In [ ]:
from google.colab import drive
drive.mount('/content/gdrive')
import os
os.chdir('/content/gdrive/My Drive/finch/tensorflow2/spoken_language_understanding/atis/main')
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
from sklearn.metrics import classification_report, f1_score, accuracy_score

import tensorflow as tf
import pprint
import logging
import time
import numpy as np

print("TensorFlow Version", tf.__version__)
print('GPU Enabled:', tf.test.is_gpu_available())
TensorFlow Version 2.3.0
WARNING:tensorflow:From <ipython-input-3-27b53cc52b5d>:11: 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 [4]:
def get_vocab(vocab_path):
  word2idx = {}
  with open(vocab_path) as f:
    for i, line in enumerate(f):
      line = line.rstrip()
      word2idx[line] = i
  return word2idx
In [5]:
def data_generator(f_path, params):
  print('Reading', f_path)
  with open(f_path) as f:
    for line in f:
      line = line.rstrip()
      text, slot_intent = line.split('\t')
      words = text.split()[1:-1]
      slot_intent = slot_intent.split()
      slots, intent = slot_intent[1:-1], slot_intent[-1]
      assert len(words) == len(slots)
      
      words = [params['word2idx'].get(w, len(params['word2idx'])) for w in words]
      intent = params['intent2idx'].get(intent, len(params['intent2idx']))
      slots = [params['slot2idx'].get(s, len(params['slot2idx'])) for s in slots]
      
      yield (words, (intent, slots))
In [6]:
def dataset(is_training, params):
  _shapes = ([None], ((), [None]))
  _types = (tf.int32, (tf.int32, tf.int32))
  _pads = (0, (-1, 0))
  
  if is_training:
    ds = tf.data.Dataset.from_generator(
      lambda: data_generator(params['train_path'], params),
      output_shapes = _shapes,
      output_types = _types,)
    ds = ds.shuffle(params['num_samples'])
    ds = ds.padded_batch(params['batch_size'], _shapes, _pads)
    ds = ds.prefetch(tf.data.experimental.AUTOTUNE)
  else:
    ds = tf.data.Dataset.from_generator(
      lambda: data_generator(params['test_path'], params),
      output_shapes = _shapes,
      output_types = _types,)
    ds = ds.padded_batch(params['batch_size'], _shapes, _pads)
    ds = ds.prefetch(tf.data.experimental.AUTOTUNE)
  
  return ds
In [7]:
def get_timing_signal_1d(length,
                         channels,
                         min_timescale=1.0,
                         max_timescale=1.0e4,
                         start_index=0):
  to_float = lambda x: tf.cast(x, tf.float32)
  position = to_float(tf.range(length) + start_index)
  num_timescales = channels // 2
  log_timescale_increment = (
      tf.math.log(float(max_timescale) / float(min_timescale)) /
      tf.maximum(to_float(num_timescales) - 1, 1))
  inv_timescales = min_timescale * tf.exp(
      to_float(tf.range(num_timescales)) * -log_timescale_increment)
  scaled_time = tf.expand_dims(position, 1) * tf.expand_dims(inv_timescales, 0)
  signal = tf.concat([tf.sin(scaled_time), tf.cos(scaled_time)], axis=1)
  signal = tf.pad(signal, [[0, 0], [0, tf.compat.v1.mod(channels, 2)]])
  signal = tf.reshape(signal, [1, length, channels])
  return signal
In [8]:
class LayerNorm(tf.keras.layers.Layer):
  def __init__(self, params):
    super().__init__()
    self._epsilon = params['epsilon']
    self._hidden_units = params['global_units']
  
  def build(self, input_shape):
    self.scale = self.add_weight(name='scale',
                                 shape=[self._hidden_units],
                                 initializer=tf.ones_initializer(),
                                 trainable=True)
    self.bias = self.add_weight(name='bias',
                                shape=[self._hidden_units],
                                initializer=tf.zeros_initializer(),
                                trainable=True)
    super().build(input_shape)
  
  def call(self, inputs):
    mean, variance = tf.nn.moments(inputs, [-1], keepdims=True)
    norm_x = (inputs - mean) * tf.math.rsqrt(variance + self._epsilon)
    return norm_x * self.scale + self.bias
  
  def compute_output_shape(self, input_shape):
    return input_shape


class EncoderBlock(tf.keras.Model):
  def __init__(self, SubModel, params, name):
    super().__init__(name = name)
    self.layer_norm = LayerNorm(params)
    self.sub_model = SubModel(params)
    self.dropout = tf.keras.layers.Dropout(params['dropout_rate'])
  
  def call(self, inputs, training):
    inputs, masks = inputs
    x = self.layer_norm(inputs)
    x = self.sub_model((x, masks), training=training)
    x = self.dropout(x, training=training)
    x += inputs
    return x


class MultiheadSelfAttention(tf.keras.Model):
  def __init__(self, params):
    super().__init__()
    self.qkv_linear = tf.keras.layers.Dense(3*params['hidden_units'], name='qkv_linear')
    self.dropout = tf.keras.layers.Dropout(params['dropout_rate'])
    self.out_linear = tf.keras.layers.Dense(params['global_units'], params['activation'], name='out_linear')
    self.num_heads = params['num_heads']
    self.is_bidirectional = params['is_bidirectional']
  
  def call(self, inputs, training):
    x, masks = inputs
    timesteps = tf.shape(x)[1]
    
    q_k_v = self.qkv_linear(x)
    q, k, v = tf.split(q_k_v, 3, axis=-1)
    
    if self.num_heads > 1:
      q = tf.concat(tf.split(q, self.num_heads, axis=2), axis=0)                        
      k = tf.concat(tf.split(k, self.num_heads, axis=2), axis=0)                        
      v = tf.concat(tf.split(v, self.num_heads, axis=2), axis=0)
    
    align = tf.matmul(q, k, transpose_b=True)
    align *= tf.math.rsqrt(tf.cast(k.shape[-1], tf.float32))
    
    if (masks is not None) or (not self.is_bidirectional):
      paddings = tf.fill(tf.shape(align), float('-inf'))
    
    if masks is not None:
      c_masks = tf.tile(masks, [params['num_heads'], 1])
      c_masks = tf.tile(tf.expand_dims(c_masks, 1), [1, timesteps, 1])
      align = tf.where(tf.equal(c_masks, 0), paddings, align)
    
    if not self.is_bidirectional:
      lower_tri = tf.ones((timesteps, timesteps))                                       
      lower_tri = tf.linalg.LinearOperatorLowerTriangular(lower_tri).to_dense()      
      t_masks = tf.tile(tf.expand_dims(lower_tri, 0), [tf.shape(align)[0], 1, 1])     
      align = tf.where(tf.equal(t_masks, 0), paddings, align)
    
    align = tf.nn.softmax(align)
    align = self.dropout(align, training=training)
    
    if masks is not None:
      q_masks = tf.tile(masks, [params['num_heads'], 1])
      q_masks = tf.tile(tf.expand_dims(q_masks, 2), [1, 1, timesteps])
      align *= tf.cast(q_masks, tf.float32)
    
    x = tf.matmul(align, v)
    if self.num_heads > 1:
      x = tf.concat(tf.split(x, self.num_heads, axis=0), axis=2)
    x = self.out_linear(x)
    
    return x
  

class PointwiseFFN(tf.keras.Model):
  def __init__(self, params):
    super().__init__()
    self.dense_1 = tf.keras.layers.Dense(params['multiplier']*params['global_units'], params['activation'], name='fc')
    self.dropout = tf.keras.layers.Dropout(params['dropout_rate'])
    self.dense_2 = tf.keras.layers.Dense(params['global_units'], name='linear')
  
  def call(self, inputs, training):
    x, masks = inputs
    return self.dense_2(self.dropout(self.dense_1(x), training=training))
In [9]:
class Model(tf.keras.Model):
  def __init__(self, params: dict):
    super().__init__()
    self.embedding = tf.Variable(np.load(params['vocab_path']),
                                 dtype=tf.float32,
                                 name='pretrained_embedding')
    self.input_dropout = tf.keras.layers.Dropout(params['dropout_rate'])
    
    self.blocks = []
    for i in range(params['num_layers']):
      self.blocks.append(EncoderBlock(
          MultiheadSelfAttention, params, name='layer{}.1'.format(i+1)))
      self.blocks.append(EncoderBlock(
          PointwiseFFN, params, name='layer{}.2'.format(i+1)))
    
    self.intent_dropout = tf.keras.layers.Dropout(params['dropout_rate'])
    self.fc_intent = tf.keras.layers.Dense(params['global_units'], params['activation'], name='fc_intent')
    self.out_linear_intent = tf.keras.layers.Dense(params['intent_size'], name='output_intent')
    self.out_linear_slot = tf.keras.layers.Dense(params['slot_size'], name='output_slot')
    
  
  def call(self, inputs, training):
    if inputs.dtype != tf.int32:
      inputs = tf.cast(inputs, tf.int32)
    masks = tf.sign(inputs)
    
    x = tf.nn.embedding_lookup(self.embedding, inputs)
    if params['is_embedding_scaled']:
      x *= tf.sqrt(tf.cast(params['global_units'], tf.float32))
    x += get_timing_signal_1d(tf.shape(x)[1], params['global_units'])
    x = self.input_dropout(x, training=training)
    
    for block in self.blocks:
      x = block((x, masks), training=training)
    
    x_intent = tf.reduce_max(x, 1)
    x_intent = self.intent_dropout(x_intent, training=training)
    x_intent = self.out_linear_intent(self.fc_intent(x_intent))
    x_slot = self.out_linear_slot(x)
    return (x_intent, x_slot)
In [10]:
params = {
  'train_path': '../data/atis.train.w-intent.iob',
  'test_path': '../data/atis.test.w-intent.iob',
  'word_path': '../vocab/word.txt',
  'vocab_path': '../vocab/word.npy',
  'intent_path': '../vocab/intent.txt',
  'slot_path': '../vocab/slot.txt',
  'batch_size': 16,
  'num_samples': 4978,
  'num_layers': 2,
  'global_units': 300,
  'hidden_units': 512,
  'activation': tf.nn.elu,
  'num_heads': 8,
  'multiplier': 2,
  'dropout_rate': .1,
  'epsilon': 1e-6,
  'is_bidirectional': True,
  'is_embedding_scaled': False,
  'clip_norm': 5.,
}
In [11]:
params['word2idx'] = get_vocab(params['word_path'])
params['intent2idx'] = get_vocab(params['intent_path'])
params['slot2idx'] = get_vocab(params['slot_path'])

params['word_size'] = len(params['word2idx']) + 1
params['intent_size'] = len(params['intent2idx']) + 1
params['slot_size'] = len(params['slot2idx']) + 1
In [12]:
model = Model(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 = 1e-4,
  maximal_learning_rate = 8e-4,
  step_size = 8 * params['num_samples'] // params['batch_size'],
)
optim = tf.optimizers.Adam(1e-4)
global_step = 0

slot_best_f1 = .0
intent_acc_with_that = .0

t0 = time.time()
logger = logging.getLogger('tensorflow')
logger.setLevel(logging.INFO)

for n_epoch in range(1, 64+1):
  # TRAINING
  for (words, (intent, slots)) in dataset(is_training=True, params=params):
    with tf.GradientTape() as tape:
      y_intent, y_slots = model(words, training=True)
      loss_intent = tf.compat.v1.losses.softmax_cross_entropy(
        onehot_labels = tf.one_hot(intent, len(params['intent2idx'])+1),
        logits = y_intent,
        label_smoothing = .2)
      # weight of 'O' is set to be small
      weights = tf.cast(tf.sign(slots), tf.float32)
      padding = tf.constant(1e-2, tf.float32, weights.shape)
      weights = tf.where(tf.equal(weights, 0.), padding, weights)

      loss_slots = tf.compat.v1.losses.softmax_cross_entropy(
        onehot_labels = tf.one_hot(slots, len(params['slot2idx'])+1),
        logits = y_slots,
        weights = tf.cast(weights, tf.float32),
        label_smoothing = .2)
      # joint loss
      loss = loss_intent + loss_slots
    
    optim.lr.assign(decay_lr(global_step))
    grads = tape.gradient(loss, model.trainable_variables)
    grads, _ = tf.clip_by_global_norm(grads, params['clip_norm'])
    optim.apply_gradients(zip(grads, model.trainable_variables))

    if global_step % 50 == 0:
      logger.info("Step {} | Loss: {:.4f} | Loss_intent: {:.4f} | Loss_slots: {:.4f} | Spent: {:.1f} secs | LR: {:.6f}".format(
          global_step, loss.numpy().item(), loss_intent.numpy().item(), loss_slots.numpy().item(), time.time()-t0, optim.lr.numpy().item()))
      t0 = time.time()
    global_step += 1
    
  # EVALUATION
  intent_true = []
  intent_pred = []
  slot_true = []
  slot_pred = []

  for (words, (intent, slots)) in dataset(is_training=False, params=params):
    y_intent, y_slots = model(words, training=False)
    y_intent = tf.argmax(y_intent, -1)
    y_slots = tf.argmax(y_slots, -1)
    
    intent_true += intent.numpy().flatten().tolist()
    intent_pred += y_intent.numpy().flatten().tolist()
    slot_true += slots.numpy().flatten().tolist()
    slot_pred += y_slots.numpy().flatten().tolist()
    
  f1_slots = f1_score(y_true = slot_true,
                      y_pred = slot_pred,
                      labels = list(params['slot2idx'].values()),
                      sample_weight = np.sign(slot_true),
                      average='micro',)
  
  acc_intent = accuracy_score(intent_true, intent_pred)

  logger.info("Slot F1: {:.3f}, Intent Acc: {:.3f}".format(f1_slots, acc_intent))

  if n_epoch != 1 and n_epoch % 8 == 0:
    logger.info('\n'+classification_report(y_true = intent_true,
                                          y_pred = intent_pred,
                                          labels = list(params['intent2idx'].values()),
                                          target_names = list(params['intent2idx'].keys()),
                                          digits=3))
    logger.info('\n'+classification_report(y_true = slot_true,
                                          y_pred = slot_pred,
                                          labels = list(params['slot2idx'].values()),
                                          target_names = list(params['slot2idx'].keys()),
                                          sample_weight = np.sign(slot_true),
                                          digits=3))
  
  if f1_slots > slot_best_f1:
    slot_best_f1 = f1_slots
    intent_acc_with_that = acc_intent
    # you can save model here
  logger.info("Best Slot F1: {:.3f}, Intent Acc: {:.3f}".format(slot_best_f1, intent_acc_with_that))
[('layer1.1/layer_norm/scale:0', TensorShape([300])),
 ('layer1.1/layer_norm/bias:0', TensorShape([300])),
 ('layer1.1/multihead_self_attention/qkv_linear/kernel:0',
  TensorShape([300, 1536])),
 ('layer1.1/multihead_self_attention/qkv_linear/bias:0', TensorShape([1536])),
 ('layer1.1/multihead_self_attention/out_linear/kernel:0',
  TensorShape([512, 300])),
 ('layer1.1/multihead_self_attention/out_linear/bias:0', TensorShape([300])),
 ('layer1.2/layer_norm_1/scale:0', TensorShape([300])),
 ('layer1.2/layer_norm_1/bias:0', TensorShape([300])),
 ('layer1.2/pointwise_ffn/fc/kernel:0', TensorShape([300, 600])),
 ('layer1.2/pointwise_ffn/fc/bias:0', TensorShape([600])),
 ('layer1.2/pointwise_ffn/linear/kernel:0', TensorShape([600, 300])),
 ('layer1.2/pointwise_ffn/linear/bias:0', TensorShape([300])),
 ('layer2.1/layer_norm_2/scale:0', TensorShape([300])),
 ('layer2.1/layer_norm_2/bias:0', TensorShape([300])),
 ('layer2.1/multihead_self_attention_1/qkv_linear/kernel:0',
  TensorShape([300, 1536])),
 ('layer2.1/multihead_self_attention_1/qkv_linear/bias:0', TensorShape([1536])),
 ('layer2.1/multihead_self_attention_1/out_linear/kernel:0',
  TensorShape([512, 300])),
 ('layer2.1/multihead_self_attention_1/out_linear/bias:0', TensorShape([300])),
 ('layer2.2/layer_norm_3/scale:0', TensorShape([300])),
 ('layer2.2/layer_norm_3/bias:0', TensorShape([300])),
 ('layer2.2/pointwise_ffn_1/fc/kernel:0', TensorShape([300, 600])),
 ('layer2.2/pointwise_ffn_1/fc/bias:0', TensorShape([600])),
 ('layer2.2/pointwise_ffn_1/linear/kernel:0', TensorShape([600, 300])),
 ('layer2.2/pointwise_ffn_1/linear/bias:0', TensorShape([300])),
 ('fc_intent/kernel:0', TensorShape([300, 300])),
 ('fc_intent/bias:0', TensorShape([300])),
 ('output_intent/kernel:0', TensorShape([300, 23])),
 ('output_intent/bias:0', TensorShape([23])),
 ('output_slot/kernel:0', TensorShape([300, 122])),
 ('output_slot/bias:0', TensorShape([122])),
 ('pretrained_embedding:0', TensorShape([750, 300]))]
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 0 | Loss: 7.3419 | Loss_intent: 6.0561 | Loss_slots: 1.2858 | Spent: 3.7 secs | LR: 0.000100
INFO:tensorflow:Step 50 | Loss: 2.3517 | Loss_intent: 1.6495 | Loss_slots: 0.7023 | Spent: 3.0 secs | LR: 0.000114
INFO:tensorflow:Step 100 | Loss: 2.9615 | Loss_intent: 2.0872 | Loss_slots: 0.8743 | Spent: 3.0 secs | LR: 0.000128
INFO:tensorflow:Step 150 | Loss: 2.7355 | Loss_intent: 1.9056 | Loss_slots: 0.8299 | Spent: 3.0 secs | LR: 0.000142
INFO:tensorflow:Step 200 | Loss: 2.4799 | Loss_intent: 1.4809 | Loss_slots: 0.9990 | Spent: 3.0 secs | LR: 0.000156
INFO:tensorflow:Step 250 | Loss: 2.6218 | Loss_intent: 1.9484 | Loss_slots: 0.6734 | Spent: 3.0 secs | LR: 0.000170
INFO:tensorflow:Step 300 | Loss: 1.9150 | Loss_intent: 1.3569 | Loss_slots: 0.5581 | Spent: 3.0 secs | LR: 0.000184
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.589, Intent Acc: 0.877
INFO:tensorflow:Best Slot F1: 0.589, Intent Acc: 0.877
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 350 | Loss: 1.9942 | Loss_intent: 1.4273 | Loss_slots: 0.5668 | Spent: 5.9 secs | LR: 0.000198
INFO:tensorflow:Step 400 | Loss: 2.0493 | Loss_intent: 1.3547 | Loss_slots: 0.6946 | Spent: 3.0 secs | LR: 0.000212
INFO:tensorflow:Step 450 | Loss: 1.6705 | Loss_intent: 1.1696 | Loss_slots: 0.5009 | Spent: 3.0 secs | LR: 0.000227
INFO:tensorflow:Step 500 | Loss: 1.9514 | Loss_intent: 1.3506 | Loss_slots: 0.6008 | Spent: 3.0 secs | LR: 0.000241
INFO:tensorflow:Step 550 | Loss: 2.0775 | Loss_intent: 1.5687 | Loss_slots: 0.5088 | Spent: 3.0 secs | LR: 0.000255
INFO:tensorflow:Step 600 | Loss: 1.7934 | Loss_intent: 1.2595 | Loss_slots: 0.5339 | Spent: 3.0 secs | LR: 0.000269
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.773, Intent Acc: 0.922
INFO:tensorflow:Best Slot F1: 0.773, Intent Acc: 0.922
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 650 | Loss: 1.6983 | Loss_intent: 1.2229 | Loss_slots: 0.4754 | Spent: 5.3 secs | LR: 0.000283
INFO:tensorflow:Step 700 | Loss: 1.9518 | Loss_intent: 1.4447 | Loss_slots: 0.5070 | Spent: 3.0 secs | LR: 0.000297
INFO:tensorflow:Step 750 | Loss: 1.5277 | Loss_intent: 1.1253 | Loss_slots: 0.4024 | Spent: 3.1 secs | LR: 0.000311
INFO:tensorflow:Step 800 | Loss: 2.0177 | Loss_intent: 1.4358 | Loss_slots: 0.5819 | Spent: 3.0 secs | LR: 0.000325
INFO:tensorflow:Step 850 | Loss: 2.0691 | Loss_intent: 1.5938 | Loss_slots: 0.4753 | Spent: 3.0 secs | LR: 0.000339
INFO:tensorflow:Step 900 | Loss: 1.6930 | Loss_intent: 1.1475 | Loss_slots: 0.5455 | Spent: 3.0 secs | LR: 0.000353
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.829, Intent Acc: 0.927
INFO:tensorflow:Best Slot F1: 0.829, Intent Acc: 0.927
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 950 | Loss: 1.6584 | Loss_intent: 1.3878 | Loss_slots: 0.2706 | Spent: 5.4 secs | LR: 0.000367
INFO:tensorflow:Step 1000 | Loss: 1.5867 | Loss_intent: 1.3110 | Loss_slots: 0.2758 | Spent: 3.0 secs | LR: 0.000381
INFO:tensorflow:Step 1050 | Loss: 1.7491 | Loss_intent: 1.2649 | Loss_slots: 0.4842 | Spent: 3.1 secs | LR: 0.000395
INFO:tensorflow:Step 1100 | Loss: 1.6585 | Loss_intent: 1.1530 | Loss_slots: 0.5056 | Spent: 3.0 secs | LR: 0.000409
INFO:tensorflow:Step 1150 | Loss: 1.4725 | Loss_intent: 1.1533 | Loss_slots: 0.3192 | Spent: 3.0 secs | LR: 0.000423
INFO:tensorflow:Step 1200 | Loss: 1.6144 | Loss_intent: 1.1740 | Loss_slots: 0.4404 | Spent: 3.0 secs | LR: 0.000437
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.861, Intent Acc: 0.946
INFO:tensorflow:Best Slot F1: 0.861, Intent Acc: 0.946
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 1250 | Loss: 1.5772 | Loss_intent: 1.1521 | Loss_slots: 0.4251 | Spent: 5.3 secs | LR: 0.000452
INFO:tensorflow:Step 1300 | Loss: 1.5956 | Loss_intent: 1.1998 | Loss_slots: 0.3958 | Spent: 3.0 secs | LR: 0.000466
INFO:tensorflow:Step 1350 | Loss: 1.7940 | Loss_intent: 1.2183 | Loss_slots: 0.5757 | Spent: 3.0 secs | LR: 0.000480
INFO:tensorflow:Step 1400 | Loss: 1.7381 | Loss_intent: 1.1579 | Loss_slots: 0.5802 | Spent: 3.0 secs | LR: 0.000494
INFO:tensorflow:Step 1450 | Loss: 1.4300 | Loss_intent: 1.1313 | Loss_slots: 0.2987 | Spent: 3.0 secs | LR: 0.000508
INFO:tensorflow:Step 1500 | Loss: 1.5272 | Loss_intent: 1.2083 | Loss_slots: 0.3189 | Spent: 3.0 secs | LR: 0.000522
INFO:tensorflow:Step 1550 | Loss: 1.6487 | Loss_intent: 1.1157 | Loss_slots: 0.5330 | Spent: 3.0 secs | LR: 0.000536
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.875, Intent Acc: 0.954
INFO:tensorflow:Best Slot F1: 0.875, Intent Acc: 0.954
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 1600 | Loss: 1.6661 | Loss_intent: 1.1709 | Loss_slots: 0.4952 | Spent: 5.3 secs | LR: 0.000550
INFO:tensorflow:Step 1650 | Loss: 1.9200 | Loss_intent: 1.3686 | Loss_slots: 0.5514 | Spent: 3.0 secs | LR: 0.000564
INFO:tensorflow:Step 1700 | Loss: 1.5944 | Loss_intent: 1.1768 | Loss_slots: 0.4176 | Spent: 3.0 secs | LR: 0.000578
INFO:tensorflow:Step 1750 | Loss: 1.7017 | Loss_intent: 1.1881 | Loss_slots: 0.5136 | Spent: 3.0 secs | LR: 0.000592
INFO:tensorflow:Step 1800 | Loss: 1.7377 | Loss_intent: 1.2228 | Loss_slots: 0.5150 | Spent: 3.0 secs | LR: 0.000606
INFO:tensorflow:Step 1850 | Loss: 1.4614 | Loss_intent: 1.1285 | Loss_slots: 0.3329 | Spent: 3.0 secs | LR: 0.000620
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.896, Intent Acc: 0.959
INFO:tensorflow:Best Slot F1: 0.896, Intent Acc: 0.959
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 1900 | Loss: 1.4691 | Loss_intent: 1.1686 | Loss_slots: 0.3005 | Spent: 5.3 secs | LR: 0.000634
INFO:tensorflow:Step 1950 | Loss: 1.4939 | Loss_intent: 1.1645 | Loss_slots: 0.3294 | Spent: 3.0 secs | LR: 0.000648
INFO:tensorflow:Step 2000 | Loss: 2.0899 | Loss_intent: 1.5826 | Loss_slots: 0.5073 | Spent: 3.0 secs | LR: 0.000662
INFO:tensorflow:Step 2050 | Loss: 1.4631 | Loss_intent: 1.1090 | Loss_slots: 0.3541 | Spent: 3.0 secs | LR: 0.000677
INFO:tensorflow:Step 2100 | Loss: 1.5135 | Loss_intent: 1.1121 | Loss_slots: 0.4014 | Spent: 3.1 secs | LR: 0.000691
INFO:tensorflow:Step 2150 | Loss: 1.5407 | Loss_intent: 1.1020 | Loss_slots: 0.4387 | Spent: 3.0 secs | LR: 0.000705
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.899, Intent Acc: 0.945
INFO:tensorflow:Best Slot F1: 0.899, Intent Acc: 0.945
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 2200 | Loss: 1.4856 | Loss_intent: 1.1275 | Loss_slots: 0.3581 | Spent: 5.4 secs | LR: 0.000719
INFO:tensorflow:Step 2250 | Loss: 1.5691 | Loss_intent: 1.1120 | Loss_slots: 0.4570 | Spent: 3.0 secs | LR: 0.000733
INFO:tensorflow:Step 2300 | Loss: 1.6007 | Loss_intent: 1.1435 | Loss_slots: 0.4572 | Spent: 3.1 secs | LR: 0.000747
INFO:tensorflow:Step 2350 | Loss: 1.6320 | Loss_intent: 1.2335 | Loss_slots: 0.3984 | Spent: 3.1 secs | LR: 0.000761
INFO:tensorflow:Step 2400 | Loss: 1.6252 | Loss_intent: 1.2137 | Loss_slots: 0.4116 | Spent: 3.0 secs | LR: 0.000775
INFO:tensorflow:Step 2450 | Loss: 1.5413 | Loss_intent: 1.1568 | Loss_slots: 0.3845 | Spent: 3.0 secs | LR: 0.000789
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.912, Intent Acc: 0.966
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.978     0.989     0.983       632
                            atis_airfare      0.941     1.000     0.970        48
                     atis_ground_service      1.000     1.000     1.000        36
                            atis_airline      1.000     0.974     0.987        38
                       atis_abbreviation      1.000     0.909     0.952        33
                           atis_aircraft      1.000     1.000     1.000         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.375     1.000     0.545         3
                atis_flight#atis_airfare      0.800     0.333     0.471        12
                            atis_airport      0.941     0.889     0.914        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      0.800     0.667     0.727         6
                        atis_ground_fare      1.000     1.000     1.000         7
                           atis_capacity      1.000     0.952     0.976        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      0.714     0.833     0.769         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.966     0.972     0.969       888
                               macro avg      0.656     0.661     0.647       888
                            weighted avg      0.971     0.972     0.969       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.931     0.996     0.962     716.0
         B-fromloc.city_name      0.971     0.967     0.969     704.0
           I-toloc.city_name      0.892     0.992     0.939     265.0
      B-depart_date.day_name      0.981     0.972     0.976     212.0
              B-airline_name      0.962     0.990     0.976     101.0
         I-fromloc.city_name      0.932     0.927     0.929     177.0
 B-depart_time.period_of_day      0.973     0.831     0.896     130.0
              I-airline_name      0.969     0.969     0.969      65.0
    B-depart_date.day_number      0.930     0.964     0.946      55.0
    B-depart_date.month_name      0.964     0.964     0.964      56.0
          B-depart_time.time      0.740     1.000     0.851      57.0
                B-round_trip      1.000     0.986     0.993      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      0.697     0.958     0.807      24.0
 B-depart_time.time_relative      0.984     0.923     0.952      65.0
          I-depart_time.time      0.875     0.942     0.907      52.0
         B-stoploc.city_name      0.889     0.800     0.842      20.0
                 B-city_name      0.780     0.561     0.653      57.0
                B-class_type      0.920     0.958     0.939      24.0
          B-arrive_time.time      0.660     0.971     0.786      34.0
 B-arrive_time.time_relative      0.853     0.935     0.892      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      1.000     1.000     1.000      21.0
          I-arrive_time.time      0.694     0.971     0.810      35.0
              B-airline_code      0.914     0.941     0.928      34.0
    I-depart_date.day_number      1.000     0.933     0.966      15.0
      I-fromloc.airport_name      0.393     0.733     0.512      15.0
      B-fromloc.airport_name      0.235     0.333     0.276      12.0
      B-arrive_date.day_name      0.556     0.909     0.690      11.0
          B-toloc.state_code      0.947     1.000     0.973      18.0
B-depart_date.today_relative      1.000     0.889     0.941       9.0
             B-flight_number      0.692     0.818     0.750      11.0
 B-depart_date.date_relative      0.850     1.000     0.919      17.0
          B-toloc.state_name      0.735     0.893     0.806      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.545     1.000     0.706       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      1.000     0.276     0.432      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      0.778     0.233     0.359      30.0
        I-toloc.airport_name      0.600     1.000     0.750       3.0
            B-transport_type      0.857     0.600     0.706      10.0
    B-arrive_date.month_name      0.600     0.500     0.545       6.0
    B-arrive_date.day_number      0.714     0.833     0.769       6.0
         I-stoploc.city_name      1.000     0.300     0.462      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     0.957     0.978      23.0
    B-depart_time.period_mod      0.625     1.000     0.769       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     0.333     0.500       3.0
        B-fromloc.state_name      0.769     0.588     0.667      17.0
              B-airport_name      0.833     0.238     0.370      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.848     0.848     0.848      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      1.000     0.333     0.500       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      1.000     1.000     1.000       4.0
    B-arrive_time.start_time      1.000     0.125     0.222       8.0
        B-toloc.airport_code      0.000     0.000     0.000       4.0
      B-arrive_time.end_time      1.000     0.375     0.545       8.0
      I-arrive_time.end_time      0.000     0.000     0.000       8.0
      I-depart_time.end_time      1.000     0.333     0.500       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.714     1.000     0.833       5.0
          I-restriction_code      1.000     0.667     0.800       3.0
    I-depart_time.start_time      0.000     0.000     0.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      0.000     0.000     0.000       2.0
                I-flight_mod      0.000     0.000     0.000       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.000     0.000     0.000       3.0
        I-fromloc.state_name      0.000     0.000     0.000       1.0
                B-state_code      0.000     0.000     0.000       1.0
    I-arrive_time.start_time      0.000     0.000     0.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      0.000     0.000     0.000       1.0
 I-depart_time.period_of_day      0.000     0.000     0.000       1.0
                  B-day_name      0.000     0.000     0.000       2.0
             B-period_of_day      0.000     0.000     0.000       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      0.000     0.000     0.000       1.0
                 B-days_code      1.000     1.000     1.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.000     0.000     0.000       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.911     0.912     0.912    3657.0
                   macro avg      0.530     0.495     0.492    3657.0
                weighted avg      0.906     0.912     0.901    3657.0

INFO:tensorflow:Best Slot F1: 0.912, Intent Acc: 0.966
Reading ../data/atis.train.w-intent.iob
/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.
  _warn_prf(average, modifier, msg_start, len(result))
/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Recall and F-score are ill-defined and being set to 0.0 in labels with no true samples. Use `zero_division` parameter to control this behavior.
  _warn_prf(average, modifier, msg_start, len(result))
INFO:tensorflow:Step 2500 | Loss: 1.4916 | Loss_intent: 1.1554 | Loss_slots: 0.3362 | Spent: 5.4 secs | LR: 0.000797
INFO:tensorflow:Step 2550 | Loss: 1.4946 | Loss_intent: 1.1100 | Loss_slots: 0.3847 | Spent: 3.0 secs | LR: 0.000783
INFO:tensorflow:Step 2600 | Loss: 1.5387 | Loss_intent: 1.0908 | Loss_slots: 0.4479 | Spent: 3.0 secs | LR: 0.000769
INFO:tensorflow:Step 2650 | Loss: 1.6002 | Loss_intent: 1.2698 | Loss_slots: 0.3304 | Spent: 3.0 secs | LR: 0.000755
INFO:tensorflow:Step 2700 | Loss: 1.7967 | Loss_intent: 1.3423 | Loss_slots: 0.4544 | Spent: 3.1 secs | LR: 0.000741
INFO:tensorflow:Step 2750 | Loss: 1.4933 | Loss_intent: 1.2119 | Loss_slots: 0.2814 | Spent: 3.0 secs | LR: 0.000727
INFO:tensorflow:Step 2800 | Loss: 1.4683 | Loss_intent: 1.1160 | Loss_slots: 0.3523 | Spent: 3.0 secs | LR: 0.000713
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.926, Intent Acc: 0.960
INFO:tensorflow:Best Slot F1: 0.926, Intent Acc: 0.960
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 2850 | Loss: 1.5075 | Loss_intent: 1.1481 | Loss_slots: 0.3593 | Spent: 5.4 secs | LR: 0.000698
INFO:tensorflow:Step 2900 | Loss: 1.4590 | Loss_intent: 1.1321 | Loss_slots: 0.3269 | Spent: 3.0 secs | LR: 0.000684
INFO:tensorflow:Step 2950 | Loss: 1.5107 | Loss_intent: 1.1106 | Loss_slots: 0.4001 | Spent: 3.0 secs | LR: 0.000670
INFO:tensorflow:Step 3000 | Loss: 1.5736 | Loss_intent: 1.1213 | Loss_slots: 0.4523 | Spent: 3.0 secs | LR: 0.000656
INFO:tensorflow:Step 3050 | Loss: 1.4956 | Loss_intent: 1.1151 | Loss_slots: 0.3805 | Spent: 3.0 secs | LR: 0.000642
INFO:tensorflow:Step 3100 | Loss: 1.6610 | Loss_intent: 1.2432 | Loss_slots: 0.4177 | Spent: 3.0 secs | LR: 0.000628
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.934, Intent Acc: 0.948
INFO:tensorflow:Best Slot F1: 0.934, Intent Acc: 0.948
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 3150 | Loss: 1.3824 | Loss_intent: 1.1168 | Loss_slots: 0.2656 | Spent: 5.4 secs | LR: 0.000614
INFO:tensorflow:Step 3200 | Loss: 1.4110 | Loss_intent: 1.0967 | Loss_slots: 0.3144 | Spent: 3.0 secs | LR: 0.000600
INFO:tensorflow:Step 3250 | Loss: 1.5473 | Loss_intent: 1.1925 | Loss_slots: 0.3548 | Spent: 3.0 secs | LR: 0.000586
INFO:tensorflow:Step 3300 | Loss: 1.5251 | Loss_intent: 1.1287 | Loss_slots: 0.3964 | Spent: 3.0 secs | LR: 0.000572
INFO:tensorflow:Step 3350 | Loss: 1.4888 | Loss_intent: 1.1094 | Loss_slots: 0.3794 | Spent: 3.0 secs | LR: 0.000558
INFO:tensorflow:Step 3400 | Loss: 1.3622 | Loss_intent: 1.0861 | Loss_slots: 0.2761 | Spent: 3.0 secs | LR: 0.000544
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.934, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.934, Intent Acc: 0.966
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 3450 | Loss: 1.3417 | Loss_intent: 1.0915 | Loss_slots: 0.2502 | Spent: 5.4 secs | LR: 0.000530
INFO:tensorflow:Step 3500 | Loss: 1.4744 | Loss_intent: 1.0958 | Loss_slots: 0.3787 | Spent: 3.0 secs | LR: 0.000516
INFO:tensorflow:Step 3550 | Loss: 1.6154 | Loss_intent: 1.1990 | Loss_slots: 0.4165 | Spent: 3.0 secs | LR: 0.000502
INFO:tensorflow:Step 3600 | Loss: 1.4448 | Loss_intent: 1.0905 | Loss_slots: 0.3543 | Spent: 3.0 secs | LR: 0.000488
INFO:tensorflow:Step 3650 | Loss: 1.3684 | Loss_intent: 1.0972 | Loss_slots: 0.2712 | Spent: 3.0 secs | LR: 0.000473
INFO:tensorflow:Step 3700 | Loss: 1.6293 | Loss_intent: 1.0903 | Loss_slots: 0.5390 | Spent: 3.0 secs | LR: 0.000459
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.939, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.939, Intent Acc: 0.966
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 3750 | Loss: 1.4098 | Loss_intent: 1.0839 | Loss_slots: 0.3259 | Spent: 5.3 secs | LR: 0.000445
INFO:tensorflow:Step 3800 | Loss: 1.3770 | Loss_intent: 1.0869 | Loss_slots: 0.2901 | Spent: 3.0 secs | LR: 0.000431
INFO:tensorflow:Step 3850 | Loss: 1.6321 | Loss_intent: 1.2401 | Loss_slots: 0.3920 | Spent: 3.0 secs | LR: 0.000417
INFO:tensorflow:Step 3900 | Loss: 1.4306 | Loss_intent: 1.0873 | Loss_slots: 0.3434 | Spent: 3.0 secs | LR: 0.000403
INFO:tensorflow:Step 3950 | Loss: 1.4473 | Loss_intent: 1.0918 | Loss_slots: 0.3556 | Spent: 3.0 secs | LR: 0.000389
INFO:tensorflow:Step 4000 | Loss: 1.4844 | Loss_intent: 1.0840 | Loss_slots: 0.4003 | Spent: 3.0 secs | LR: 0.000375
INFO:tensorflow:Step 4050 | Loss: 1.3141 | Loss_intent: 1.0880 | Loss_slots: 0.2260 | Spent: 3.0 secs | LR: 0.000361
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.939, Intent Acc: 0.970
INFO:tensorflow:Best Slot F1: 0.939, Intent Acc: 0.966
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 4100 | Loss: 1.5467 | Loss_intent: 1.1409 | Loss_slots: 0.4058 | Spent: 5.3 secs | LR: 0.000347
INFO:tensorflow:Step 4150 | Loss: 1.5214 | Loss_intent: 1.0891 | Loss_slots: 0.4323 | Spent: 3.0 secs | LR: 0.000333
INFO:tensorflow:Step 4200 | Loss: 1.5017 | Loss_intent: 1.0858 | Loss_slots: 0.4159 | Spent: 3.0 secs | LR: 0.000319
INFO:tensorflow:Step 4250 | Loss: 1.4322 | Loss_intent: 1.0865 | Loss_slots: 0.3457 | Spent: 3.0 secs | LR: 0.000305
INFO:tensorflow:Step 4300 | Loss: 1.2758 | Loss_intent: 1.0840 | Loss_slots: 0.1918 | Spent: 3.0 secs | LR: 0.000291
INFO:tensorflow:Step 4350 | Loss: 1.4703 | Loss_intent: 1.0847 | Loss_slots: 0.3856 | Spent: 3.0 secs | LR: 0.000277
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.943, Intent Acc: 0.972
INFO:tensorflow:Best Slot F1: 0.943, Intent Acc: 0.972
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 4400 | Loss: 1.5113 | Loss_intent: 1.0837 | Loss_slots: 0.4276 | Spent: 5.5 secs | LR: 0.000263
INFO:tensorflow:Step 4450 | Loss: 1.5359 | Loss_intent: 1.0840 | Loss_slots: 0.4519 | Spent: 3.2 secs | LR: 0.000248
INFO:tensorflow:Step 4500 | Loss: 1.5226 | Loss_intent: 1.0829 | Loss_slots: 0.4397 | Spent: 3.2 secs | LR: 0.000234
INFO:tensorflow:Step 4550 | Loss: 1.4555 | Loss_intent: 1.0884 | Loss_slots: 0.3672 | Spent: 3.2 secs | LR: 0.000220
INFO:tensorflow:Step 4600 | Loss: 1.4084 | Loss_intent: 1.0859 | Loss_slots: 0.3225 | Spent: 3.0 secs | LR: 0.000206
INFO:tensorflow:Step 4650 | Loss: 1.3888 | Loss_intent: 1.0857 | Loss_slots: 0.3032 | Spent: 3.0 secs | LR: 0.000192
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.948, Intent Acc: 0.970
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 4700 | Loss: 1.4747 | Loss_intent: 1.0884 | Loss_slots: 0.3863 | Spent: 5.3 secs | LR: 0.000178
INFO:tensorflow:Step 4750 | Loss: 1.4200 | Loss_intent: 1.0882 | Loss_slots: 0.3318 | Spent: 3.0 secs | LR: 0.000164
INFO:tensorflow:Step 4800 | Loss: 1.4354 | Loss_intent: 1.0857 | Loss_slots: 0.3497 | Spent: 3.0 secs | LR: 0.000150
INFO:tensorflow:Step 4850 | Loss: 1.2773 | Loss_intent: 1.0837 | Loss_slots: 0.1935 | Spent: 3.0 secs | LR: 0.000136
INFO:tensorflow:Step 4900 | Loss: 1.3334 | Loss_intent: 1.0881 | Loss_slots: 0.2453 | Spent: 3.0 secs | LR: 0.000122
INFO:tensorflow:Step 4950 | Loss: 1.3998 | Loss_intent: 1.0979 | Loss_slots: 0.3020 | Spent: 3.1 secs | LR: 0.000108
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.945, Intent Acc: 0.969
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.980     0.989     0.984       632
                            atis_airfare      0.979     0.979     0.979        48
                     atis_ground_service      0.973     1.000     0.986        36
                            atis_airline      1.000     1.000     1.000        38
                       atis_abbreviation      0.970     0.970     0.970        33
                           atis_aircraft      1.000     0.889     0.941         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.200     0.333     0.250         3
                atis_flight#atis_airfare      0.833     0.417     0.556        12
                            atis_airport      0.900     1.000     0.947        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     0.857     0.923         7
                           atis_capacity      0.913     1.000     0.955        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      0.833     0.833     0.833         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.969     0.974     0.971       888
                               macro avg      0.658     0.633     0.639       888
                            weighted avg      0.971     0.974     0.971       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.970     0.997     0.983     716.0
         B-fromloc.city_name      0.987     0.990     0.989     704.0
           I-toloc.city_name      0.971     1.000     0.985     265.0
      B-depart_date.day_name      0.986     0.981     0.983     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.972     0.994     0.983     177.0
 B-depart_time.period_of_day      0.958     0.877     0.916     130.0
              I-airline_name      0.985     1.000     0.992      65.0
    B-depart_date.day_number      0.946     0.964     0.955      55.0
    B-depart_date.month_name      0.964     0.964     0.964      56.0
          B-depart_time.time      0.838     1.000     0.912      57.0
                B-round_trip      1.000     0.973     0.986      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      1.000     0.958     0.979      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.881     1.000     0.937      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.795     0.544     0.646      57.0
                B-class_type      0.960     1.000     0.980      24.0
          B-arrive_time.time      0.917     0.971     0.943      34.0
 B-arrive_time.time_relative      0.833     0.968     0.896      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      0.955     1.000     0.977      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.853     0.921      34.0
    I-depart_date.day_number      1.000     0.933     0.966      15.0
      I-fromloc.airport_name      0.417     1.000     0.588      15.0
      B-fromloc.airport_name      0.344     0.917     0.500      12.0
      B-arrive_date.day_name      0.667     0.909     0.769      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     0.889     0.941       9.0
             B-flight_number      0.421     0.727     0.533      11.0
 B-depart_date.date_relative      0.850     1.000     0.919      17.0
          B-toloc.state_name      0.900     0.964     0.931      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      1.000     0.310     0.474      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.533     0.696      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      0.909     1.000     0.952      10.0
    B-arrive_date.month_name      0.667     0.667     0.667       6.0
    B-arrive_date.day_number      0.667     0.667     0.667       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.500     0.400     0.444       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     0.333     0.500       3.0
        B-fromloc.state_name      0.941     0.941     0.941      17.0
              B-airport_name      0.857     0.286     0.429      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.938     0.909     0.923      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.800     0.444     0.571       9.0
    B-depart_time.start_time      1.000     0.667     0.800       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      1.000     1.000     1.000       4.0
    B-arrive_time.start_time      0.889     1.000     0.941       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      1.000     1.000     1.000       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      0.500     1.000     0.667       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      1.000     0.500     0.667       2.0
                I-flight_mod      0.000     0.000     0.000       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.000     0.000     0.000       3.0
        I-fromloc.state_name      0.000     0.000     0.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      0.000     0.000     0.000       1.0
 I-depart_time.period_of_day      0.000     0.000     0.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.250     0.400       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      0.000     0.000     0.000       1.0
                 B-days_code      0.500     1.000     0.667       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.000     0.000     0.000       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.944     0.946     0.945    3657.0
                   macro avg      0.614     0.588     0.585    3657.0
                weighted avg      0.949     0.946     0.942    3657.0

INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 5000 | Loss: 1.5065 | Loss_intent: 1.0950 | Loss_slots: 0.4115 | Spent: 5.3 secs | LR: 0.000103
INFO:tensorflow:Step 5050 | Loss: 1.5004 | Loss_intent: 1.0826 | Loss_slots: 0.4178 | Spent: 3.0 secs | LR: 0.000110
INFO:tensorflow:Step 5100 | Loss: 1.4713 | Loss_intent: 1.0919 | Loss_slots: 0.3795 | Spent: 3.0 secs | LR: 0.000117
INFO:tensorflow:Step 5150 | Loss: 1.5438 | Loss_intent: 1.0991 | Loss_slots: 0.4447 | Spent: 3.0 secs | LR: 0.000124
INFO:tensorflow:Step 5200 | Loss: 1.3519 | Loss_intent: 1.0899 | Loss_slots: 0.2620 | Spent: 3.0 secs | LR: 0.000131
INFO:tensorflow:Step 5250 | Loss: 1.3860 | Loss_intent: 1.0933 | Loss_slots: 0.2927 | Spent: 3.0 secs | LR: 0.000138
INFO:tensorflow:Step 5300 | Loss: 1.4895 | Loss_intent: 1.1019 | Loss_slots: 0.3876 | Spent: 3.0 secs | LR: 0.000145
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.946, Intent Acc: 0.969
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 5350 | Loss: 1.4292 | Loss_intent: 1.0918 | Loss_slots: 0.3374 | Spent: 5.3 secs | LR: 0.000152
INFO:tensorflow:Step 5400 | Loss: 1.4454 | Loss_intent: 1.1849 | Loss_slots: 0.2606 | Spent: 3.0 secs | LR: 0.000159
INFO:tensorflow:Step 5450 | Loss: 1.4711 | Loss_intent: 1.0837 | Loss_slots: 0.3874 | Spent: 3.0 secs | LR: 0.000166
INFO:tensorflow:Step 5500 | Loss: 1.3621 | Loss_intent: 1.0882 | Loss_slots: 0.2739 | Spent: 3.0 secs | LR: 0.000173
INFO:tensorflow:Step 5550 | Loss: 1.3858 | Loss_intent: 1.0812 | Loss_slots: 0.3046 | Spent: 3.0 secs | LR: 0.000180
INFO:tensorflow:Step 5600 | Loss: 1.4009 | Loss_intent: 1.0869 | Loss_slots: 0.3141 | Spent: 3.0 secs | LR: 0.000187
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.948, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 5650 | Loss: 1.3467 | Loss_intent: 1.0826 | Loss_slots: 0.2641 | Spent: 5.2 secs | LR: 0.000194
INFO:tensorflow:Step 5700 | Loss: 1.3432 | Loss_intent: 1.0832 | Loss_slots: 0.2600 | Spent: 3.0 secs | LR: 0.000202
INFO:tensorflow:Step 5750 | Loss: 1.3984 | Loss_intent: 1.0855 | Loss_slots: 0.3130 | Spent: 3.0 secs | LR: 0.000209
INFO:tensorflow:Step 5800 | Loss: 1.4171 | Loss_intent: 1.0894 | Loss_slots: 0.3278 | Spent: 3.0 secs | LR: 0.000216
INFO:tensorflow:Step 5850 | Loss: 1.5002 | Loss_intent: 1.0837 | Loss_slots: 0.4165 | Spent: 3.0 secs | LR: 0.000223
INFO:tensorflow:Step 5900 | Loss: 1.3734 | Loss_intent: 1.0820 | Loss_slots: 0.2914 | Spent: 3.0 secs | LR: 0.000230
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.942, Intent Acc: 0.973
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 5950 | Loss: 1.5100 | Loss_intent: 1.1417 | Loss_slots: 0.3683 | Spent: 5.2 secs | LR: 0.000237
INFO:tensorflow:Step 6000 | Loss: 1.4180 | Loss_intent: 1.0924 | Loss_slots: 0.3255 | Spent: 2.9 secs | LR: 0.000244
INFO:tensorflow:Step 6050 | Loss: 1.4805 | Loss_intent: 1.0965 | Loss_slots: 0.3840 | Spent: 2.9 secs | LR: 0.000251
INFO:tensorflow:Step 6100 | Loss: 1.3773 | Loss_intent: 1.0831 | Loss_slots: 0.2942 | Spent: 3.0 secs | LR: 0.000258
INFO:tensorflow:Step 6150 | Loss: 1.3482 | Loss_intent: 1.0839 | Loss_slots: 0.2643 | Spent: 2.9 secs | LR: 0.000265
INFO:tensorflow:Step 6200 | Loss: 1.5669 | Loss_intent: 1.1136 | Loss_slots: 0.4533 | Spent: 3.0 secs | LR: 0.000272
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.948, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 6250 | Loss: 1.5475 | Loss_intent: 1.0882 | Loss_slots: 0.4593 | Spent: 5.3 secs | LR: 0.000279
INFO:tensorflow:Step 6300 | Loss: 1.4326 | Loss_intent: 1.0853 | Loss_slots: 0.3473 | Spent: 3.0 secs | LR: 0.000286
INFO:tensorflow:Step 6350 | Loss: 1.3119 | Loss_intent: 1.0834 | Loss_slots: 0.2286 | Spent: 3.0 secs | LR: 0.000293
INFO:tensorflow:Step 6400 | Loss: 1.4961 | Loss_intent: 1.0919 | Loss_slots: 0.4041 | Spent: 3.0 secs | LR: 0.000300
INFO:tensorflow:Step 6450 | Loss: 1.4545 | Loss_intent: 1.1179 | Loss_slots: 0.3366 | Spent: 3.0 secs | LR: 0.000307
INFO:tensorflow:Step 6500 | Loss: 1.3964 | Loss_intent: 1.0955 | Loss_slots: 0.3009 | Spent: 3.0 secs | LR: 0.000314
INFO:tensorflow:Step 6550 | Loss: 1.3446 | Loss_intent: 1.0811 | Loss_slots: 0.2635 | Spent: 2.9 secs | LR: 0.000321
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.948, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 6600 | Loss: 1.5106 | Loss_intent: 1.1460 | Loss_slots: 0.3646 | Spent: 5.2 secs | LR: 0.000328
INFO:tensorflow:Step 6650 | Loss: 1.5020 | Loss_intent: 1.0918 | Loss_slots: 0.4102 | Spent: 2.9 secs | LR: 0.000335
INFO:tensorflow:Step 6700 | Loss: 1.4707 | Loss_intent: 1.0820 | Loss_slots: 0.3887 | Spent: 3.0 secs | LR: 0.000342
INFO:tensorflow:Step 6750 | Loss: 1.4633 | Loss_intent: 1.0839 | Loss_slots: 0.3793 | Spent: 3.0 secs | LR: 0.000349
INFO:tensorflow:Step 6800 | Loss: 1.5279 | Loss_intent: 1.0905 | Loss_slots: 0.4373 | Spent: 3.0 secs | LR: 0.000356
INFO:tensorflow:Step 6850 | Loss: 1.5430 | Loss_intent: 1.0841 | Loss_slots: 0.4589 | Spent: 3.1 secs | LR: 0.000363
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.945, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 6900 | Loss: 1.5368 | Loss_intent: 1.1096 | Loss_slots: 0.4272 | Spent: 5.4 secs | LR: 0.000370
INFO:tensorflow:Step 6950 | Loss: 1.4241 | Loss_intent: 1.0835 | Loss_slots: 0.3406 | Spent: 3.0 secs | LR: 0.000377
INFO:tensorflow:Step 7000 | Loss: 1.4003 | Loss_intent: 1.1195 | Loss_slots: 0.2808 | Spent: 3.0 secs | LR: 0.000384
INFO:tensorflow:Step 7050 | Loss: 1.3850 | Loss_intent: 1.0856 | Loss_slots: 0.2994 | Spent: 2.9 secs | LR: 0.000391
INFO:tensorflow:Step 7100 | Loss: 1.3852 | Loss_intent: 1.0831 | Loss_slots: 0.3020 | Spent: 2.9 secs | LR: 0.000398
INFO:tensorflow:Step 7150 | Loss: 1.5518 | Loss_intent: 1.0940 | Loss_slots: 0.4578 | Spent: 3.0 secs | LR: 0.000405
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.939, Intent Acc: 0.973
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 7200 | Loss: 1.4102 | Loss_intent: 1.0927 | Loss_slots: 0.3175 | Spent: 5.3 secs | LR: 0.000412
INFO:tensorflow:Step 7250 | Loss: 1.5422 | Loss_intent: 1.1344 | Loss_slots: 0.4079 | Spent: 3.0 secs | LR: 0.000419
INFO:tensorflow:Step 7300 | Loss: 1.4262 | Loss_intent: 1.0829 | Loss_slots: 0.3434 | Spent: 3.0 secs | LR: 0.000427
INFO:tensorflow:Step 7350 | Loss: 1.3612 | Loss_intent: 1.1005 | Loss_slots: 0.2608 | Spent: 2.9 secs | LR: 0.000434
INFO:tensorflow:Step 7400 | Loss: 1.6418 | Loss_intent: 1.2152 | Loss_slots: 0.4266 | Spent: 3.0 secs | LR: 0.000441
INFO:tensorflow:Step 7450 | Loss: 1.4409 | Loss_intent: 1.1029 | Loss_slots: 0.3380 | Spent: 3.0 secs | LR: 0.000448
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.946, Intent Acc: 0.973
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.983     0.991     0.987       632
                            atis_airfare      0.980     1.000     0.990        48
                     atis_ground_service      1.000     1.000     1.000        36
                            atis_airline      1.000     1.000     1.000        38
                       atis_abbreviation      0.970     0.970     0.970        33
                           atis_aircraft      1.000     1.000     1.000         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.333     0.667     0.444         3
                atis_flight#atis_airfare      0.800     0.333     0.471        12
                            atis_airport      0.857     1.000     0.923        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     1.000     1.000         7
                           atis_capacity      0.955     1.000     0.977        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      1.000     0.833     0.909         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.973     0.979     0.976       888
                               macro avg      0.671     0.657     0.655       888
                            weighted avg      0.976     0.979     0.975       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.978     0.994     0.986     716.0
         B-fromloc.city_name      0.980     0.994     0.987     704.0
           I-toloc.city_name      0.978     0.996     0.987     265.0
      B-depart_date.day_name      0.990     0.976     0.983     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.967     0.989     0.978     177.0
 B-depart_time.period_of_day      0.966     0.877     0.919     130.0
              I-airline_name      0.970     1.000     0.985      65.0
    B-depart_date.day_number      0.981     0.927     0.953      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.838     1.000     0.912      57.0
                B-round_trip      1.000     0.973     0.986      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      0.958     0.958     0.958      24.0
 B-depart_time.time_relative      1.000     0.969     0.984      65.0
          I-depart_time.time      0.881     1.000     0.937      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.780     0.684     0.729      57.0
                B-class_type      0.889     1.000     0.941      24.0
          B-arrive_time.time      0.892     0.971     0.930      34.0
 B-arrive_time.time_relative      0.912     1.000     0.954      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      0.955     1.000     0.977      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.824     0.903      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.429     1.000     0.600      15.0
      B-fromloc.airport_name      0.381     0.667     0.485      12.0
      B-arrive_date.day_name      0.647     1.000     0.786      11.0
          B-toloc.state_code      0.947     1.000     0.973      18.0
B-depart_date.today_relative      1.000     0.889     0.941       9.0
             B-flight_number      0.400     0.909     0.556      11.0
 B-depart_date.date_relative      0.882     0.882     0.882      17.0
          B-toloc.state_name      0.964     0.964     0.964      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.667     1.000     0.800       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      1.000     0.310     0.474      29.0
               B-fare_amount      1.000     0.500     0.667       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.567     0.723      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      1.000     0.900     0.947      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.714     0.833     0.769       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     0.957     0.978      23.0
    B-depart_time.period_mod      0.750     0.600     0.667       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     0.333     0.500       3.0
        B-fromloc.state_name      0.895     1.000     0.944      17.0
              B-airport_name      0.875     0.333     0.483      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.867     0.788     0.825      33.0
                       B-mod      0.167     0.500     0.250       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      1.000     0.667     0.800       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      0.571     1.000     0.727       4.0
    B-arrive_time.start_time      0.875     0.875     0.875       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.889     1.000     0.941       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      1.000     1.000     1.000       5.0
          I-restriction_code      1.000     0.667     0.800       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      0.500     1.000     0.667       2.0
                I-flight_mod      0.000     0.000     0.000       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.667     0.667     0.667       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      1.000     1.000     1.000       1.0
 I-depart_time.period_of_day      0.000     0.000     0.000       1.0
                  B-day_name      0.333     0.500     0.400       2.0
             B-period_of_day      1.000     0.250     0.400       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      0.000     0.000     0.000       1.0
                 B-days_code      0.500     1.000     0.667       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.000     0.000     0.000       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.945     0.946     0.946    3657.0
                   macro avg      0.622     0.608     0.600    3657.0
                weighted avg      0.949     0.946     0.942    3657.0

INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 7500 | Loss: 1.3567 | Loss_intent: 1.0946 | Loss_slots: 0.2621 | Spent: 5.4 secs | LR: 0.000445
INFO:tensorflow:Step 7550 | Loss: 1.4298 | Loss_intent: 1.0883 | Loss_slots: 0.3415 | Spent: 3.0 secs | LR: 0.000438
INFO:tensorflow:Step 7600 | Loss: 1.5855 | Loss_intent: 1.1995 | Loss_slots: 0.3861 | Spent: 3.0 secs | LR: 0.000431
INFO:tensorflow:Step 7650 | Loss: 1.4260 | Loss_intent: 1.0959 | Loss_slots: 0.3301 | Spent: 3.0 secs | LR: 0.000424
INFO:tensorflow:Step 7700 | Loss: 1.4953 | Loss_intent: 1.0994 | Loss_slots: 0.3959 | Spent: 3.0 secs | LR: 0.000417
INFO:tensorflow:Step 7750 | Loss: 1.5235 | Loss_intent: 1.0914 | Loss_slots: 0.4320 | Spent: 3.0 secs | LR: 0.000410
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.943, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.948, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 7800 | Loss: 1.4451 | Loss_intent: 1.1671 | Loss_slots: 0.2780 | Spent: 5.2 secs | LR: 0.000403
INFO:tensorflow:Step 7850 | Loss: 1.4689 | Loss_intent: 1.1109 | Loss_slots: 0.3580 | Spent: 3.0 secs | LR: 0.000396
INFO:tensorflow:Step 7900 | Loss: 1.4305 | Loss_intent: 1.1473 | Loss_slots: 0.2832 | Spent: 3.0 secs | LR: 0.000389
INFO:tensorflow:Step 7950 | Loss: 1.4016 | Loss_intent: 1.1070 | Loss_slots: 0.2947 | Spent: 3.0 secs | LR: 0.000382
INFO:tensorflow:Step 8000 | Loss: 1.5108 | Loss_intent: 1.0844 | Loss_slots: 0.4264 | Spent: 3.0 secs | LR: 0.000375
INFO:tensorflow:Step 8050 | Loss: 1.4724 | Loss_intent: 1.0925 | Loss_slots: 0.3799 | Spent: 3.0 secs | LR: 0.000368
INFO:tensorflow:Step 8100 | Loss: 1.4900 | Loss_intent: 1.0864 | Loss_slots: 0.4036 | Spent: 3.0 secs | LR: 0.000361
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.970
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 8150 | Loss: 1.4692 | Loss_intent: 1.0840 | Loss_slots: 0.3852 | Spent: 5.3 secs | LR: 0.000354
INFO:tensorflow:Step 8200 | Loss: 1.5082 | Loss_intent: 1.0830 | Loss_slots: 0.4252 | Spent: 3.0 secs | LR: 0.000347
INFO:tensorflow:Step 8250 | Loss: 1.5074 | Loss_intent: 1.0942 | Loss_slots: 0.4132 | Spent: 3.0 secs | LR: 0.000340
INFO:tensorflow:Step 8300 | Loss: 1.4098 | Loss_intent: 1.0895 | Loss_slots: 0.3203 | Spent: 3.0 secs | LR: 0.000333
INFO:tensorflow:Step 8350 | Loss: 1.6221 | Loss_intent: 1.1061 | Loss_slots: 0.5160 | Spent: 3.0 secs | LR: 0.000326
INFO:tensorflow:Step 8400 | Loss: 1.5228 | Loss_intent: 1.0841 | Loss_slots: 0.4387 | Spent: 3.0 secs | LR: 0.000319
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.947, Intent Acc: 0.960
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 8450 | Loss: 1.4232 | Loss_intent: 1.0837 | Loss_slots: 0.3395 | Spent: 5.2 secs | LR: 0.000312
INFO:tensorflow:Step 8500 | Loss: 1.3526 | Loss_intent: 1.0838 | Loss_slots: 0.2687 | Spent: 3.0 secs | LR: 0.000305
INFO:tensorflow:Step 8550 | Loss: 1.4882 | Loss_intent: 1.0825 | Loss_slots: 0.4057 | Spent: 3.0 secs | LR: 0.000298
INFO:tensorflow:Step 8600 | Loss: 1.4326 | Loss_intent: 1.0851 | Loss_slots: 0.3475 | Spent: 3.0 secs | LR: 0.000291
INFO:tensorflow:Step 8650 | Loss: 1.4432 | Loss_intent: 1.0818 | Loss_slots: 0.3614 | Spent: 3.0 secs | LR: 0.000284
INFO:tensorflow:Step 8700 | Loss: 1.4014 | Loss_intent: 1.0807 | Loss_slots: 0.3207 | Spent: 2.9 secs | LR: 0.000277
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.949, Intent Acc: 0.957
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 8750 | Loss: 1.4583 | Loss_intent: 1.0911 | Loss_slots: 0.3673 | Spent: 5.2 secs | LR: 0.000270
INFO:tensorflow:Step 8800 | Loss: 1.3810 | Loss_intent: 1.0832 | Loss_slots: 0.2979 | Spent: 3.0 secs | LR: 0.000263
INFO:tensorflow:Step 8850 | Loss: 1.3719 | Loss_intent: 1.0836 | Loss_slots: 0.2883 | Spent: 3.0 secs | LR: 0.000256
INFO:tensorflow:Step 8900 | Loss: 1.4740 | Loss_intent: 1.0872 | Loss_slots: 0.3868 | Spent: 2.9 secs | LR: 0.000248
INFO:tensorflow:Step 8950 | Loss: 1.4001 | Loss_intent: 1.0925 | Loss_slots: 0.3075 | Spent: 3.0 secs | LR: 0.000241
INFO:tensorflow:Step 9000 | Loss: 1.3091 | Loss_intent: 1.0821 | Loss_slots: 0.2270 | Spent: 3.0 secs | LR: 0.000234
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.951, Intent Acc: 0.961
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 9050 | Loss: 1.3637 | Loss_intent: 1.0899 | Loss_slots: 0.2739 | Spent: 5.6 secs | LR: 0.000227
INFO:tensorflow:Step 9100 | Loss: 1.5606 | Loss_intent: 1.0805 | Loss_slots: 0.4801 | Spent: 3.2 secs | LR: 0.000220
INFO:tensorflow:Step 9150 | Loss: 1.5207 | Loss_intent: 1.0927 | Loss_slots: 0.4280 | Spent: 3.1 secs | LR: 0.000213
INFO:tensorflow:Step 9200 | Loss: 1.3353 | Loss_intent: 1.0818 | Loss_slots: 0.2534 | Spent: 3.0 secs | LR: 0.000206
INFO:tensorflow:Step 9250 | Loss: 1.4401 | Loss_intent: 1.0846 | Loss_slots: 0.3555 | Spent: 3.0 secs | LR: 0.000199
INFO:tensorflow:Step 9300 | Loss: 1.3183 | Loss_intent: 1.0883 | Loss_slots: 0.2300 | Spent: 3.0 secs | LR: 0.000192
INFO:tensorflow:Step 9350 | Loss: 1.4448 | Loss_intent: 1.0818 | Loss_slots: 0.3630 | Spent: 3.0 secs | LR: 0.000185
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.951, Intent Acc: 0.963
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.970
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 9400 | Loss: 1.4312 | Loss_intent: 1.0853 | Loss_slots: 0.3459 | Spent: 5.3 secs | LR: 0.000178
INFO:tensorflow:Step 9450 | Loss: 1.4537 | Loss_intent: 1.0830 | Loss_slots: 0.3707 | Spent: 3.0 secs | LR: 0.000171
INFO:tensorflow:Step 9500 | Loss: 1.4483 | Loss_intent: 1.0833 | Loss_slots: 0.3649 | Spent: 3.0 secs | LR: 0.000164
INFO:tensorflow:Step 9550 | Loss: 1.4358 | Loss_intent: 1.0839 | Loss_slots: 0.3519 | Spent: 3.0 secs | LR: 0.000157
INFO:tensorflow:Step 9600 | Loss: 1.2842 | Loss_intent: 1.0819 | Loss_slots: 0.2023 | Spent: 3.0 secs | LR: 0.000150
INFO:tensorflow:Step 9650 | Loss: 1.4828 | Loss_intent: 1.0807 | Loss_slots: 0.4021 | Spent: 2.9 secs | LR: 0.000143
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.965
INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 9700 | Loss: 1.3646 | Loss_intent: 1.0821 | Loss_slots: 0.2825 | Spent: 5.3 secs | LR: 0.000136
INFO:tensorflow:Step 9750 | Loss: 1.4170 | Loss_intent: 1.0819 | Loss_slots: 0.3351 | Spent: 2.9 secs | LR: 0.000129
INFO:tensorflow:Step 9800 | Loss: 1.4803 | Loss_intent: 1.0843 | Loss_slots: 0.3960 | Spent: 2.9 secs | LR: 0.000122
INFO:tensorflow:Step 9850 | Loss: 1.4831 | Loss_intent: 1.0813 | Loss_slots: 0.4019 | Spent: 2.9 secs | LR: 0.000115
INFO:tensorflow:Step 9900 | Loss: 1.4704 | Loss_intent: 1.0847 | Loss_slots: 0.3857 | Spent: 3.0 secs | LR: 0.000108
INFO:tensorflow:Step 9950 | Loss: 1.4942 | Loss_intent: 1.0829 | Loss_slots: 0.4113 | Spent: 3.0 secs | LR: 0.000101
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.951, Intent Acc: 0.962
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.974     0.989     0.981       632
                            atis_airfare      0.959     0.979     0.969        48
                     atis_ground_service      0.973     1.000     0.986        36
                            atis_airline      1.000     1.000     1.000        38
                       atis_abbreviation      0.933     0.848     0.889        33
                           atis_aircraft      0.889     0.889     0.889         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.200     0.333     0.250         3
                atis_flight#atis_airfare      0.800     0.333     0.471        12
                            atis_airport      0.900     1.000     0.947        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     0.714     0.833         7
                           atis_capacity      0.913     1.000     0.955        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      1.000     0.833     0.909         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.962     0.967     0.965       888
                               macro avg      0.656     0.618     0.628       888
                            weighted avg      0.964     0.967     0.963       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.973     0.993     0.983     716.0
         B-fromloc.city_name      0.983     0.996     0.989     704.0
           I-toloc.city_name      0.957     1.000     0.978     265.0
      B-depart_date.day_name      0.990     0.981     0.986     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.967     0.994     0.981     177.0
 B-depart_time.period_of_day      0.976     0.931     0.953     130.0
              I-airline_name      1.000     1.000     1.000      65.0
    B-depart_date.day_number      0.964     0.982     0.973      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.851     1.000     0.919      57.0
                B-round_trip      1.000     0.986     0.993      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      1.000     0.958     0.979      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.981     1.000     0.990      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.906     0.509     0.652      57.0
                B-class_type      0.960     1.000     0.980      24.0
          B-arrive_time.time      0.971     0.971     0.971      34.0
 B-arrive_time.time_relative      0.857     0.968     0.909      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      1.000     1.000     1.000      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.882     0.938      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.395     1.000     0.566      15.0
      B-fromloc.airport_name      0.407     0.917     0.564      12.0
      B-arrive_date.day_name      0.688     1.000     0.815      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     1.000     1.000       9.0
             B-flight_number      0.550     1.000     0.710      11.0
 B-depart_date.date_relative      0.895     1.000     0.944      17.0
          B-toloc.state_name      0.933     1.000     0.966      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      0.909     0.345     0.500      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.300     0.462      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      0.909     1.000     0.952      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.833     0.833     0.833       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.750     0.600     0.667       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     1.000     1.000       3.0
        B-fromloc.state_name      1.000     1.000     1.000      17.0
              B-airport_name      0.500     0.333     0.400      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.861     0.939     0.899      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      1.000     0.667     0.800       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      1.000     1.000     1.000       4.0
    B-arrive_time.start_time      0.889     1.000     0.941       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.889     1.000     0.941       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      1.000     1.000     1.000       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      1.000     0.500     0.667       2.0
                I-flight_mod      1.000     0.167     0.286       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.667     0.667     0.667       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      1.000     1.000     1.000       1.0
 I-depart_time.period_of_day      0.000     0.000     0.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.500     0.667       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      1.000     1.000     1.000       1.0
                 B-days_code      1.000     1.000     1.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      1.000     0.333     0.500       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.951     0.952     0.951    3657.0
                   macro avg      0.668     0.637     0.637    3657.0
                weighted avg      0.954     0.952     0.947    3657.0

INFO:tensorflow:Best Slot F1: 0.952, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 10000 | Loss: 1.4477 | Loss_intent: 1.0879 | Loss_slots: 0.3599 | Spent: 5.3 secs | LR: 0.000103
INFO:tensorflow:Step 10050 | Loss: 1.3125 | Loss_intent: 1.0861 | Loss_slots: 0.2264 | Spent: 3.0 secs | LR: 0.000107
INFO:tensorflow:Step 10100 | Loss: 1.4844 | Loss_intent: 1.0816 | Loss_slots: 0.4028 | Spent: 3.0 secs | LR: 0.000110
INFO:tensorflow:Step 10150 | Loss: 1.2708 | Loss_intent: 1.0848 | Loss_slots: 0.1859 | Spent: 3.0 secs | LR: 0.000114
INFO:tensorflow:Step 10200 | Loss: 1.4858 | Loss_intent: 1.0921 | Loss_slots: 0.3937 | Spent: 3.0 secs | LR: 0.000117
INFO:tensorflow:Step 10250 | Loss: 1.3970 | Loss_intent: 1.0845 | Loss_slots: 0.3125 | Spent: 3.0 secs | LR: 0.000121
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.953, Intent Acc: 0.968
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 10300 | Loss: 1.4546 | Loss_intent: 1.0810 | Loss_slots: 0.3736 | Spent: 5.2 secs | LR: 0.000124
INFO:tensorflow:Step 10350 | Loss: 1.4885 | Loss_intent: 1.0940 | Loss_slots: 0.3945 | Spent: 3.0 secs | LR: 0.000128
INFO:tensorflow:Step 10400 | Loss: 1.4509 | Loss_intent: 1.0847 | Loss_slots: 0.3662 | Spent: 3.0 secs | LR: 0.000131
INFO:tensorflow:Step 10450 | Loss: 1.3959 | Loss_intent: 1.0799 | Loss_slots: 0.3160 | Spent: 3.0 secs | LR: 0.000135
INFO:tensorflow:Step 10500 | Loss: 1.3422 | Loss_intent: 1.0825 | Loss_slots: 0.2597 | Spent: 3.0 secs | LR: 0.000138
INFO:tensorflow:Step 10550 | Loss: 1.4467 | Loss_intent: 1.0807 | Loss_slots: 0.3660 | Spent: 3.0 secs | LR: 0.000142
INFO:tensorflow:Step 10600 | Loss: 1.5043 | Loss_intent: 1.0812 | Loss_slots: 0.4231 | Spent: 3.0 secs | LR: 0.000145
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 10650 | Loss: 1.3301 | Loss_intent: 1.0846 | Loss_slots: 0.2455 | Spent: 5.2 secs | LR: 0.000149
INFO:tensorflow:Step 10700 | Loss: 1.4324 | Loss_intent: 1.0817 | Loss_slots: 0.3507 | Spent: 3.0 secs | LR: 0.000152
INFO:tensorflow:Step 10750 | Loss: 1.4029 | Loss_intent: 1.0820 | Loss_slots: 0.3209 | Spent: 2.9 secs | LR: 0.000156
INFO:tensorflow:Step 10800 | Loss: 1.3628 | Loss_intent: 1.0820 | Loss_slots: 0.2808 | Spent: 3.0 secs | LR: 0.000159
INFO:tensorflow:Step 10850 | Loss: 1.5052 | Loss_intent: 1.0838 | Loss_slots: 0.4214 | Spent: 3.0 secs | LR: 0.000163
INFO:tensorflow:Step 10900 | Loss: 1.2933 | Loss_intent: 1.0887 | Loss_slots: 0.2046 | Spent: 3.0 secs | LR: 0.000166
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.969
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 10950 | Loss: 1.4680 | Loss_intent: 1.0840 | Loss_slots: 0.3840 | Spent: 5.2 secs | LR: 0.000170
INFO:tensorflow:Step 11000 | Loss: 1.3417 | Loss_intent: 1.0843 | Loss_slots: 0.2574 | Spent: 3.0 secs | LR: 0.000173
INFO:tensorflow:Step 11050 | Loss: 1.5018 | Loss_intent: 1.0840 | Loss_slots: 0.4177 | Spent: 3.0 secs | LR: 0.000177
INFO:tensorflow:Step 11100 | Loss: 1.4430 | Loss_intent: 1.0865 | Loss_slots: 0.3565 | Spent: 3.0 secs | LR: 0.000180
INFO:tensorflow:Step 11150 | Loss: 1.3601 | Loss_intent: 1.0870 | Loss_slots: 0.2731 | Spent: 2.9 secs | LR: 0.000184
INFO:tensorflow:Step 11200 | Loss: 1.4071 | Loss_intent: 1.0953 | Loss_slots: 0.3118 | Spent: 2.9 secs | LR: 0.000187
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.949, Intent Acc: 0.965
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 11250 | Loss: 1.4719 | Loss_intent: 1.0819 | Loss_slots: 0.3900 | Spent: 5.3 secs | LR: 0.000191
INFO:tensorflow:Step 11300 | Loss: 1.4008 | Loss_intent: 1.0813 | Loss_slots: 0.3195 | Spent: 2.9 secs | LR: 0.000194
INFO:tensorflow:Step 11350 | Loss: 1.4370 | Loss_intent: 1.0810 | Loss_slots: 0.3560 | Spent: 3.0 secs | LR: 0.000198
INFO:tensorflow:Step 11400 | Loss: 1.4232 | Loss_intent: 1.0852 | Loss_slots: 0.3381 | Spent: 3.1 secs | LR: 0.000202
INFO:tensorflow:Step 11450 | Loss: 1.4915 | Loss_intent: 1.0823 | Loss_slots: 0.4092 | Spent: 2.9 secs | LR: 0.000205
INFO:tensorflow:Step 11500 | Loss: 1.5032 | Loss_intent: 1.0938 | Loss_slots: 0.4094 | Spent: 3.0 secs | LR: 0.000209
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.961
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 11550 | Loss: 1.4682 | Loss_intent: 1.0808 | Loss_slots: 0.3875 | Spent: 5.2 secs | LR: 0.000212
INFO:tensorflow:Step 11600 | Loss: 1.4290 | Loss_intent: 1.0813 | Loss_slots: 0.3477 | Spent: 2.9 secs | LR: 0.000216
INFO:tensorflow:Step 11650 | Loss: 1.3482 | Loss_intent: 1.0814 | Loss_slots: 0.2669 | Spent: 3.0 secs | LR: 0.000219
INFO:tensorflow:Step 11700 | Loss: 1.4630 | Loss_intent: 1.0925 | Loss_slots: 0.3705 | Spent: 3.0 secs | LR: 0.000223
INFO:tensorflow:Step 11750 | Loss: 1.3765 | Loss_intent: 1.0879 | Loss_slots: 0.2886 | Spent: 3.0 secs | LR: 0.000226
INFO:tensorflow:Step 11800 | Loss: 1.4181 | Loss_intent: 1.0880 | Loss_slots: 0.3301 | Spent: 3.0 secs | LR: 0.000230
INFO:tensorflow:Step 11850 | Loss: 1.3737 | Loss_intent: 1.0831 | Loss_slots: 0.2906 | Spent: 3.0 secs | LR: 0.000233
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.956
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 11900 | Loss: 1.5165 | Loss_intent: 1.0905 | Loss_slots: 0.4259 | Spent: 5.3 secs | LR: 0.000237
INFO:tensorflow:Step 11950 | Loss: 1.5430 | Loss_intent: 1.0822 | Loss_slots: 0.4608 | Spent: 3.0 secs | LR: 0.000240
INFO:tensorflow:Step 12000 | Loss: 1.4566 | Loss_intent: 1.0828 | Loss_slots: 0.3739 | Spent: 3.0 secs | LR: 0.000244
INFO:tensorflow:Step 12050 | Loss: 1.4701 | Loss_intent: 1.0905 | Loss_slots: 0.3796 | Spent: 3.0 secs | LR: 0.000247
INFO:tensorflow:Step 12100 | Loss: 1.3939 | Loss_intent: 1.0984 | Loss_slots: 0.2955 | Spent: 3.0 secs | LR: 0.000251
INFO:tensorflow:Step 12150 | Loss: 1.4948 | Loss_intent: 1.0889 | Loss_slots: 0.4060 | Spent: 3.0 secs | LR: 0.000254
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.961
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 12200 | Loss: 1.5584 | Loss_intent: 1.0856 | Loss_slots: 0.4728 | Spent: 5.2 secs | LR: 0.000258
INFO:tensorflow:Step 12250 | Loss: 1.3807 | Loss_intent: 1.0823 | Loss_slots: 0.2984 | Spent: 3.0 secs | LR: 0.000261
INFO:tensorflow:Step 12300 | Loss: 1.4435 | Loss_intent: 1.0853 | Loss_slots: 0.3582 | Spent: 2.9 secs | LR: 0.000265
INFO:tensorflow:Step 12350 | Loss: 1.3857 | Loss_intent: 1.0858 | Loss_slots: 0.2999 | Spent: 3.1 secs | LR: 0.000268
INFO:tensorflow:Step 12400 | Loss: 1.4618 | Loss_intent: 1.0839 | Loss_slots: 0.3779 | Spent: 3.0 secs | LR: 0.000272
INFO:tensorflow:Step 12450 | Loss: 1.4172 | Loss_intent: 1.0844 | Loss_slots: 0.3328 | Spent: 3.0 secs | LR: 0.000275
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.950, Intent Acc: 0.969
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.984     0.991     0.987       632
                            atis_airfare      0.959     0.979     0.969        48
                     atis_ground_service      0.947     1.000     0.973        36
                            atis_airline      0.974     1.000     0.987        38
                       atis_abbreviation      0.939     0.939     0.939        33
                           atis_aircraft      0.889     0.889     0.889         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.375     1.000     0.545         3
                atis_flight#atis_airfare      0.833     0.417     0.556        12
                            atis_airport      0.947     1.000     0.973        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     0.571     0.727         7
                           atis_capacity      1.000     1.000     1.000        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      1.000     0.833     0.909         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.969     0.974     0.971       888
                               macro avg      0.670     0.649     0.645       888
                            weighted avg      0.974     0.974     0.972       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.971     0.997     0.984     716.0
         B-fromloc.city_name      0.985     0.997     0.991     704.0
           I-toloc.city_name      0.946     1.000     0.972     265.0
      B-depart_date.day_name      0.990     0.981     0.986     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.978     0.989     0.983     177.0
 B-depart_time.period_of_day      0.984     0.931     0.957     130.0
              I-airline_name      0.985     1.000     0.992      65.0
    B-depart_date.day_number      0.964     0.964     0.964      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.826     1.000     0.905      57.0
                B-round_trip      1.000     0.986     0.993      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      1.000     0.958     0.979      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.981     1.000     0.990      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.875     0.491     0.629      57.0
                B-class_type      0.923     1.000     0.960      24.0
          B-arrive_time.time      0.917     0.971     0.943      34.0
 B-arrive_time.time_relative      0.909     0.968     0.937      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      1.000     1.000     1.000      21.0
          I-arrive_time.time      1.000     0.971     0.986      35.0
              B-airline_code      1.000     0.941     0.970      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.405     1.000     0.577      15.0
      B-fromloc.airport_name      0.407     0.917     0.564      12.0
      B-arrive_date.day_name      0.688     1.000     0.815      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     1.000     1.000       9.0
             B-flight_number      0.562     0.818     0.667      11.0
 B-depart_date.date_relative      0.889     0.941     0.914      17.0
          B-toloc.state_name      0.903     1.000     0.949      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      0.909     0.345     0.500      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.300     0.462      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      0.909     1.000     0.952      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.833     0.833     0.833       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.800     0.800     0.800       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     1.000     1.000       3.0
        B-fromloc.state_name      1.000     1.000     1.000      17.0
              B-airport_name      0.667     0.286     0.400      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.933     0.848     0.889      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      0.667     0.667     0.667       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      0.364     1.000     0.533       4.0
    B-arrive_time.start_time      0.875     0.875     0.875       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-arrive_time.end_time      0.889     1.000     0.941       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      1.000     0.667     0.800       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      0.500     0.500     0.500       2.0
                I-flight_mod      1.000     0.167     0.286       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.500     0.667     0.571       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      1.000     1.000     1.000       1.0
 I-depart_time.period_of_day      0.000     0.000     0.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.500     0.667       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      0.000     0.000     0.000       1.0
                 B-days_code      1.000     1.000     1.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      1.000     0.333     0.500       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.949     0.951     0.950    3657.0
                   macro avg      0.648     0.623     0.619    3657.0
                weighted avg      0.953     0.951     0.945    3657.0

INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 12500 | Loss: 1.3819 | Loss_intent: 1.0855 | Loss_slots: 0.2963 | Spent: 5.3 secs | LR: 0.000271
INFO:tensorflow:Step 12550 | Loss: 1.3415 | Loss_intent: 1.0883 | Loss_slots: 0.2532 | Spent: 3.0 secs | LR: 0.000268
INFO:tensorflow:Step 12600 | Loss: 1.4170 | Loss_intent: 1.0931 | Loss_slots: 0.3238 | Spent: 3.0 secs | LR: 0.000264
INFO:tensorflow:Step 12650 | Loss: 1.4459 | Loss_intent: 1.0974 | Loss_slots: 0.3485 | Spent: 3.0 secs | LR: 0.000261
INFO:tensorflow:Step 12700 | Loss: 1.3809 | Loss_intent: 1.0828 | Loss_slots: 0.2982 | Spent: 2.9 secs | LR: 0.000257
INFO:tensorflow:Step 12750 | Loss: 1.3998 | Loss_intent: 1.0896 | Loss_slots: 0.3102 | Spent: 3.0 secs | LR: 0.000254
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 12800 | Loss: 1.4304 | Loss_intent: 1.1005 | Loss_slots: 0.3299 | Spent: 5.2 secs | LR: 0.000250
INFO:tensorflow:Step 12850 | Loss: 1.4547 | Loss_intent: 1.0821 | Loss_slots: 0.3726 | Spent: 3.0 secs | LR: 0.000247
INFO:tensorflow:Step 12900 | Loss: 1.4117 | Loss_intent: 1.0896 | Loss_slots: 0.3221 | Spent: 3.0 secs | LR: 0.000243
INFO:tensorflow:Step 12950 | Loss: 1.4422 | Loss_intent: 1.0859 | Loss_slots: 0.3563 | Spent: 3.0 secs | LR: 0.000239
INFO:tensorflow:Step 13000 | Loss: 1.4319 | Loss_intent: 1.0843 | Loss_slots: 0.3476 | Spent: 3.0 secs | LR: 0.000236
INFO:tensorflow:Step 13050 | Loss: 1.3702 | Loss_intent: 1.0865 | Loss_slots: 0.2837 | Spent: 2.9 secs | LR: 0.000232
INFO:tensorflow:Step 13100 | Loss: 1.4660 | Loss_intent: 1.0847 | Loss_slots: 0.3813 | Spent: 3.0 secs | LR: 0.000229
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.965
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 13150 | Loss: 1.4129 | Loss_intent: 1.0837 | Loss_slots: 0.3292 | Spent: 5.2 secs | LR: 0.000225
INFO:tensorflow:Step 13200 | Loss: 1.5300 | Loss_intent: 1.0849 | Loss_slots: 0.4451 | Spent: 2.9 secs | LR: 0.000222
INFO:tensorflow:Step 13250 | Loss: 1.4472 | Loss_intent: 1.1041 | Loss_slots: 0.3431 | Spent: 2.9 secs | LR: 0.000218
INFO:tensorflow:Step 13300 | Loss: 1.4768 | Loss_intent: 1.0848 | Loss_slots: 0.3920 | Spent: 2.9 secs | LR: 0.000215
INFO:tensorflow:Step 13350 | Loss: 1.2860 | Loss_intent: 1.0846 | Loss_slots: 0.2014 | Spent: 3.0 secs | LR: 0.000211
INFO:tensorflow:Step 13400 | Loss: 1.4241 | Loss_intent: 1.0807 | Loss_slots: 0.3434 | Spent: 3.0 secs | LR: 0.000208
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.948, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 13450 | Loss: 1.4424 | Loss_intent: 1.0808 | Loss_slots: 0.3616 | Spent: 5.2 secs | LR: 0.000204
INFO:tensorflow:Step 13500 | Loss: 1.4383 | Loss_intent: 1.0810 | Loss_slots: 0.3573 | Spent: 3.0 secs | LR: 0.000201
INFO:tensorflow:Step 13550 | Loss: 1.3830 | Loss_intent: 1.0849 | Loss_slots: 0.2981 | Spent: 3.0 secs | LR: 0.000197
INFO:tensorflow:Step 13600 | Loss: 1.3965 | Loss_intent: 1.0808 | Loss_slots: 0.3157 | Spent: 3.0 secs | LR: 0.000194
INFO:tensorflow:Step 13650 | Loss: 1.4396 | Loss_intent: 1.0817 | Loss_slots: 0.3579 | Spent: 2.9 secs | LR: 0.000190
INFO:tensorflow:Step 13700 | Loss: 1.3701 | Loss_intent: 1.0811 | Loss_slots: 0.2890 | Spent: 3.2 secs | LR: 0.000187
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.960
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 13750 | Loss: 1.4376 | Loss_intent: 1.0835 | Loss_slots: 0.3542 | Spent: 5.7 secs | LR: 0.000183
INFO:tensorflow:Step 13800 | Loss: 1.4540 | Loss_intent: 1.0848 | Loss_slots: 0.3692 | Spent: 3.1 secs | LR: 0.000180
INFO:tensorflow:Step 13850 | Loss: 1.2582 | Loss_intent: 1.0832 | Loss_slots: 0.1751 | Spent: 3.0 secs | LR: 0.000176
INFO:tensorflow:Step 13900 | Loss: 1.4459 | Loss_intent: 1.0903 | Loss_slots: 0.3556 | Spent: 3.0 secs | LR: 0.000173
INFO:tensorflow:Step 13950 | Loss: 1.4643 | Loss_intent: 1.0804 | Loss_slots: 0.3839 | Spent: 3.0 secs | LR: 0.000169
INFO:tensorflow:Step 14000 | Loss: 1.4765 | Loss_intent: 1.0840 | Loss_slots: 0.3924 | Spent: 3.0 secs | LR: 0.000166
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.951, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 14050 | Loss: 1.4099 | Loss_intent: 1.0818 | Loss_slots: 0.3281 | Spent: 5.3 secs | LR: 0.000162
INFO:tensorflow:Step 14100 | Loss: 1.2982 | Loss_intent: 1.0820 | Loss_slots: 0.2162 | Spent: 3.0 secs | LR: 0.000159
INFO:tensorflow:Step 14150 | Loss: 1.3631 | Loss_intent: 1.0824 | Loss_slots: 0.2807 | Spent: 3.0 secs | LR: 0.000155
INFO:tensorflow:Step 14200 | Loss: 1.3859 | Loss_intent: 1.0809 | Loss_slots: 0.3050 | Spent: 3.0 secs | LR: 0.000152
INFO:tensorflow:Step 14250 | Loss: 1.3413 | Loss_intent: 1.0814 | Loss_slots: 0.2599 | Spent: 2.9 secs | LR: 0.000148
INFO:tensorflow:Step 14300 | Loss: 1.4648 | Loss_intent: 1.0803 | Loss_slots: 0.3845 | Spent: 3.0 secs | LR: 0.000145
INFO:tensorflow:Step 14350 | Loss: 1.4793 | Loss_intent: 1.1104 | Loss_slots: 0.3689 | Spent: 3.0 secs | LR: 0.000141
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 14400 | Loss: 1.3505 | Loss_intent: 1.0802 | Loss_slots: 0.2704 | Spent: 5.3 secs | LR: 0.000138
INFO:tensorflow:Step 14450 | Loss: 1.4198 | Loss_intent: 1.0821 | Loss_slots: 0.3377 | Spent: 3.0 secs | LR: 0.000134
INFO:tensorflow:Step 14500 | Loss: 1.3834 | Loss_intent: 1.0840 | Loss_slots: 0.2994 | Spent: 3.0 secs | LR: 0.000131
INFO:tensorflow:Step 14550 | Loss: 1.3974 | Loss_intent: 1.0830 | Loss_slots: 0.3143 | Spent: 3.0 secs | LR: 0.000127
INFO:tensorflow:Step 14600 | Loss: 1.3264 | Loss_intent: 1.0919 | Loss_slots: 0.2345 | Spent: 3.0 secs | LR: 0.000123
INFO:tensorflow:Step 14650 | Loss: 1.5101 | Loss_intent: 1.0816 | Loss_slots: 0.4285 | Spent: 3.0 secs | LR: 0.000120
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 14700 | Loss: 1.4506 | Loss_intent: 1.0806 | Loss_slots: 0.3699 | Spent: 5.2 secs | LR: 0.000116
INFO:tensorflow:Step 14750 | Loss: 1.4490 | Loss_intent: 1.0803 | Loss_slots: 0.3686 | Spent: 3.0 secs | LR: 0.000113
INFO:tensorflow:Step 14800 | Loss: 1.3942 | Loss_intent: 1.0835 | Loss_slots: 0.3107 | Spent: 3.0 secs | LR: 0.000109
INFO:tensorflow:Step 14850 | Loss: 1.3406 | Loss_intent: 1.0865 | Loss_slots: 0.2541 | Spent: 3.0 secs | LR: 0.000106
INFO:tensorflow:Step 14900 | Loss: 1.3943 | Loss_intent: 1.0816 | Loss_slots: 0.3127 | Spent: 3.0 secs | LR: 0.000102
INFO:tensorflow:Step 14950 | Loss: 1.4142 | Loss_intent: 1.0810 | Loss_slots: 0.3332 | Spent: 3.0 secs | LR: 0.000101
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.969
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.980     0.987     0.983       632
                            atis_airfare      0.979     0.979     0.979        48
                     atis_ground_service      1.000     1.000     1.000        36
                            atis_airline      1.000     1.000     1.000        38
                       atis_abbreviation      0.939     0.939     0.939        33
                           atis_aircraft      0.889     0.889     0.889         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.429     1.000     0.600         3
                atis_flight#atis_airfare      0.800     0.333     0.471        12
                            atis_airport      0.900     1.000     0.947        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     1.000     1.000         7
                           atis_capacity      1.000     1.000     1.000        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      0.833     0.833     0.833         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.969     0.974     0.971       888
                               macro avg      0.665     0.665     0.654       888
                            weighted avg      0.972     0.974     0.971       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.975     0.996     0.985     716.0
         B-fromloc.city_name      0.990     0.997     0.994     704.0
           I-toloc.city_name      0.964     1.000     0.981     265.0
      B-depart_date.day_name      0.990     0.981     0.986     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.983     0.983     0.983     177.0
 B-depart_time.period_of_day      1.000     0.900     0.947     130.0
              I-airline_name      1.000     1.000     1.000      65.0
    B-depart_date.day_number      0.982     0.982     0.982      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.826     1.000     0.905      57.0
                B-round_trip      1.000     0.973     0.986      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      0.857     1.000     0.923      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.929     1.000     0.963      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.846     0.579     0.688      57.0
                B-class_type      0.960     1.000     0.980      24.0
          B-arrive_time.time      0.917     0.971     0.943      34.0
 B-arrive_time.time_relative      0.857     0.968     0.909      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      0.955     1.000     0.977      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.912     0.954      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.405     1.000     0.577      15.0
      B-fromloc.airport_name      0.407     0.917     0.564      12.0
      B-arrive_date.day_name      0.688     1.000     0.815      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     1.000     1.000       9.0
             B-flight_number      0.529     0.818     0.643      11.0
 B-depart_date.date_relative      0.895     1.000     0.944      17.0
          B-toloc.state_name      0.966     1.000     0.982      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      0.909     0.345     0.500      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.500     0.667      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      1.000     0.900     0.947      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.833     0.833     0.833       6.0
         I-stoploc.city_name      1.000     0.800     0.889      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.714     1.000     0.833       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     1.000     1.000       3.0
        B-fromloc.state_name      0.944     1.000     0.971      17.0
              B-airport_name      0.583     0.333     0.424      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      0.967     0.879     0.921      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      0.667     0.667     0.667       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.500     1.000     0.667       1.0
          B-restriction_code      0.400     1.000     0.571       4.0
    B-arrive_time.start_time      0.875     0.875     0.875       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      0.750     1.000     0.857       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      1.000     0.500     0.667       2.0
                I-flight_mod      1.000     0.167     0.286       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      1.000     0.333     0.500       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      1.000     1.000     1.000       1.0
 I-depart_time.period_of_day      1.000     1.000     1.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.500     0.667       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      1.000     1.000     1.000       1.0
                 B-days_code      1.000     1.000     1.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.750     1.000     0.857       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.952     0.954     0.953    3657.0
                   macro avg      0.670     0.656     0.647    3657.0
                weighted avg      0.955     0.954     0.949    3657.0

INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 15000 | Loss: 1.4553 | Loss_intent: 1.0808 | Loss_slots: 0.3745 | Spent: 5.3 secs | LR: 0.000102
INFO:tensorflow:Step 15050 | Loss: 1.3914 | Loss_intent: 1.0818 | Loss_slots: 0.3097 | Spent: 3.0 secs | LR: 0.000104
INFO:tensorflow:Step 15100 | Loss: 1.4076 | Loss_intent: 1.0825 | Loss_slots: 0.3251 | Spent: 3.0 secs | LR: 0.000106
INFO:tensorflow:Step 15150 | Loss: 1.4310 | Loss_intent: 1.0814 | Loss_slots: 0.3497 | Spent: 3.0 secs | LR: 0.000108
INFO:tensorflow:Step 15200 | Loss: 1.3508 | Loss_intent: 1.0800 | Loss_slots: 0.2707 | Spent: 3.0 secs | LR: 0.000109
INFO:tensorflow:Step 15250 | Loss: 1.4272 | Loss_intent: 1.0806 | Loss_slots: 0.3467 | Spent: 2.9 secs | LR: 0.000111
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.963
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 15300 | Loss: 1.3437 | Loss_intent: 1.0811 | Loss_slots: 0.2626 | Spent: 5.3 secs | LR: 0.000113
INFO:tensorflow:Step 15350 | Loss: 1.3795 | Loss_intent: 1.0819 | Loss_slots: 0.2976 | Spent: 3.0 secs | LR: 0.000115
INFO:tensorflow:Step 15400 | Loss: 1.2712 | Loss_intent: 1.0844 | Loss_slots: 0.1868 | Spent: 2.9 secs | LR: 0.000116
INFO:tensorflow:Step 15450 | Loss: 1.3848 | Loss_intent: 1.0806 | Loss_slots: 0.3042 | Spent: 3.0 secs | LR: 0.000118
INFO:tensorflow:Step 15500 | Loss: 1.3069 | Loss_intent: 1.0876 | Loss_slots: 0.2193 | Spent: 3.0 secs | LR: 0.000120
INFO:tensorflow:Step 15550 | Loss: 1.3541 | Loss_intent: 1.0826 | Loss_slots: 0.2715 | Spent: 3.0 secs | LR: 0.000122
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.951, Intent Acc: 0.968
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 15600 | Loss: 1.5197 | Loss_intent: 1.0803 | Loss_slots: 0.4394 | Spent: 5.3 secs | LR: 0.000123
INFO:tensorflow:Step 15650 | Loss: 1.2928 | Loss_intent: 1.0812 | Loss_slots: 0.2116 | Spent: 3.0 secs | LR: 0.000125
INFO:tensorflow:Step 15700 | Loss: 1.4918 | Loss_intent: 1.0888 | Loss_slots: 0.4030 | Spent: 2.9 secs | LR: 0.000127
INFO:tensorflow:Step 15750 | Loss: 1.3917 | Loss_intent: 1.0809 | Loss_slots: 0.3107 | Spent: 2.9 secs | LR: 0.000129
INFO:tensorflow:Step 15800 | Loss: 1.4288 | Loss_intent: 1.0832 | Loss_slots: 0.3456 | Spent: 3.0 secs | LR: 0.000130
INFO:tensorflow:Step 15850 | Loss: 1.3736 | Loss_intent: 1.0841 | Loss_slots: 0.2895 | Spent: 3.0 secs | LR: 0.000132
INFO:tensorflow:Step 15900 | Loss: 1.4634 | Loss_intent: 1.0830 | Loss_slots: 0.3805 | Spent: 3.0 secs | LR: 0.000134
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 15950 | Loss: 1.2809 | Loss_intent: 1.0803 | Loss_slots: 0.2005 | Spent: 5.5 secs | LR: 0.000136
INFO:tensorflow:Step 16000 | Loss: 1.3945 | Loss_intent: 1.0816 | Loss_slots: 0.3129 | Spent: 3.0 secs | LR: 0.000137
INFO:tensorflow:Step 16050 | Loss: 1.3837 | Loss_intent: 1.0806 | Loss_slots: 0.3032 | Spent: 3.0 secs | LR: 0.000139
INFO:tensorflow:Step 16100 | Loss: 1.3853 | Loss_intent: 1.0803 | Loss_slots: 0.3051 | Spent: 3.0 secs | LR: 0.000141
INFO:tensorflow:Step 16150 | Loss: 1.2853 | Loss_intent: 1.0824 | Loss_slots: 0.2029 | Spent: 3.0 secs | LR: 0.000143
INFO:tensorflow:Step 16200 | Loss: 1.5052 | Loss_intent: 1.0813 | Loss_slots: 0.4239 | Spent: 3.0 secs | LR: 0.000145
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.962
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 16250 | Loss: 1.4904 | Loss_intent: 1.0805 | Loss_slots: 0.4100 | Spent: 5.2 secs | LR: 0.000146
INFO:tensorflow:Step 16300 | Loss: 1.3647 | Loss_intent: 1.0803 | Loss_slots: 0.2844 | Spent: 3.0 secs | LR: 0.000148
INFO:tensorflow:Step 16350 | Loss: 1.3881 | Loss_intent: 1.0985 | Loss_slots: 0.2896 | Spent: 3.0 secs | LR: 0.000150
INFO:tensorflow:Step 16400 | Loss: 1.4612 | Loss_intent: 1.0845 | Loss_slots: 0.3767 | Spent: 3.0 secs | LR: 0.000152
INFO:tensorflow:Step 16450 | Loss: 1.4133 | Loss_intent: 1.0824 | Loss_slots: 0.3309 | Spent: 3.0 secs | LR: 0.000153
INFO:tensorflow:Step 16500 | Loss: 1.5067 | Loss_intent: 1.0852 | Loss_slots: 0.4215 | Spent: 3.0 secs | LR: 0.000155
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.963
INFO:tensorflow:Best Slot F1: 0.954, Intent Acc: 0.964
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 16550 | Loss: 1.4248 | Loss_intent: 1.0831 | Loss_slots: 0.3417 | Spent: 5.4 secs | LR: 0.000157
INFO:tensorflow:Step 16600 | Loss: 1.3700 | Loss_intent: 1.0871 | Loss_slots: 0.2829 | Spent: 3.0 secs | LR: 0.000159
INFO:tensorflow:Step 16650 | Loss: 1.4843 | Loss_intent: 1.0869 | Loss_slots: 0.3974 | Spent: 3.0 secs | LR: 0.000160
INFO:tensorflow:Step 16700 | Loss: 1.3482 | Loss_intent: 1.0828 | Loss_slots: 0.2654 | Spent: 3.0 secs | LR: 0.000162
INFO:tensorflow:Step 16750 | Loss: 1.4435 | Loss_intent: 1.0909 | Loss_slots: 0.3526 | Spent: 3.0 secs | LR: 0.000164
INFO:tensorflow:Step 16800 | Loss: 1.3265 | Loss_intent: 1.0819 | Loss_slots: 0.2446 | Spent: 3.0 secs | LR: 0.000166
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.955, Intent Acc: 0.965
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 16850 | Loss: 1.4766 | Loss_intent: 1.0804 | Loss_slots: 0.3963 | Spent: 5.2 secs | LR: 0.000167
INFO:tensorflow:Step 16900 | Loss: 1.3487 | Loss_intent: 1.0806 | Loss_slots: 0.2681 | Spent: 3.0 secs | LR: 0.000169
INFO:tensorflow:Step 16950 | Loss: 1.3744 | Loss_intent: 1.0805 | Loss_slots: 0.2939 | Spent: 3.0 secs | LR: 0.000171
INFO:tensorflow:Step 17000 | Loss: 1.3897 | Loss_intent: 1.0821 | Loss_slots: 0.3076 | Spent: 3.0 secs | LR: 0.000173
INFO:tensorflow:Step 17050 | Loss: 1.4397 | Loss_intent: 1.0815 | Loss_slots: 0.3582 | Spent: 3.0 secs | LR: 0.000174
INFO:tensorflow:Step 17100 | Loss: 1.3915 | Loss_intent: 1.0821 | Loss_slots: 0.3094 | Spent: 2.9 secs | LR: 0.000176
INFO:tensorflow:Step 17150 | Loss: 1.5631 | Loss_intent: 1.2064 | Loss_slots: 0.3566 | Spent: 3.0 secs | LR: 0.000178
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.955, Intent Acc: 0.971
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 17200 | Loss: 1.4696 | Loss_intent: 1.0812 | Loss_slots: 0.3884 | Spent: 5.2 secs | LR: 0.000180
INFO:tensorflow:Step 17250 | Loss: 1.3531 | Loss_intent: 1.0883 | Loss_slots: 0.2648 | Spent: 3.0 secs | LR: 0.000181
INFO:tensorflow:Step 17300 | Loss: 1.4588 | Loss_intent: 1.1512 | Loss_slots: 0.3076 | Spent: 3.0 secs | LR: 0.000183
INFO:tensorflow:Step 17350 | Loss: 1.3871 | Loss_intent: 1.0814 | Loss_slots: 0.3057 | Spent: 3.0 secs | LR: 0.000185
INFO:tensorflow:Step 17400 | Loss: 1.4281 | Loss_intent: 1.0830 | Loss_slots: 0.3450 | Spent: 2.9 secs | LR: 0.000187
INFO:tensorflow:Step 17450 | Loss: 1.4087 | Loss_intent: 1.0841 | Loss_slots: 0.3246 | Spent: 3.0 secs | LR: 0.000187
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.973
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.981     0.991     0.986       632
                            atis_airfare      0.980     1.000     0.990        48
                     atis_ground_service      1.000     1.000     1.000        36
                            atis_airline      1.000     1.000     1.000        38
                       atis_abbreviation      0.941     0.970     0.955        33
                           atis_aircraft      1.000     1.000     1.000         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.333     0.667     0.444         3
                atis_flight#atis_airfare      0.800     0.333     0.471        12
                            atis_airport      0.947     1.000     0.973        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      1.000     0.667     0.800         6
                        atis_ground_fare      1.000     1.000     1.000         7
                           atis_capacity      0.955     1.000     0.977        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      1.000     0.833     0.909         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.973     0.979     0.976       888
                               macro avg      0.674     0.657     0.657       888
                            weighted avg      0.975     0.979     0.975       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.977     0.994     0.985     716.0
         B-fromloc.city_name      0.989     0.996     0.992     704.0
           I-toloc.city_name      0.967     0.996     0.981     265.0
      B-depart_date.day_name      0.991     0.986     0.988     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.983     0.983     0.983     177.0
 B-depart_time.period_of_day      0.992     0.915     0.952     130.0
              I-airline_name      1.000     1.000     1.000      65.0
    B-depart_date.day_number      0.982     0.982     0.982      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.838     1.000     0.912      57.0
                B-round_trip      1.000     0.973     0.986      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      1.000     1.000     1.000      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.945     1.000     0.972      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.829     0.596     0.694      57.0
                B-class_type      0.960     1.000     0.980      24.0
          B-arrive_time.time      0.971     0.971     0.971      34.0
 B-arrive_time.time_relative      0.909     0.968     0.937      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      0.955     1.000     0.977      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.941     0.970      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.395     1.000     0.566      15.0
      B-fromloc.airport_name      0.393     0.917     0.550      12.0
      B-arrive_date.day_name      0.733     1.000     0.846      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     1.000     1.000       9.0
             B-flight_number      0.526     0.909     0.667      11.0
 B-depart_date.date_relative      0.895     1.000     0.944      17.0
          B-toloc.state_name      0.966     1.000     0.982      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      0.833     0.345     0.488      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.533     0.696      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      0.909     1.000     0.952      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.833     0.833     0.833       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.800     0.800     0.800       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     1.000     1.000       3.0
        B-fromloc.state_name      1.000     1.000     1.000      17.0
              B-airport_name      0.583     0.333     0.424      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      1.000     0.848     0.918      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      0.667     0.667     0.667       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      0.000     0.000     0.000       1.0
          B-restriction_code      0.308     1.000     0.471       4.0
    B-arrive_time.start_time      0.889     1.000     0.941       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.889     1.000     0.941       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      1.000     1.000     1.000       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      1.000     0.500     0.667       2.0
                I-flight_mod      1.000     0.167     0.286       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      0.000     0.000     0.000       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      0.000     0.000     0.000       1.0
 I-depart_time.period_of_day      1.000     1.000     1.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.500     0.667       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      1.000     1.000     1.000       1.0
                 B-days_code      0.000     0.000     0.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      1.000     0.500     0.667       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.600     1.000     0.750       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.953     0.955     0.954    3657.0
                   macro avg      0.652     0.636     0.629    3657.0
                weighted avg      0.957     0.955     0.951    3657.0

INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 17500 | Loss: 1.4062 | Loss_intent: 1.0830 | Loss_slots: 0.3233 | Spent: 5.3 secs | LR: 0.000185
INFO:tensorflow:Step 17550 | Loss: 1.4348 | Loss_intent: 1.0804 | Loss_slots: 0.3544 | Spent: 2.9 secs | LR: 0.000183
INFO:tensorflow:Step 17600 | Loss: 1.4294 | Loss_intent: 1.0819 | Loss_slots: 0.3475 | Spent: 3.0 secs | LR: 0.000181
INFO:tensorflow:Step 17650 | Loss: 1.4377 | Loss_intent: 1.0856 | Loss_slots: 0.3521 | Spent: 3.0 secs | LR: 0.000180
INFO:tensorflow:Step 17700 | Loss: 1.4014 | Loss_intent: 1.0854 | Loss_slots: 0.3160 | Spent: 3.0 secs | LR: 0.000178
INFO:tensorflow:Step 17750 | Loss: 1.4652 | Loss_intent: 1.0807 | Loss_slots: 0.3844 | Spent: 3.0 secs | LR: 0.000176
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.971
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 17800 | Loss: 1.3545 | Loss_intent: 1.0801 | Loss_slots: 0.2744 | Spent: 5.3 secs | LR: 0.000174
INFO:tensorflow:Step 17850 | Loss: 1.3839 | Loss_intent: 1.0825 | Loss_slots: 0.3015 | Spent: 2.9 secs | LR: 0.000172
INFO:tensorflow:Step 17900 | Loss: 1.4677 | Loss_intent: 1.0821 | Loss_slots: 0.3856 | Spent: 3.0 secs | LR: 0.000171
INFO:tensorflow:Step 17950 | Loss: 1.4287 | Loss_intent: 1.0845 | Loss_slots: 0.3442 | Spent: 3.0 secs | LR: 0.000169
INFO:tensorflow:Step 18000 | Loss: 1.5211 | Loss_intent: 1.0818 | Loss_slots: 0.4392 | Spent: 3.0 secs | LR: 0.000167
INFO:tensorflow:Step 18050 | Loss: 1.3914 | Loss_intent: 1.0806 | Loss_slots: 0.3108 | Spent: 3.0 secs | LR: 0.000165
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 18100 | Loss: 1.4722 | Loss_intent: 1.0806 | Loss_slots: 0.3916 | Spent: 5.3 secs | LR: 0.000164
INFO:tensorflow:Step 18150 | Loss: 1.3910 | Loss_intent: 1.0818 | Loss_slots: 0.3092 | Spent: 3.0 secs | LR: 0.000162
INFO:tensorflow:Step 18200 | Loss: 1.4720 | Loss_intent: 1.0802 | Loss_slots: 0.3918 | Spent: 2.9 secs | LR: 0.000160
INFO:tensorflow:Step 18250 | Loss: 1.4054 | Loss_intent: 1.0810 | Loss_slots: 0.3244 | Spent: 3.0 secs | LR: 0.000158
INFO:tensorflow:Step 18300 | Loss: 1.4288 | Loss_intent: 1.0806 | Loss_slots: 0.3482 | Spent: 3.1 secs | LR: 0.000157
INFO:tensorflow:Step 18350 | Loss: 1.4998 | Loss_intent: 1.0807 | Loss_slots: 0.4191 | Spent: 3.2 secs | LR: 0.000155
INFO:tensorflow:Step 18400 | Loss: 1.3268 | Loss_intent: 1.0828 | Loss_slots: 0.2440 | Spent: 3.2 secs | LR: 0.000153
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.952, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 18450 | Loss: 1.4274 | Loss_intent: 1.0817 | Loss_slots: 0.3457 | Spent: 5.5 secs | LR: 0.000151
INFO:tensorflow:Step 18500 | Loss: 1.4332 | Loss_intent: 1.0799 | Loss_slots: 0.3533 | Spent: 3.0 secs | LR: 0.000150
INFO:tensorflow:Step 18550 | Loss: 1.3983 | Loss_intent: 1.0856 | Loss_slots: 0.3127 | Spent: 3.0 secs | LR: 0.000148
INFO:tensorflow:Step 18600 | Loss: 1.4488 | Loss_intent: 1.0810 | Loss_slots: 0.3679 | Spent: 3.0 secs | LR: 0.000146
INFO:tensorflow:Step 18650 | Loss: 1.4125 | Loss_intent: 1.0873 | Loss_slots: 0.3252 | Spent: 2.9 secs | LR: 0.000144
INFO:tensorflow:Step 18700 | Loss: 1.4413 | Loss_intent: 1.0804 | Loss_slots: 0.3609 | Spent: 3.0 secs | LR: 0.000143
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.953, Intent Acc: 0.964
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 18750 | Loss: 1.5198 | Loss_intent: 1.0801 | Loss_slots: 0.4397 | Spent: 5.2 secs | LR: 0.000141
INFO:tensorflow:Step 18800 | Loss: 1.4481 | Loss_intent: 1.0811 | Loss_slots: 0.3670 | Spent: 3.0 secs | LR: 0.000139
INFO:tensorflow:Step 18850 | Loss: 1.4266 | Loss_intent: 1.0805 | Loss_slots: 0.3461 | Spent: 3.0 secs | LR: 0.000137
INFO:tensorflow:Step 18900 | Loss: 1.4505 | Loss_intent: 1.0811 | Loss_slots: 0.3693 | Spent: 3.0 secs | LR: 0.000136
INFO:tensorflow:Step 18950 | Loss: 1.3408 | Loss_intent: 1.0815 | Loss_slots: 0.2594 | Spent: 3.0 secs | LR: 0.000134
INFO:tensorflow:Step 19000 | Loss: 1.4515 | Loss_intent: 1.0818 | Loss_slots: 0.3696 | Spent: 3.0 secs | LR: 0.000132
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.965
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 19050 | Loss: 1.4843 | Loss_intent: 1.0802 | Loss_slots: 0.4041 | Spent: 5.3 secs | LR: 0.000130
INFO:tensorflow:Step 19100 | Loss: 1.2607 | Loss_intent: 1.0806 | Loss_slots: 0.1801 | Spent: 3.0 secs | LR: 0.000129
INFO:tensorflow:Step 19150 | Loss: 1.3385 | Loss_intent: 1.0823 | Loss_slots: 0.2562 | Spent: 3.0 secs | LR: 0.000127
INFO:tensorflow:Step 19200 | Loss: 1.3934 | Loss_intent: 1.0808 | Loss_slots: 0.3126 | Spent: 3.0 secs | LR: 0.000125
INFO:tensorflow:Step 19250 | Loss: 1.4827 | Loss_intent: 1.0804 | Loss_slots: 0.4023 | Spent: 2.9 secs | LR: 0.000123
INFO:tensorflow:Step 19300 | Loss: 1.4125 | Loss_intent: 1.0819 | Loss_slots: 0.3306 | Spent: 3.0 secs | LR: 0.000122
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.966
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 19350 | Loss: 1.4294 | Loss_intent: 1.0803 | Loss_slots: 0.3490 | Spent: 5.2 secs | LR: 0.000120
INFO:tensorflow:Step 19400 | Loss: 1.3484 | Loss_intent: 1.0802 | Loss_slots: 0.2682 | Spent: 3.0 secs | LR: 0.000118
INFO:tensorflow:Step 19450 | Loss: 1.4552 | Loss_intent: 1.0817 | Loss_slots: 0.3735 | Spent: 3.0 secs | LR: 0.000116
INFO:tensorflow:Step 19500 | Loss: 1.3786 | Loss_intent: 1.0813 | Loss_slots: 0.2973 | Spent: 2.9 secs | LR: 0.000114
INFO:tensorflow:Step 19550 | Loss: 1.2916 | Loss_intent: 1.0807 | Loss_slots: 0.2109 | Spent: 2.9 secs | LR: 0.000113
INFO:tensorflow:Step 19600 | Loss: 1.4558 | Loss_intent: 1.0813 | Loss_slots: 0.3745 | Spent: 2.9 secs | LR: 0.000111
INFO:tensorflow:Step 19650 | Loss: 1.2697 | Loss_intent: 1.0801 | Loss_slots: 0.1896 | Spent: 3.0 secs | LR: 0.000109
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.955, Intent Acc: 0.961
INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965
Reading ../data/atis.train.w-intent.iob
INFO:tensorflow:Step 19700 | Loss: 1.3726 | Loss_intent: 1.0811 | Loss_slots: 0.2915 | Spent: 5.2 secs | LR: 0.000107
INFO:tensorflow:Step 19750 | Loss: 1.3401 | Loss_intent: 1.0807 | Loss_slots: 0.2594 | Spent: 2.9 secs | LR: 0.000106
INFO:tensorflow:Step 19800 | Loss: 1.4026 | Loss_intent: 1.0832 | Loss_slots: 0.3194 | Spent: 3.0 secs | LR: 0.000104
INFO:tensorflow:Step 19850 | Loss: 1.3597 | Loss_intent: 1.0801 | Loss_slots: 0.2796 | Spent: 3.0 secs | LR: 0.000102
INFO:tensorflow:Step 19900 | Loss: 1.3378 | Loss_intent: 1.0800 | Loss_slots: 0.2578 | Spent: 3.0 secs | LR: 0.000100
INFO:tensorflow:Step 19950 | Loss: 1.4364 | Loss_intent: 1.0804 | Loss_slots: 0.3560 | Spent: 3.0 secs | LR: 0.000101
Reading ../data/atis.test.w-intent.iob
INFO:tensorflow:Slot F1: 0.954, Intent Acc: 0.962
INFO:tensorflow:
                                          precision    recall  f1-score   support

                             atis_flight      0.972     0.983     0.977       632
                            atis_airfare      0.980     1.000     0.990        48
                     atis_ground_service      0.973     1.000     0.986        36
                            atis_airline      1.000     0.974     0.987        38
                       atis_abbreviation      1.000     0.848     0.918        33
                           atis_aircraft      1.000     0.889     0.941         9
                        atis_flight_time      1.000     1.000     1.000         1
                           atis_quantity      0.429     1.000     0.600         3
                atis_flight#atis_airfare      0.833     0.417     0.556        12
                            atis_airport      0.900     1.000     0.947        18
                           atis_distance      1.000     1.000     1.000        10
                               atis_city      0.500     0.667     0.571         6
                        atis_ground_fare      1.000     0.857     0.923         7
                           atis_capacity      1.000     1.000     1.000        21
                          atis_flight_no      0.889     1.000     0.941         8
                               atis_meal      0.833     0.833     0.833         6
                        atis_restriction      0.000     0.000     0.000         0
             atis_airline#atis_flight_no      0.000     0.000     0.000         0
    atis_ground_service#atis_ground_fare      0.000     0.000     0.000         0
           atis_airfare#atis_flight_time      0.000     0.000     0.000         0
                           atis_cheapest      0.000     0.000     0.000         0
atis_aircraft#atis_flight#atis_flight_no      0.000     0.000     0.000         0

                               micro avg      0.962     0.967     0.965       888
                               macro avg      0.650     0.658     0.644       888
                            weighted avg      0.966     0.967     0.965       888

INFO:tensorflow:
                              precision    recall  f1-score   support

                           O      0.000     0.000     0.000       0.0
           B-toloc.city_name      0.977     0.996     0.986     716.0
         B-fromloc.city_name      0.990     0.997     0.994     704.0
           I-toloc.city_name      0.971     0.996     0.983     265.0
      B-depart_date.day_name      0.990     0.981     0.986     212.0
              B-airline_name      0.981     1.000     0.990     101.0
         I-fromloc.city_name      0.978     0.994     0.986     177.0
 B-depart_time.period_of_day      1.000     0.892     0.943     130.0
              I-airline_name      1.000     1.000     1.000      65.0
    B-depart_date.day_number      0.981     0.964     0.972      55.0
    B-depart_date.month_name      0.982     0.964     0.973      56.0
          B-depart_time.time      0.838     1.000     0.912      57.0
                B-round_trip      1.000     0.986     0.993      73.0
             B-cost_relative      1.000     0.973     0.986      37.0
                I-round_trip      1.000     1.000     1.000      71.0
                B-flight_mod      0.960     1.000     0.980      24.0
 B-depart_time.time_relative      0.984     0.969     0.977      65.0
          I-depart_time.time      0.897     1.000     0.945      52.0
         B-stoploc.city_name      1.000     1.000     1.000      20.0
                 B-city_name      0.868     0.579     0.695      57.0
                B-class_type      0.960     1.000     0.980      24.0
          B-arrive_time.time      0.943     0.971     0.957      34.0
 B-arrive_time.time_relative      0.857     0.968     0.909      31.0
                I-class_type      1.000     1.000     1.000      17.0
               B-flight_stop      1.000     1.000     1.000      21.0
          I-arrive_time.time      0.971     0.971     0.971      35.0
              B-airline_code      1.000     0.941     0.970      34.0
    I-depart_date.day_number      1.000     1.000     1.000      15.0
      I-fromloc.airport_name      0.405     1.000     0.577      15.0
      B-fromloc.airport_name      0.423     0.917     0.579      12.0
      B-arrive_date.day_name      0.688     1.000     0.815      11.0
          B-toloc.state_code      1.000     1.000     1.000      18.0
B-depart_date.today_relative      1.000     1.000     1.000       9.0
             B-flight_number      0.526     0.909     0.667      11.0
 B-depart_date.date_relative      0.944     1.000     0.971      17.0
          B-toloc.state_name      0.966     1.000     0.982      28.0
           B-fare_basis_code      0.944     1.000     0.971      17.0
               B-flight_time      1.000     1.000     1.000       1.0
                        B-or      1.000     1.000     1.000       3.0
 B-arrive_time.period_of_day      0.750     1.000     0.857       6.0
          B-meal_description      1.000     0.900     0.947      10.0
             I-cost_relative      1.000     0.667     0.800       3.0
              I-airport_name      0.909     0.345     0.500      29.0
               B-fare_amount      0.400     1.000     0.571       2.0
               I-fare_amount      1.000     1.000     1.000       2.0
                 I-city_name      1.000     0.533     0.696      30.0
        I-toloc.airport_name      1.000     1.000     1.000       3.0
            B-transport_type      1.000     1.000     1.000      10.0
    B-arrive_date.month_name      0.714     0.833     0.769       6.0
    B-arrive_date.day_number      0.714     0.833     0.769       6.0
         I-stoploc.city_name      1.000     0.900     0.947      10.0
                      B-meal      1.000     1.000     1.000      16.0
        B-fromloc.state_code      1.000     1.000     1.000      23.0
    B-depart_time.period_mod      0.833     1.000     0.909       5.0
                   B-connect      1.000     1.000     1.000       6.0
               B-flight_days      1.000     1.000     1.000      10.0
        B-toloc.airport_name      1.000     1.000     1.000       3.0
        B-fromloc.state_name      0.944     1.000     0.971      17.0
              B-airport_name      0.500     0.333     0.400      21.0
                   B-economy      1.000     1.000     1.000       6.0
               I-flight_time      1.000     1.000     1.000       1.0
             B-aircraft_code      1.000     0.818     0.900      33.0
                       B-mod      1.000     0.500     0.667       2.0
              B-airport_code      0.000     0.000     0.000       9.0
    B-depart_time.start_time      0.667     0.667     0.667       3.0
      B-depart_time.end_time      1.000     0.667     0.800       3.0
          B-depart_date.year      1.000     0.667     0.800       3.0
            I-transport_type      1.000     1.000     1.000       1.0
          B-restriction_code      0.333     1.000     0.500       4.0
    B-arrive_time.start_time      0.889     1.000     0.941       8.0
        B-toloc.airport_code      1.000     0.750     0.857       4.0
      B-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-arrive_time.end_time      0.875     0.875     0.875       8.0
      I-depart_time.end_time      1.000     0.667     0.800       3.0
               I-flight_stop      0.000     0.000     0.000       0.0
      B-fromloc.airport_code      0.833     1.000     0.909       5.0
          I-restriction_code      1.000     1.000     1.000       3.0
    I-depart_time.start_time      1.000     1.000     1.000       1.0
          I-toloc.state_name      1.000     1.000     1.000       1.0
I-depart_date.today_relative      0.000     0.000     0.000       0.0
 B-arrive_date.date_relative      1.000     1.000     1.000       2.0
                I-flight_mod      1.000     0.167     0.286       6.0
                   I-economy      0.000     0.000     0.000       0.0
 B-return_date.date_relative      1.000     0.333     0.500       3.0
        I-fromloc.state_name      1.000     1.000     1.000       1.0
                B-state_code      1.000     1.000     1.000       1.0
    I-arrive_time.start_time      1.000     1.000     1.000       1.0
    I-arrive_date.day_number      0.000     0.000     0.000       0.0
                 B-meal_code      1.000     1.000     1.000       1.0
 I-depart_time.period_of_day      1.000     1.000     1.000       1.0
                  B-day_name      1.000     0.500     0.667       2.0
             B-period_of_day      1.000     0.500     0.667       4.0
        B-stoploc.state_code      0.000     0.000     0.000       0.0
    B-return_date.month_name      0.000     0.000     0.000       0.0
    B-return_date.day_number      0.000     0.000     0.000       0.0
    B-arrive_time.period_mod      0.000     0.000     0.000       0.0
                 I-meal_code      0.000     0.000     0.000       0.0
        B-toloc.country_name      1.000     1.000     1.000       1.0
                 B-days_code      1.000     1.000     1.000       1.0
 I-arrive_time.period_of_day      0.000     0.000     0.000       0.0
            I-today_relative      0.000     0.000     0.000       0.0
 B-return_time.period_of_day      0.000     0.000     0.000       0.0
                      B-time      0.000     0.000     0.000       0.0
           I-fare_basis_code      0.000     0.000     0.000       0.0
 I-arrive_time.time_relative      0.000     0.000     0.000       4.0
 I-depart_time.time_relative      0.000     0.000     0.000       1.0
            B-today_relative      0.000     0.000     0.000       0.0
                B-state_name      0.000     0.000     0.000       9.0
B-arrive_date.today_relative      0.000     0.000     0.000       0.0
    B-return_time.period_mod      0.000     0.000     0.000       0.0
                B-month_name      0.000     0.000     0.000       0.0
                B-day_number      0.000     0.000     0.000       0.0
 I-return_date.date_relative      0.750     1.000     0.857       3.0
I-return_date.today_relative      0.000     0.000     0.000       0.0
      B-stoploc.airport_name      0.000     0.000     0.000       0.0
             B-time_relative      0.000     0.000     0.000       0.0
                      I-time      0.000     0.000     0.000       0.0
    I-return_date.day_number      0.000     0.000     0.000       0.0
          I-meal_description      0.000     0.000     0.000       0.0
B-return_date.today_relative      0.000     0.000     0.000       0.0
      B-return_date.day_name      0.000     0.000     0.000       2.0

                   micro avg      0.953     0.955     0.954    3657.0
                   macro avg      0.678     0.664     0.656    3657.0
                weighted avg      0.958     0.955     0.951    3657.0

INFO:tensorflow:Best Slot F1: 0.955, Intent Acc: 0.965