Cant get LSTM model to give required predictions
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Describe the feature and the current behavior/state. I built a model which can predict parts of speech of words when given separately. Now I am building a model which can predict parts of speech of words in sentences. For this i have created two arrays. 1st Array(Input train) - which has sentences tokenized as arrays[14,546,789,4556](words as sequences, There are many arrays like this representing sentences), 2nd Array- Arrays of parts of speech of each word in14,7,3,21(respective parts of speech as sequences), .Both words and parts and speech are converted to sequences
CODE
model = tf.keras.Sequential()
model.add(tf.keras.layers.Embedding(input_dim=11040,output_dim=64,
input_length= 30, batch_input_shape=[128,None]))
model.add(tf.keras.layers.LSTM(30, activation='tanh',
recurrent_activation='hard_sigmoid',
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',stateful = True))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(30)) model.summary()
PROBLEM
It is returning a single array where each element in the predicted array represents a whole sentences where it should give array of parts of speech for each sentence in the input. Please tell me how to change the model and why. I am a beginner trying to learn machine learning.
machine-learning python keras tensorflow regression
asked 1 min ago
user56565user56565
1
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add a comment |
$begingroup$
Describe the feature and the current behavior/state. I built a model which can predict parts of speech of words when given separately. Now I am building a model which can predict parts of speech of words in sentences. For this i have created two arrays. 1st Array(Input train) - which has sentences tokenized as arrays[14,546,789,4556](words as sequences, There are many arrays like this representing sentences), 2nd Array- Arrays of parts of speech of each word in14,7,3,21(respective parts of speech as sequences), .Both words and parts and speech are converted to sequences
CODE
model = tf.keras.Sequential()
model.add(tf.keras.layers.Embedding(input_dim=11040,output_dim=64,
input_length= 30, batch_input_shape=[128,None]))
model.add(tf.keras.layers.LSTM(30, activation='tanh',
recurrent_activation='hard_sigmoid',
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',stateful = True))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(30)) model.summary()
PROBLEM
It is returning a single array where each element in the predicted array represents a whole sentences where it should give array of parts of speech for each sentence in the input. Please tell me how to change the model and why. I am a beginner trying to learn machine learning.
machine-learning python keras tensorflow regression
asked 1 min ago
user56565user56565
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
Describe the feature and the current behavior/state. I built a model which can predict parts of speech of words when given separately. Now I am building a model which can predict parts of speech of words in sentences. For this i have created two arrays. 1st Array(Input train) - which has sentences tokenized as arrays[14,546,789,4556](words as sequences, There are many arrays like this representing sentences), 2nd Array- Arrays of parts of speech of each word in14,7,3,21(respective parts of speech as sequences), .Both words and parts and speech are converted to sequences
CODE
model = tf.keras.Sequential()
model.add(tf.keras.layers.Embedding(input_dim=11040,output_dim=64,
input_length= 30, batch_input_shape=[128,None]))
model.add(tf.keras.layers.LSTM(30, activation='tanh',
recurrent_activation='hard_sigmoid',
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',stateful = True))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(30)) model.summary()
PROBLEM
It is returning a single array where each element in the predicted array represents a whole sentences where it should give array of parts of speech for each sentence in the input. Please tell me how to change the model and why. I am a beginner trying to learn machine learning.
machine-learning python keras tensorflow regression
asked 1 min ago
user56565user56565
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
Describe the feature and the current behavior/state. I built a model which can predict parts of speech of words when given separately. Now I am building a model which can predict parts of speech of words in sentences. For this i have created two arrays. 1st Array(Input train) - which has sentences tokenized as arrays[14,546,789,4556](words as sequences, There are many arrays like this representing sentences), 2nd Array- Arrays of parts of speech of each word in14,7,3,21(respective parts of speech as sequences), .Both words and parts and speech are converted to sequences
CODE
model = tf.keras.Sequential()
model.add(tf.keras.layers.Embedding(input_dim=11040,output_dim=64,
input_length= 30, batch_input_shape=[128,None]))
model.add(tf.keras.layers.LSTM(30, activation='tanh',
recurrent_activation='hard_sigmoid',
kernel_initializer='glorot_uniform',
recurrent_initializer='orthogonal',stateful = True))
model.add(tf.keras.layers.Flatten())
model.add(tf.keras.layers.Dense(30)) model.summary()
PROBLEM
It is returning a single array where each element in the predicted array represents a whole sentences where it should give array of parts of speech for each sentence in the input. Please tell me how to change the model and why. I am a beginner trying to learn machine learning.
machine-learning python keras tensorflow regression
machine-learning python keras tensorflow regression
asked 1 min ago
user56565user56565
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user56565user56565
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user56565user56565
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 1 min ago
user56565user56565
1
asked 1 min ago
user56565user56565
1
1
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
user56565 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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