
INFO:tensorflow:Step 4800 | Loss: 0.2832 | Spent: 3.9 secs | LR: 0.002761
INFO:tensorflow:Step 4850 | Loss: 0.2780 | Spent: 3.9 secs | LR: 0.002788
INFO:tensorflow:Step 4900 | Loss: 0.2665 | Spent: 3.9 secs | LR: 0.002816
INFO:tensorflow:Step 4950 | Loss: 0.3016 | Spent: 3.9 secs | LR: 0.002844
INFO:tensorflow:Step 5000 | Loss: 0.2647 | Spent: 3.9 secs | LR: 0.002871
INFO:tensorflow:Step 5050 | Loss: 0.2891 | Spent: 3.9 secs | LR: 0.002899
INFO:tensorflow:Step 5100 | Loss: 0.2944 | Spent: 3.9 secs | LR: 0.002927
INFO:tensorflow:Step 5150 | Loss: 0.2821 | Spent: 3.9 secs | LR: 0.002955
INFO:tensorflow:Step 5200 | Loss: 0.2678 | Spent: 3.9 secs | LR: 0.002982
INFO:tensorflow:Step 5250 | Loss: 0.2908 | Spent: 3.9 secs | LR: 0.003010
INFO:tensorflow:Step 5300 | Loss: 0.2750 | Spent: 3.9 secs | LR: 0.003038
INFO:tensorflow:Step 5350 | Loss: 0.2820 | Spent: 3.9 secs | LR: 0.003065
INFO:tensorflow:Step 5400 | Loss: 0.2669 | Spent: 3.9 secs | LR: 0.003093
INFO:tensorflow:Step 5450 | Loss: 0.3002 | Spent: 3.9 secs | LR: 0.003121
INFO:tensorflow:Step 5500 | Loss: 0.2748 | Spent: 3.9 secs | LR: 0.003149
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.492| [email protected]: 0.635 | [email protected]: 0.528 | [email protected]: 0.416
INFO:tensorflow:Best MRR: 0.492
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 5550 | Loss: 0.3629 | Spent: 34.9 secs | LR: 0.003176
INFO:tensorflow:Step 5600 | Loss: 0.3003 | Spent: 3.9 secs | LR: 0.003204
INFO:tensorflow:Step 5650 | Loss: 0.2881 | Spent: 3.9 secs | LR: 0.003232
INFO:tensorflow:Step 5700 | Loss: 0.2555 | Spent: 3.9 secs | LR: 0.003260
INFO:tensorflow:Step 5750 | Loss: 0.3026 | Spent: 3.9 secs | LR: 0.003287
INFO:tensorflow:Step 5800 | Loss: 0.2858 | Spent: 3.9 secs | LR: 0.003315
INFO:tensorflow:Step 5850 | Loss: 0.2934 | Spent: 3.9 secs | LR: 0.003343
INFO:tensorflow:Step 5900 | Loss: 0.2847 | Spent: 3.9 secs | LR: 0.003370
INFO:tensorflow:Step 5950 | Loss: 0.2422 | Spent: 3.9 secs | LR: 0.003398
INFO:tensorflow:Step 6000 | Loss: 0.2732 | Spent: 3.9 secs | LR: 0.003426
INFO:tensorflow:Step 6050 | Loss: 0.2682 | Spent: 3.9 secs | LR: 0.003454
INFO:tensorflow:Step 6100 | Loss: 0.2585 | Spent: 3.9 secs | LR: 0.003481
INFO:tensorflow:Step 6150 | Loss: 0.2876 | Spent: 3.9 secs | LR: 0.003509
INFO:tensorflow:Step 6200 | Loss: 0.2848 | Spent: 3.9 secs | LR: 0.003537
INFO:tensorflow:Step 6250 | Loss: 0.2719 | Spent: 3.9 secs | LR: 0.003564
INFO:tensorflow:Step 6300 | Loss: 0.2883 | Spent: 3.9 secs | LR: 0.003592
INFO:tensorflow:Step 6350 | Loss: 0.2723 | Spent: 3.9 secs | LR: 0.003620
INFO:tensorflow:Step 6400 | Loss: 0.2805 | Spent: 3.9 secs | LR: 0.003648
INFO:tensorflow:Step 6450 | Loss: 0.2418 | Spent: 3.9 secs | LR: 0.003675
INFO:tensorflow:Step 6500 | Loss: 0.2847 | Spent: 3.9 secs | LR: 0.003703
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INFO:tensorflow:Step 6600 | Loss: 0.2762 | Spent: 4.0 secs | LR: 0.003758
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.662| [email protected]: 0.791 | [email protected]: 0.704 | [email protected]: 0.590
INFO:tensorflow:Best MRR: 0.662
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 6650 | Loss: 0.2630 | Spent: 34.1 secs | LR: 0.003786
INFO:tensorflow:Step 6700 | Loss: 0.2793 | Spent: 3.9 secs | LR: 0.003814
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INFO:tensorflow:Step 6900 | Loss: 0.2620 | Spent: 3.9 secs | LR: 0.003925
INFO:tensorflow:Step 6950 | Loss: 0.2612 | Spent: 3.9 secs | LR: 0.003952
INFO:tensorflow:Step 7000 | Loss: 0.2587 | Spent: 3.9 secs | LR: 0.003980
INFO:tensorflow:Step 7050 | Loss: 0.2811 | Spent: 3.9 secs | LR: 0.004008
INFO:tensorflow:Step 7100 | Loss: 0.2344 | Spent: 3.9 secs | LR: 0.004036
INFO:tensorflow:Step 7150 | Loss: 0.2638 | Spent: 3.9 secs | LR: 0.004063
INFO:tensorflow:Step 7200 | Loss: 0.2505 | Spent: 3.9 secs | LR: 0.004091
INFO:tensorflow:Step 7250 | Loss: 0.2260 | Spent: 3.9 secs | LR: 0.004119
INFO:tensorflow:Step 7300 | Loss: 0.2660 | Spent: 4.0 secs | LR: 0.004146
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INFO:tensorflow:Step 7400 | Loss: 0.2661 | Spent: 3.9 secs | LR: 0.004202
INFO:tensorflow:Step 7450 | Loss: 0.2559 | Spent: 3.9 secs | LR: 0.004230
INFO:tensorflow:Step 7500 | Loss: 0.2676 | Spent: 3.9 secs | LR: 0.004257
INFO:tensorflow:Step 7550 | Loss: 0.2326 | Spent: 3.9 secs | LR: 0.004285
INFO:tensorflow:Step 7600 | Loss: 0.2362 | Spent: 3.9 secs | LR: 0.004313
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INFO:tensorflow:Step 7700 | Loss: 0.2457 | Spent: 3.9 secs | LR: 0.004368
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.738| [email protected]: 0.855 | [email protected]: 0.780 | [email protected]: 0.672
INFO:tensorflow:Best MRR: 0.738
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 7750 | Loss: 0.2394 | Spent: 34.2 secs | LR: 0.004396
INFO:tensorflow:Step 7800 | Loss: 0.2774 | Spent: 3.9 secs | LR: 0.004424
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INFO:tensorflow:Step 8150 | Loss: 0.2398 | Spent: 3.9 secs | LR: 0.004618
INFO:tensorflow:Step 8200 | Loss: 0.2513 | Spent: 3.9 secs | LR: 0.004645
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INFO:tensorflow:Step 8300 | Loss: 0.2337 | Spent: 3.9 secs | LR: 0.004701
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INFO:tensorflow:Step 8450 | Loss: 0.2562 | Spent: 3.9 secs | LR: 0.004784
INFO:tensorflow:Step 8500 | Loss: 0.2379 | Spent: 3.9 secs | LR: 0.004812
INFO:tensorflow:Step 8550 | Loss: 0.2493 | Spent: 3.9 secs | LR: 0.004839
INFO:tensorflow:Step 8600 | Loss: 0.2548 | Spent: 3.8 secs | LR: 0.004867
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INFO:tensorflow:Step 8800 | Loss: 0.2491 | Spent: 3.9 secs | LR: 0.004978
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.740| [email protected]: 0.855 | [email protected]: 0.790 | [email protected]: 0.673
INFO:tensorflow:Best MRR: 0.740
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 8850 | Loss: 0.2639 | Spent: 34.2 secs | LR: 0.004994
INFO:tensorflow:Step 8900 | Loss: 0.2526 | Spent: 4.0 secs | LR: 0.004967
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INFO:tensorflow:Step 9250 | Loss: 0.2639 | Spent: 3.9 secs | LR: 0.004773
INFO:tensorflow:Step 9300 | Loss: 0.2498 | Spent: 3.9 secs | LR: 0.004745
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INFO:tensorflow:Step 9400 | Loss: 0.2538 | Spent: 4.0 secs | LR: 0.004690
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INFO:tensorflow:Step 9950 | Loss: 0.2582 | Spent: 3.9 secs | LR: 0.004385
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.768| [email protected]: 0.874 | [email protected]: 0.813 | [email protected]: 0.706
INFO:tensorflow:Best MRR: 0.768
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 10000 | Loss: 0.2524 | Spent: 34.1 secs | LR: 0.004357
INFO:tensorflow:Step 10050 | Loss: 0.2535 | Spent: 3.9 secs | LR: 0.004329
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INFO:tensorflow:Step 10400 | Loss: 0.2513 | Spent: 3.9 secs | LR: 0.004135
INFO:tensorflow:Step 10450 | Loss: 0.2435 | Spent: 3.9 secs | LR: 0.004108
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INFO:tensorflow:Step 11050 | Loss: 0.2577 | Spent: 3.9 secs | LR: 0.003775
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.831| [email protected]: 0.907 | [email protected]: 0.864 | [email protected]: 0.785
INFO:tensorflow:Best MRR: 0.831
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 11100 | Loss: 0.2331 | Spent: 34.4 secs | LR: 0.003747
INFO:tensorflow:Step 11150 | Loss: 0.2409 | Spent: 4.0 secs | LR: 0.003720
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INFO:tensorflow:Step 11550 | Loss: 0.2374 | Spent: 3.9 secs | LR: 0.003498
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INFO:tensorflow:Step 12150 | Loss: 0.2442 | Spent: 3.9 secs | LR: 0.003165
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.855| [email protected]: 0.923 | [email protected]: 0.886 | [email protected]: 0.815
INFO:tensorflow:Best MRR: 0.855
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 12200 | Loss: 0.2258 | Spent: 34.3 secs | LR: 0.003138
INFO:tensorflow:Step 12250 | Loss: 0.2369 | Spent: 4.0 secs | LR: 0.003110
INFO:tensorflow:Step 12300 | Loss: 0.2381 | Spent: 3.9 secs | LR: 0.003082
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INFO:tensorflow:Step 12450 | Loss: 0.2229 | Spent: 3.9 secs | LR: 0.002999
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INFO:tensorflow:Step 12600 | Loss: 0.2245 | Spent: 3.9 secs | LR: 0.002916
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INFO:tensorflow:Step 12750 | Loss: 0.2505 | Spent: 3.9 secs | LR: 0.002833
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INFO:tensorflow:Step 13000 | Loss: 0.2506 | Spent: 3.9 secs | LR: 0.002694
INFO:tensorflow:Step 13050 | Loss: 0.2258 | Spent: 3.9 secs | LR: 0.002666
INFO:tensorflow:Step 13100 | Loss: 0.2059 | Spent: 3.9 secs | LR: 0.002639
INFO:tensorflow:Step 13150 | Loss: 0.2425 | Spent: 3.9 secs | LR: 0.002611
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INFO:tensorflow:Step 13250 | Loss: 0.2338 | Spent: 3.9 secs | LR: 0.002556
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.863| [email protected]: 0.926 | [email protected]: 0.892 | [email protected]: 0.824
INFO:tensorflow:Best MRR: 0.863
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 13300 | Loss: 0.2283 | Spent: 34.3 secs | LR: 0.002528
INFO:tensorflow:Step 13350 | Loss: 0.2323 | Spent: 3.9 secs | LR: 0.002500
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INFO:tensorflow:Step 13700 | Loss: 0.2455 | Spent: 3.9 secs | LR: 0.002306
INFO:tensorflow:Step 13750 | Loss: 0.2168 | Spent: 3.9 secs | LR: 0.002278
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INFO:tensorflow:Step 14050 | Loss: 0.2488 | Spent: 3.9 secs | LR: 0.002112
INFO:tensorflow:Step 14100 | Loss: 0.2196 | Spent: 3.9 secs | LR: 0.002084
INFO:tensorflow:Step 14150 | Loss: 0.2338 | Spent: 3.9 secs | LR: 0.002057
INFO:tensorflow:Step 14200 | Loss: 0.2497 | Spent: 3.9 secs | LR: 0.002029
INFO:tensorflow:Step 14250 | Loss: 0.2410 | Spent: 3.9 secs | LR: 0.002001
INFO:tensorflow:Step 14300 | Loss: 0.2158 | Spent: 3.9 secs | LR: 0.001974
INFO:tensorflow:Step 14350 | Loss: 0.2325 | Spent: 3.9 secs | LR: 0.001946
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.871| [email protected]: 0.930 | [email protected]: 0.897 | [email protected]: 0.837
INFO:tensorflow:Best MRR: 0.871
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 14400 | Loss: 0.2581 | Spent: 34.1 secs | LR: 0.001918
INFO:tensorflow:Step 14450 | Loss: 0.2241 | Spent: 3.9 secs | LR: 0.001890
INFO:tensorflow:Step 14500 | Loss: 0.2382 | Spent: 3.9 secs | LR: 0.001863
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INFO:tensorflow:Step 14600 | Loss: 0.2317 | Spent: 3.9 secs | LR: 0.001807
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INFO:tensorflow:Step 14750 | Loss: 0.2204 | Spent: 3.9 secs | LR: 0.001724
INFO:tensorflow:Step 14800 | Loss: 0.2271 | Spent: 3.9 secs | LR: 0.001696
INFO:tensorflow:Step 14850 | Loss: 0.2551 | Spent: 3.9 secs | LR: 0.001669
INFO:tensorflow:Step 14900 | Loss: 0.2345 | Spent: 3.9 secs | LR: 0.001641
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INFO:tensorflow:Step 15000 | Loss: 0.2185 | Spent: 3.9 secs | LR: 0.001586
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INFO:tensorflow:Step 15200 | Loss: 0.2317 | Spent: 3.9 secs | LR: 0.001475
INFO:tensorflow:Step 15250 | Loss: 0.2480 | Spent: 3.9 secs | LR: 0.001447
INFO:tensorflow:Step 15300 | Loss: 0.2465 | Spent: 3.9 secs | LR: 0.001419
INFO:tensorflow:Step 15350 | Loss: 0.2339 | Spent: 3.9 secs | LR: 0.001392
INFO:tensorflow:Step 15400 | Loss: 0.2363 | Spent: 4.0 secs | LR: 0.001364
INFO:tensorflow:Step 15450 | Loss: 0.2128 | Spent: 3.9 secs | LR: 0.001336
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.876| [email protected]: 0.935 | [email protected]: 0.901 | [email protected]: 0.842
INFO:tensorflow:Best MRR: 0.876
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 15500 | Loss: 0.2482 | Spent: 34.4 secs | LR: 0.001308
INFO:tensorflow:Step 15550 | Loss: 0.2150 | Spent: 3.9 secs | LR: 0.001281
INFO:tensorflow:Step 15600 | Loss: 0.2118 | Spent: 3.9 secs | LR: 0.001253
INFO:tensorflow:Step 15650 | Loss: 0.2558 | Spent: 3.9 secs | LR: 0.001225
INFO:tensorflow:Step 15700 | Loss: 0.2429 | Spent: 3.9 secs | LR: 0.001198
INFO:tensorflow:Step 15750 | Loss: 0.2191 | Spent: 3.9 secs | LR: 0.001170
INFO:tensorflow:Step 15800 | Loss: 0.2271 | Spent: 3.9 secs | LR: 0.001142
INFO:tensorflow:Step 15850 | Loss: 0.2241 | Spent: 3.9 secs | LR: 0.001114
INFO:tensorflow:Step 15900 | Loss: 0.2386 | Spent: 3.9 secs | LR: 0.001087
INFO:tensorflow:Step 15950 | Loss: 0.2434 | Spent: 3.9 secs | LR: 0.001059
INFO:tensorflow:Step 16000 | Loss: 0.2297 | Spent: 3.9 secs | LR: 0.001031
INFO:tensorflow:Step 16050 | Loss: 0.2553 | Spent: 3.9 secs | LR: 0.001004
INFO:tensorflow:Step 16100 | Loss: 0.2328 | Spent: 3.9 secs | LR: 0.000976
INFO:tensorflow:Step 16150 | Loss: 0.2185 | Spent: 3.9 secs | LR: 0.000948
INFO:tensorflow:Step 16200 | Loss: 0.2259 | Spent: 3.9 secs | LR: 0.000920
INFO:tensorflow:Step 16250 | Loss: 0.2469 | Spent: 3.9 secs | LR: 0.000893
INFO:tensorflow:Step 16300 | Loss: 0.2180 | Spent: 3.9 secs | LR: 0.000865
INFO:tensorflow:Step 16350 | Loss: 0.2055 | Spent: 3.9 secs | LR: 0.000837
INFO:tensorflow:Step 16400 | Loss: 0.2252 | Spent: 3.9 secs | LR: 0.000810
INFO:tensorflow:Step 16450 | Loss: 0.2394 | Spent: 3.9 secs | LR: 0.000782
INFO:tensorflow:Step 16500 | Loss: 0.2407 | Spent: 4.0 secs | LR: 0.000754
INFO:tensorflow:Step 16550 | Loss: 0.2077 | Spent: 3.9 secs | LR: 0.000726
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.885| [email protected]: 0.939 | [email protected]: 0.909 | [email protected]: 0.853
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 16600 | Loss: 0.2156 | Spent: 34.1 secs | LR: 0.000699
INFO:tensorflow:Step 16650 | Loss: 0.2195 | Spent: 3.9 secs | LR: 0.000671
INFO:tensorflow:Step 16700 | Loss: 0.2343 | Spent: 3.9 secs | LR: 0.000643
INFO:tensorflow:Step 16750 | Loss: 0.2337 | Spent: 3.9 secs | LR: 0.000615
INFO:tensorflow:Step 16800 | Loss: 0.2344 | Spent: 3.9 secs | LR: 0.000588
INFO:tensorflow:Step 16850 | Loss: 0.2433 | Spent: 3.9 secs | LR: 0.000560
INFO:tensorflow:Step 16900 | Loss: 0.2245 | Spent: 3.9 secs | LR: 0.000532
INFO:tensorflow:Step 16950 | Loss: 0.2532 | Spent: 3.9 secs | LR: 0.000505
INFO:tensorflow:Step 17000 | Loss: 0.2145 | Spent: 3.9 secs | LR: 0.000477
INFO:tensorflow:Step 17050 | Loss: 0.2443 | Spent: 3.9 secs | LR: 0.000449
INFO:tensorflow:Step 17100 | Loss: 0.2440 | Spent: 3.9 secs | LR: 0.000421
INFO:tensorflow:Step 17150 | Loss: 0.2384 | Spent: 3.9 secs | LR: 0.000394
INFO:tensorflow:Step 17200 | Loss: 0.2325 | Spent: 3.9 secs | LR: 0.000366
INFO:tensorflow:Step 17250 | Loss: 0.2401 | Spent: 3.9 secs | LR: 0.000338
INFO:tensorflow:Step 17300 | Loss: 0.2242 | Spent: 3.9 secs | LR: 0.000311
INFO:tensorflow:Step 17350 | Loss: 0.2287 | Spent: 3.9 secs | LR: 0.000283
INFO:tensorflow:Step 17400 | Loss: 0.2412 | Spent: 3.9 secs | LR: 0.000255
INFO:tensorflow:Step 17450 | Loss: 0.2357 | Spent: 3.9 secs | LR: 0.000227
INFO:tensorflow:Step 17500 | Loss: 0.2413 | Spent: 3.9 secs | LR: 0.000200
INFO:tensorflow:Step 17550 | Loss: 0.2107 | Spent: 3.9 secs | LR: 0.000172
INFO:tensorflow:Step 17600 | Loss: 0.2297 | Spent: 3.9 secs | LR: 0.000144
INFO:tensorflow:Step 17650 | Loss: 0.2170 | Spent: 3.9 secs | LR: 0.000117
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.884| [email protected]: 0.939 | [email protected]: 0.909 | [email protected]: 0.851
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 17700 | Loss: 0.2181 | Spent: 34.7 secs | LR: 0.000106
INFO:tensorflow:Step 17750 | Loss: 0.2201 | Spent: 4.0 secs | LR: 0.000119
INFO:tensorflow:Step 17800 | Loss: 0.1936 | Spent: 3.9 secs | LR: 0.000133
INFO:tensorflow:Step 17850 | Loss: 0.2336 | Spent: 4.0 secs | LR: 0.000147
INFO:tensorflow:Step 17900 | Loss: 0.2179 | Spent: 3.9 secs | LR: 0.000161
INFO:tensorflow:Step 17950 | Loss: 0.1988 | Spent: 4.0 secs | LR: 0.000175
INFO:tensorflow:Step 18000 | Loss: 0.2169 | Spent: 3.9 secs | LR: 0.000189
INFO:tensorflow:Step 18050 | Loss: 0.2180 | Spent: 3.9 secs | LR: 0.000203
INFO:tensorflow:Step 18100 | Loss: 0.2293 | Spent: 3.9 secs | LR: 0.000216
INFO:tensorflow:Step 18150 | Loss: 0.2297 | Spent: 3.9 secs | LR: 0.000230
INFO:tensorflow:Step 18200 | Loss: 0.2267 | Spent: 4.0 secs | LR: 0.000244
INFO:tensorflow:Step 18250 | Loss: 0.2377 | Spent: 4.0 secs | LR: 0.000258
INFO:tensorflow:Step 18300 | Loss: 0.2319 | Spent: 4.0 secs | LR: 0.000272
INFO:tensorflow:Step 18350 | Loss: 0.2462 | Spent: 3.9 secs | LR: 0.000286
INFO:tensorflow:Step 18400 | Loss: 0.2218 | Spent: 3.9 secs | LR: 0.000300
INFO:tensorflow:Step 18450 | Loss: 0.2226 | Spent: 3.9 secs | LR: 0.000313
INFO:tensorflow:Step 18500 | Loss: 0.2296 | Spent: 3.9 secs | LR: 0.000327
INFO:tensorflow:Step 18550 | Loss: 0.2214 | Spent: 3.9 secs | LR: 0.000341
INFO:tensorflow:Step 18600 | Loss: 0.2562 | Spent: 3.9 secs | LR: 0.000355
INFO:tensorflow:Step 18650 | Loss: 0.2463 | Spent: 3.9 secs | LR: 0.000369
INFO:tensorflow:Step 18700 | Loss: 0.2397 | Spent: 3.9 secs | LR: 0.000383
INFO:tensorflow:Step 18750 | Loss: 0.2166 | Spent: 4.0 secs | LR: 0.000397
INFO:tensorflow:Step 18800 | Loss: 0.2217 | Spent: 4.0 secs | LR: 0.000410
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.883| [email protected]: 0.940 | [email protected]: 0.909 | [email protected]: 0.849
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 18850 | Loss: 0.2229 | Spent: 34.6 secs | LR: 0.000424
INFO:tensorflow:Step 18900 | Loss: 0.2206 | Spent: 3.9 secs | LR: 0.000438
INFO:tensorflow:Step 18950 | Loss: 0.2057 | Spent: 3.9 secs | LR: 0.000452
INFO:tensorflow:Step 19000 | Loss: 0.2609 | Spent: 3.9 secs | LR: 0.000466
INFO:tensorflow:Step 19050 | Loss: 0.2128 | Spent: 3.9 secs | LR: 0.000480
INFO:tensorflow:Step 19100 | Loss: 0.2061 | Spent: 3.9 secs | LR: 0.000494
INFO:tensorflow:Step 19150 | Loss: 0.2207 | Spent: 3.9 secs | LR: 0.000507
INFO:tensorflow:Step 19200 | Loss: 0.2342 | Spent: 3.9 secs | LR: 0.000521
INFO:tensorflow:Step 19250 | Loss: 0.2316 | Spent: 3.9 secs | LR: 0.000535
INFO:tensorflow:Step 19300 | Loss: 0.2181 | Spent: 3.9 secs | LR: 0.000549
INFO:tensorflow:Step 19350 | Loss: 0.2296 | Spent: 4.0 secs | LR: 0.000563
INFO:tensorflow:Step 19400 | Loss: 0.2230 | Spent: 3.9 secs | LR: 0.000577
INFO:tensorflow:Step 19450 | Loss: 0.2311 | Spent: 3.9 secs | LR: 0.000591
INFO:tensorflow:Step 19500 | Loss: 0.2389 | Spent: 3.9 secs | LR: 0.000604
INFO:tensorflow:Step 19550 | Loss: 0.2423 | Spent: 3.9 secs | LR: 0.000618
INFO:tensorflow:Step 19600 | Loss: 0.2219 | Spent: 3.9 secs | LR: 0.000632
INFO:tensorflow:Step 19650 | Loss: 0.2241 | Spent: 3.9 secs | LR: 0.000646
INFO:tensorflow:Step 19700 | Loss: 0.2480 | Spent: 3.9 secs | LR: 0.000660
INFO:tensorflow:Step 19750 | Loss: 0.2327 | Spent: 3.9 secs | LR: 0.000674
INFO:tensorflow:Step 19800 | Loss: 0.2315 | Spent: 3.9 secs | LR: 0.000688
INFO:tensorflow:Step 19850 | Loss: 0.2258 | Spent: 3.9 secs | LR: 0.000701
INFO:tensorflow:Step 19900 | Loss: 0.2230 | Spent: 3.9 secs | LR: 0.000715
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.879| [email protected]: 0.937 | [email protected]: 0.909 | [email protected]: 0.844
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 19950 | Loss: 0.2252 | Spent: 34.8 secs | LR: 0.000729
INFO:tensorflow:Step 20000 | Loss: 0.2060 | Spent: 3.9 secs | LR: 0.000743
INFO:tensorflow:Step 20050 | Loss: 0.2352 | Spent: 3.9 secs | LR: 0.000757
INFO:tensorflow:Step 20100 | Loss: 0.2554 | Spent: 3.9 secs | LR: 0.000771
INFO:tensorflow:Step 20150 | Loss: 0.2339 | Spent: 3.9 secs | LR: 0.000785
INFO:tensorflow:Step 20200 | Loss: 0.2203 | Spent: 3.9 secs | LR: 0.000798
INFO:tensorflow:Step 20250 | Loss: 0.2452 | Spent: 3.9 secs | LR: 0.000812
INFO:tensorflow:Step 20300 | Loss: 0.2199 | Spent: 3.9 secs | LR: 0.000826
INFO:tensorflow:Step 20350 | Loss: 0.2281 | Spent: 3.9 secs | LR: 0.000840
INFO:tensorflow:Step 20400 | Loss: 0.2376 | Spent: 3.9 secs | LR: 0.000854
INFO:tensorflow:Step 20450 | Loss: 0.2347 | Spent: 3.9 secs | LR: 0.000868
INFO:tensorflow:Step 20500 | Loss: 0.2216 | Spent: 3.9 secs | LR: 0.000882
INFO:tensorflow:Step 20550 | Loss: 0.2489 | Spent: 3.9 secs | LR: 0.000895
INFO:tensorflow:Step 20600 | Loss: 0.2392 | Spent: 3.9 secs | LR: 0.000909
INFO:tensorflow:Step 20650 | Loss: 0.2168 | Spent: 3.9 secs | LR: 0.000923
INFO:tensorflow:Step 20700 | Loss: 0.2312 | Spent: 3.9 secs | LR: 0.000937
INFO:tensorflow:Step 20750 | Loss: 0.2498 | Spent: 3.9 secs | LR: 0.000951
INFO:tensorflow:Step 20800 | Loss: 0.2197 | Spent: 3.9 secs | LR: 0.000965
INFO:tensorflow:Step 20850 | Loss: 0.2174 | Spent: 3.9 secs | LR: 0.000979
INFO:tensorflow:Step 20900 | Loss: 0.2209 | Spent: 3.9 secs | LR: 0.000992
INFO:tensorflow:Step 20950 | Loss: 0.2200 | Spent: 3.9 secs | LR: 0.001006
INFO:tensorflow:Step 21000 | Loss: 0.2299 | Spent: 3.9 secs | LR: 0.001020
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.877| [email protected]: 0.935 | [email protected]: 0.903 | [email protected]: 0.841
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 21050 | Loss: 0.2258 | Spent: 34.7 secs | LR: 0.001034
INFO:tensorflow:Step 21100 | Loss: 0.2250 | Spent: 3.9 secs | LR: 0.001048
INFO:tensorflow:Step 21150 | Loss: 0.2228 | Spent: 3.9 secs | LR: 0.001062
INFO:tensorflow:Step 21200 | Loss: 0.2415 | Spent: 3.9 secs | LR: 0.001076
INFO:tensorflow:Step 21250 | Loss: 0.2219 | Spent: 3.9 secs | LR: 0.001089
INFO:tensorflow:Step 21300 | Loss: 0.2253 | Spent: 3.9 secs | LR: 0.001103
INFO:tensorflow:Step 21350 | Loss: 0.2489 | Spent: 3.9 secs | LR: 0.001117
INFO:tensorflow:Step 21400 | Loss: 0.2288 | Spent: 3.9 secs | LR: 0.001131
INFO:tensorflow:Step 21450 | Loss: 0.2347 | Spent: 3.9 secs | LR: 0.001145
INFO:tensorflow:Step 21500 | Loss: 0.2254 | Spent: 3.9 secs | LR: 0.001159
INFO:tensorflow:Step 21550 | Loss: 0.2386 | Spent: 3.9 secs | LR: 0.001173
INFO:tensorflow:Step 21600 | Loss: 0.2113 | Spent: 3.9 secs | LR: 0.001186
INFO:tensorflow:Step 21650 | Loss: 0.2330 | Spent: 3.9 secs | LR: 0.001200
INFO:tensorflow:Step 21700 | Loss: 0.2315 | Spent: 3.9 secs | LR: 0.001214
INFO:tensorflow:Step 21750 | Loss: 0.2450 | Spent: 3.9 secs | LR: 0.001228
INFO:tensorflow:Step 21800 | Loss: 0.2384 | Spent: 3.9 secs | LR: 0.001242
INFO:tensorflow:Step 21850 | Loss: 0.2159 | Spent: 3.9 secs | LR: 0.001256
INFO:tensorflow:Step 21900 | Loss: 0.2192 | Spent: 3.9 secs | LR: 0.001270
INFO:tensorflow:Step 21950 | Loss: 0.2277 | Spent: 3.9 secs | LR: 0.001283
INFO:tensorflow:Step 22000 | Loss: 0.2310 | Spent: 3.9 secs | LR: 0.001297
INFO:tensorflow:Step 22050 | Loss: 0.2135 | Spent: 3.9 secs | LR: 0.001311
INFO:tensorflow:Step 22100 | Loss: 0.2167 | Spent: 3.9 secs | LR: 0.001325
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.870| [email protected]: 0.931 | [email protected]: 0.899 | [email protected]: 0.834
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 22150 | Loss: 0.2208 | Spent: 34.6 secs | LR: 0.001339
INFO:tensorflow:Step 22200 | Loss: 0.2339 | Spent: 3.9 secs | LR: 0.001353
INFO:tensorflow:Step 22250 | Loss: 0.2342 | Spent: 3.9 secs | LR: 0.001367
INFO:tensorflow:Step 22300 | Loss: 0.2298 | Spent: 3.9 secs | LR: 0.001380
INFO:tensorflow:Step 22350 | Loss: 0.2369 | Spent: 3.9 secs | LR: 0.001394
INFO:tensorflow:Step 22400 | Loss: 0.2400 | Spent: 3.9 secs | LR: 0.001408
INFO:tensorflow:Step 22450 | Loss: 0.2457 | Spent: 3.9 secs | LR: 0.001422
INFO:tensorflow:Step 22500 | Loss: 0.2323 | Spent: 3.9 secs | LR: 0.001436
INFO:tensorflow:Step 22550 | Loss: 0.2031 | Spent: 3.9 secs | LR: 0.001450
INFO:tensorflow:Step 22600 | Loss: 0.2200 | Spent: 3.9 secs | LR: 0.001464
INFO:tensorflow:Step 22650 | Loss: 0.2535 | Spent: 3.9 secs | LR: 0.001477
INFO:tensorflow:Step 22700 | Loss: 0.2226 | Spent: 3.9 secs | LR: 0.001491
INFO:tensorflow:Step 22750 | Loss: 0.2231 | Spent: 3.9 secs | LR: 0.001505
INFO:tensorflow:Step 22800 | Loss: 0.2360 | Spent: 3.9 secs | LR: 0.001519
INFO:tensorflow:Step 22850 | Loss: 0.2284 | Spent: 4.0 secs | LR: 0.001533
INFO:tensorflow:Step 22900 | Loss: 0.2350 | Spent: 3.9 secs | LR: 0.001547
INFO:tensorflow:Step 22950 | Loss: 0.2417 | Spent: 3.9 secs | LR: 0.001561
INFO:tensorflow:Step 23000 | Loss: 0.2380 | Spent: 3.9 secs | LR: 0.001574
INFO:tensorflow:Step 23050 | Loss: 0.2421 | Spent: 3.9 secs | LR: 0.001588
INFO:tensorflow:Step 23100 | Loss: 0.2415 | Spent: 3.9 secs | LR: 0.001602
INFO:tensorflow:Step 23150 | Loss: 0.2250 | Spent: 3.9 secs | LR: 0.001616
INFO:tensorflow:Step 23200 | Loss: 0.2270 | Spent: 3.9 secs | LR: 0.001630
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.864| [email protected]: 0.929 | [email protected]: 0.893 | [email protected]: 0.826
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 23250 | Loss: 0.2375 | Spent: 34.3 secs | LR: 0.001644
INFO:tensorflow:Step 23300 | Loss: 0.2571 | Spent: 3.9 secs | LR: 0.001658
INFO:tensorflow:Step 23350 | Loss: 0.2330 | Spent: 3.9 secs | LR: 0.001671
INFO:tensorflow:Step 23400 | Loss: 0.2421 | Spent: 3.9 secs | LR: 0.001685
INFO:tensorflow:Step 23450 | Loss: 0.2142 | Spent: 3.9 secs | LR: 0.001699
INFO:tensorflow:Step 23500 | Loss: 0.2303 | Spent: 3.9 secs | LR: 0.001713
INFO:tensorflow:Step 23550 | Loss: 0.2179 | Spent: 3.9 secs | LR: 0.001727
INFO:tensorflow:Step 23600 | Loss: 0.2141 | Spent: 3.9 secs | LR: 0.001741
INFO:tensorflow:Step 23650 | Loss: 0.2316 | Spent: 3.9 secs | LR: 0.001755
INFO:tensorflow:Step 23700 | Loss: 0.2417 | Spent: 3.9 secs | LR: 0.001768
INFO:tensorflow:Step 23750 | Loss: 0.2114 | Spent: 3.9 secs | LR: 0.001782
INFO:tensorflow:Step 23800 | Loss: 0.2394 | Spent: 3.9 secs | LR: 0.001796
INFO:tensorflow:Step 23850 | Loss: 0.2092 | Spent: 3.9 secs | LR: 0.001810
INFO:tensorflow:Step 23900 | Loss: 0.2526 | Spent: 3.9 secs | LR: 0.001824
INFO:tensorflow:Step 23950 | Loss: 0.2266 | Spent: 3.9 secs | LR: 0.001838
INFO:tensorflow:Step 24000 | Loss: 0.2323 | Spent: 3.9 secs | LR: 0.001852
INFO:tensorflow:Step 24050 | Loss: 0.2357 | Spent: 3.9 secs | LR: 0.001865
INFO:tensorflow:Step 24100 | Loss: 0.2514 | Spent: 3.9 secs | LR: 0.001879
INFO:tensorflow:Step 24150 | Loss: 0.2309 | Spent: 3.9 secs | LR: 0.001893
INFO:tensorflow:Step 24200 | Loss: 0.2287 | Spent: 4.0 secs | LR: 0.001907
INFO:tensorflow:Step 24250 | Loss: 0.2305 | Spent: 4.0 secs | LR: 0.001921
INFO:tensorflow:Step 24300 | Loss: 0.2274 | Spent: 3.9 secs | LR: 0.001935
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.856| [email protected]: 0.921 | [email protected]: 0.889 | [email protected]: 0.815
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 24350 | Loss: 0.2256 | Spent: 34.2 secs | LR: 0.001949
INFO:tensorflow:Step 24400 | Loss: 0.2314 | Spent: 3.9 secs | LR: 0.001962
INFO:tensorflow:Step 24450 | Loss: 0.2366 | Spent: 3.9 secs | LR: 0.001976
INFO:tensorflow:Step 24500 | Loss: 0.2415 | Spent: 3.9 secs | LR: 0.001990
INFO:tensorflow:Step 24550 | Loss: 0.2179 | Spent: 3.9 secs | LR: 0.002004
INFO:tensorflow:Step 24600 | Loss: 0.2365 | Spent: 3.9 secs | LR: 0.002018
INFO:tensorflow:Step 24650 | Loss: 0.2293 | Spent: 3.9 secs | LR: 0.002032
INFO:tensorflow:Step 24700 | Loss: 0.2217 | Spent: 3.9 secs | LR: 0.002046
INFO:tensorflow:Step 24750 | Loss: 0.2395 | Spent: 3.9 secs | LR: 0.002059
INFO:tensorflow:Step 24800 | Loss: 0.2297 | Spent: 3.9 secs | LR: 0.002073
INFO:tensorflow:Step 24850 | Loss: 0.2395 | Spent: 3.9 secs | LR: 0.002087
INFO:tensorflow:Step 24900 | Loss: 0.2234 | Spent: 3.9 secs | LR: 0.002101
INFO:tensorflow:Step 24950 | Loss: 0.2238 | Spent: 3.9 secs | LR: 0.002115
INFO:tensorflow:Step 25000 | Loss: 0.2502 | Spent: 3.9 secs | LR: 0.002129
INFO:tensorflow:Step 25050 | Loss: 0.2070 | Spent: 3.9 secs | LR: 0.002143
INFO:tensorflow:Step 25100 | Loss: 0.2176 | Spent: 3.9 secs | LR: 0.002156
INFO:tensorflow:Step 25150 | Loss: 0.2469 | Spent: 3.9 secs | LR: 0.002170
INFO:tensorflow:Step 25200 | Loss: 0.2435 | Spent: 3.9 secs | LR: 0.002184
INFO:tensorflow:Step 25250 | Loss: 0.2349 | Spent: 3.9 secs | LR: 0.002198
INFO:tensorflow:Step 25300 | Loss: 0.2349 | Spent: 3.9 secs | LR: 0.002212
INFO:tensorflow:Step 25350 | Loss: 0.2163 | Spent: 3.9 secs | LR: 0.002226
INFO:tensorflow:Step 25400 | Loss: 0.2329 | Spent: 3.9 secs | LR: 0.002240
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.846| [email protected]: 0.919 | [email protected]: 0.879 | [email protected]: 0.802
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 25450 | Loss: 0.2291 | Spent: 34.5 secs | LR: 0.002253
INFO:tensorflow:Step 25500 | Loss: 0.2235 | Spent: 3.9 secs | LR: 0.002267
INFO:tensorflow:Step 25550 | Loss: 0.2340 | Spent: 3.9 secs | LR: 0.002281
INFO:tensorflow:Step 25600 | Loss: 0.2466 | Spent: 4.0 secs | LR: 0.002295
INFO:tensorflow:Step 25650 | Loss: 0.2229 | Spent: 3.9 secs | LR: 0.002309
INFO:tensorflow:Step 25700 | Loss: 0.2502 | Spent: 3.9 secs | LR: 0.002323
INFO:tensorflow:Step 25750 | Loss: 0.2441 | Spent: 3.9 secs | LR: 0.002337
INFO:tensorflow:Step 25800 | Loss: 0.2376 | Spent: 3.9 secs | LR: 0.002350
INFO:tensorflow:Step 25850 | Loss: 0.2598 | Spent: 3.9 secs | LR: 0.002364
INFO:tensorflow:Step 25900 | Loss: 0.2397 | Spent: 3.9 secs | LR: 0.002378
INFO:tensorflow:Step 25950 | Loss: 0.2369 | Spent: 3.9 secs | LR: 0.002392
INFO:tensorflow:Step 26000 | Loss: 0.2390 | Spent: 3.9 secs | LR: 0.002406
INFO:tensorflow:Step 26050 | Loss: 0.2253 | Spent: 3.9 secs | LR: 0.002420
INFO:tensorflow:Step 26100 | Loss: 0.2153 | Spent: 3.9 secs | LR: 0.002434
INFO:tensorflow:Step 26150 | Loss: 0.2395 | Spent: 3.9 secs | LR: 0.002447
INFO:tensorflow:Step 26200 | Loss: 0.2403 | Spent: 3.9 secs | LR: 0.002461
INFO:tensorflow:Step 26250 | Loss: 0.2461 | Spent: 3.9 secs | LR: 0.002475
INFO:tensorflow:Step 26300 | Loss: 0.2432 | Spent: 3.9 secs | LR: 0.002489
INFO:tensorflow:Step 26350 | Loss: 0.2252 | Spent: 3.9 secs | LR: 0.002503
INFO:tensorflow:Step 26400 | Loss: 0.2671 | Spent: 3.9 secs | LR: 0.002517
INFO:tensorflow:Step 26450 | Loss: 0.2188 | Spent: 3.9 secs | LR: 0.002531
INFO:tensorflow:Step 26500 | Loss: 0.2607 | Spent: 3.9 secs | LR: 0.002544
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.842| [email protected]: 0.915 | [email protected]: 0.874 | [email protected]: 0.798
INFO:tensorflow:Best MRR: 0.885
Reading ../data/wn18/train.txt
INFO:tensorflow:Step 26550 | Loss: 0.2346 | Spent: 34.3 secs | LR: 0.002542
INFO:tensorflow:Step 26600 | Loss: 0.2343 | Spent: 3.9 secs | LR: 0.002528
INFO:tensorflow:Step 26650 | Loss: 0.2397 | Spent: 3.9 secs | LR: 0.002514
INFO:tensorflow:Step 26700 | Loss: 0.2385 | Spent: 3.9 secs | LR: 0.002500
INFO:tensorflow:Step 26750 | Loss: 0.2360 | Spent: 3.9 secs | LR: 0.002486
INFO:tensorflow:Step 26800 | Loss: 0.2231 | Spent: 3.9 secs | LR: 0.002472
INFO:tensorflow:Step 26850 | Loss: 0.2320 | Spent: 3.9 secs | LR: 0.002459
INFO:tensorflow:Step 26900 | Loss: 0.2483 | Spent: 3.9 secs | LR: 0.002445
INFO:tensorflow:Step 26950 | Loss: 0.2307 | Spent: 3.9 secs | LR: 0.002431
INFO:tensorflow:Step 27000 | Loss: 0.2539 | Spent: 4.0 secs | LR: 0.002417
INFO:tensorflow:Step 27050 | Loss: 0.2277 | Spent: 4.0 secs | LR: 0.002403
INFO:tensorflow:Step 27100 | Loss: 0.2284 | Spent: 4.0 secs | LR: 0.002389
INFO:tensorflow:Step 27150 | Loss: 0.2236 | Spent: 3.9 secs | LR: 0.002375
INFO:tensorflow:Step 27200 | Loss: 0.2397 | Spent: 3.9 secs | LR: 0.002362
INFO:tensorflow:Step 27250 | Loss: 0.2481 | Spent: 3.9 secs | LR: 0.002348
INFO:tensorflow:Step 27300 | Loss: 0.2339 | Spent: 3.9 secs | LR: 0.002334
INFO:tensorflow:Step 27350 | Loss: 0.2245 | Spent: 3.9 secs | LR: 0.002320
INFO:tensorflow:Step 27400 | Loss: 0.2350 | Spent: 3.9 secs | LR: 0.002306
INFO:tensorflow:Step 27450 | Loss: 0.2324 | Spent: 3.9 secs | LR: 0.002292
INFO:tensorflow:Step 27500 | Loss: 0.2562 | Spent: 3.9 secs | LR: 0.002278
INFO:tensorflow:Step 27550 | Loss: 0.2393 | Spent: 3.9 secs | LR: 0.002265
INFO:tensorflow:Step 27600 | Loss: 0.2452 | Spent: 3.9 secs | LR: 0.002251
Reading ../data/wn18/test.txt
INFO:tensorflow:MRR: 0.853| [email protected]: 0.922 | [email protected]: 0.885 | [email protected]: 0.812
INFO:tensorflow:Best MRR: 0.885
10 times not improve the best result, therefore stop training