music-recommendation-system's Issues
Loss Always Not Change
Use Softmax on the Output Layer, the loss is only decreased a little
with tf.name_scope('loss'):
log_loss = tf.nn.softmax_cross_entropy_with_logits(logits=self.Output, labels=self.onehot_label)
self.loss = tf.reduce_mean(log_loss)
with tf.name_scope('OUTPUT_LAYER'):
initial_value = tf.truncated_normal([self.FC_output.shape[1].value, self.output_dim],
stddev=0.1)
self.output_weight = tf.Variable(initial_value, name='output_weight')
self.output_bais = tf.Variable(tf.zeros(shape=[self.output_dim]), name='output_bais')
self.Output = tf.matmul(self.FC_output, self.output_weight) + self.output_bais
self.Output = tf.nn.softmax(self.Output)
print('Output')
print(self.Output.shape)
Recommendation_Model.Accuracy is Repeated
accuracy(self) and self.accuracy is Repeated
So the accuracy is always 0 or 1
Figure out the difference between of tf.metrics.accuracy
and the accuracy function
def accuracy(self):
# Calculate accuracy
with tf.name_scope('accuracy'):
predictions = tf.argmax(self.Output, 1, name='predictions')
correct_pred = tf.equal(predictions, tf.argmax(self.onehot_label, 1))
self.accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
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